Search results for: autonomous orbit determination

Authors: G. M. Hamada, A. A. Al-Gathe, A. M. Al-Khudafi

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Determination of water saturation in sandstone is a vital question to determine the initial oil or gas in place in reservoir rocks. Water saturation determination using electrical measurements is mainly on Archie’s formula. Consequently accuracy of Archie’s formula parameters affects water saturation values rigorously. Determination of Archie’s parameters a, m, and n is proceeded by three conventional techniques, Core Archie-Parameter Estimation (CAPE) and 3-D. This work introduces the hybrid system of parallel self-organizing neural network (PSONN) targeting accepted values of Archie’s parameters and, consequently, reliable water saturation values. This work focuses on Archie’s parameters determination techniques; conventional technique, CAPE technique, and 3-D technique, and then the calculation of water saturation using current. Using the same data, a hybrid parallel self-organizing neural network (PSONN) algorithm is used to estimate Archie’s parameters and predict water saturation. Results have shown that estimated Arche’s parameters m, a, and n are highly accepted with statistical analysis, indicating that the PSONN model has a lower statistical error and higher correlation coefficient. This study was conducted using a high number of measurement points for 144 core plugs from a sandstone reservoir. PSONN algorithm can provide reliable water saturation values, and it can supplement or even replace the conventional techniques to determine Archie’s parameters and thereby calculate water saturation profiles.

Keywords: water saturation, Archie’s parameters, artificial intelligence, PSONN, sandstone reservoir

Procedia PDF Downloads 106

Authors: N. Al-Orfi, M. S. El-Shahawi, A. S. Bashammakh

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The electrochemical response of glassy carbon electrode (GCE) for the sensitive and selective determination of dianabol steroid (DS) in phosphate, Britton-Robinson (B-R) and HEPES buffers of pH 2.0 - 11, 2.0 - 11 and 6.2 - 8.0, respectively using cyclic voltammetry (CV) and differential pulse- adsorptive cathodic stripping voltammetry (DP-CSV) at bare GCE was studied. The dependence of the CV response of the developed cathodic peak potential (Ep, c), peak current (ip, c) and the current function (ip, c / υ1/2) on the scan rate (υ) at the bare GCE revealed the occurrence of electrode coupled chemical reaction of EC type mechanism. The selectivity of the proposed method was assessed in the presence of high concentrations of major interfering species e.g. uric acid, ascorbic acid, citric acid, glucose, fructose, sucrose, starch and ions Na+, K+, PO4-3, NO3- and SO42-. The recovery of the method was not significant where t(critical)=2.20 > texp=1.81-1.93 at 95% confidence. The analytical application of the sensor for the quantification of DS in biological fluids as urine was investigated. The results were demonstrated as recovery percentages in the range 95±2.5-97±4.7% with relative standard deviation (RSD) of 0.5-1.5%.

Keywords: dianabol, determination, modified electrode, urine

Procedia PDF Downloads 246

Authors: Venkataramana Sovenahalli Badigar, B. M. Suryakanth, Akshar Prasanna, Karthik Veeramalai, Vishwak Ram Vishwak Ram

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Technological advances have led to widespread autonomy in vehicles. Empowering these autonomous with the intelligence to cooperate amongst themselves leads to a more efficient use of the resources available to them. This paper proposes a demonstration of a swarm algorithm implemented on a group of autonomous vehicles. The demonstration involves two ground bots and an aerial drone which cooperate amongst them to locate an object of interest. The object of interest is modelled using a high-intensity light source which acts as a beacon. The ground bots are light sensitive and move towards the beacon. The ground bots and the drone traverse in random paths and jointly locate the beacon. This finds application in various scenarios in where human interference is difficult such as search and rescue during natural disasters, delivering crucial packages in perilous situations, etc. Experimental results show that the modified swarm algorithm implemented in this system has better performance compared to fully random based moving algorithm for object localization and tracking.

Keywords: swarm algorithm, object localization, ground bots, drone, beacon

Procedia PDF Downloads 225

Authors: King Kumire, Amos Kubeka

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The synergy of machine learning and astronomical technology advancement is giving rise to the new space age, which is pronounced by better habitability assessments. To initiate this discussion, it should be recorded for definition purposes that the symbiotic relationship between astronomy and improved computing has been code-named the Cis-Astro gateway concept. The cosmological fate of this phrase has been unashamedly plagiarized from the cis-lunar gateway template and its associated LaGrange points which act as an orbital bridge to the moon from our planet Earth. However, for this study, the scientific audience is invited to bridge toward the discovery of new habitable planets. It is imperative to state that cosmic probes of this magnitude can be utilized as the starting nodes of the astrobiological search for galactic life. This research can also assist by acting as the navigation system for future space telescope launches through the delimitation of target exoplanets. The findings and the associated platforms can be harnessed as building blocks for the modeling of climate change on planet earth. The notion that if the human genus exhausts the resources of the planet earth or there is a bug of some sort that makes the earth inhabitable for humans explains the need to find an alternative planet to inhabit. The scientific community, through interdisciplinary discussions of the International Astronautical Federation so far has the common position that engineers can reduce space mission costs by constructing a stable cis-lunar orbit infrastructure for refilling and carrying out other associated in-orbit servicing activities. Similarly, the Cis-Astro gateway can be envisaged as a budget optimization technique that models extra-solar bodies and can facilitate the scoping of future mission rendezvous. It should be registered as well that this broad and voluminous catalog of exoplanets shall be narrowed along the way using machine learning filters. The gist of this topic revolves around the indirect economic rationale of establishing a habitability scoping platform.

Keywords: machine-learning, habitability, exoplanets, supercomputing

Procedia PDF Downloads 59

Authors: King Kumire, Amos Kubeka

Abstract:

The synergy of machine learning and astronomical technology advancement is giving rise to the new space age, which is pronounced by better habitability assessments. To initiate this discussion, it should be recorded for definition purposes that the symbiotic relationship between astronomy and improved computing has been code-named the Cis-Astro gateway concept. The cosmological fate of this phrase has been unashamedly plagiarized from the cis-lunar gateway template and its associated LaGrange points which act as an orbital bridge to the moon from our planet Earth. However, for this study, the scientific audience is invited to bridge toward the discovery of new habitable planets. It is imperative to state that cosmic probes of this magnitude can be utilized as the starting nodes of the astrobiological search for galactic life. This research can also assist by acting as the navigation system for future space telescope launches through the delimitation of target exoplanets. The findings and the associated platforms can be harnessed as building blocks for the modeling of climate change on planet earth. The notion that if the human genus exhausts the resources of the planet earth or there is a bug of some sort that makes the earth inhabitable for humans explains the need to find an alternative planet to inhabit. The scientific community, through interdisciplinary discussions of the International Astronautical Federation so far, has the common position that engineers can reduce space mission costs by constructing a stable cis-lunar orbit infrastructure for refilling and carrying out other associated in-orbit servicing activities. Similarly, the Cis-Astro gateway can be envisaged as a budget optimization technique that models extra-solar bodies and can facilitate the scoping of future mission rendezvous. It should be registered as well that this broad and voluminous catalog of exoplanets shall be narrowed along the way using machine learning filters. The gist of this topic revolves around the indirect economic rationale of establishing a habitability scoping platform.

Keywords: exoplanets, habitability, machine-learning, supercomputing

Procedia PDF Downloads 78

Authors: David L. Olson, Stephen B. H. Bruder, Adam S. Watkins, Cleon E. Davis

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In global navigation satellite systems (GNSS), denied settings such as indoor environments, autonomous mobile robots are often limited to dead-reckoning navigation techniques to determine their position, velocity, and attitude (PVA). Localization is typically accomplished by employing an inertial measurement unit (IMU), which, while precise in nature, accumulates errors rapidly and severely degrades the localization solution. Standard sensor fusion methods, such as Kalman filtering, aim to fuse precise IMU measurements with accurate aiding sensors to establish a precise and accurate solution. In indoor environments, where GNSS and no other a priori information is known about the environment, effective sensor fusion is difficult to achieve, as accurate aiding sensor choices are sparse. However, an opportunity arises by employing a depth camera in the indoor environment. A depth camera can capture point clouds of the surrounding floors and walls. Extracting attitude from these surfaces can serve as an accurate aiding source, which directly combats errors that arise due to gyroscope imperfections. This configuration for sensor fusion leads to a dramatic reduction of PVA error compared to traditional aiding sensor configurations. This paper provides the theoretical basis for the depth camera aiding sensor method, initial expectations of performance benefit via simulation, and hardware implementation, thus verifying its veracity. Hardware implementation is performed on the Quanser Qbot 2™ mobile robot, with a Vector-Nav VN-200™ IMU and Kinect™ camera from Microsoft.

Keywords: autonomous mobile robotics, dead reckoning, depth camera, inertial navigation, Kalman filtering, localization, sensor fusion

Procedia PDF Downloads 180

Authors: Hanadi Mohamed Shawgi Gamal, Claus Thomas Bues

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Wood density is a variable influencing many of the technological and quality properties of wood. Understanding the pattern of wood density radial variation is important for its end-use. The X-ray technique, traditionally applied to softwood species to assess the wood quality properties, due to its simple and relatively uniform wood structure. On the other hand, very limited information is available about the validation of using this technique for hardwood species. The suitability of using the X-ray technique for the determination of hardwood density has a special significance in countries like Sudan, where only a few timbers are well known. This will not only save the time consumed by using the traditional methods, but it will also enhance the investigations of the great number of the lesser known species, the thing which will fill the huge cap of lake information of hardwood species growing in Sudan. The current study aimed to evaluate the validation of using the X-ray densitometry technique to determine the radial variation of wood density of Acacia seyal var. seyal. To this, a total of thirty trees were collected randomly from four states in Sudan. The wood density radial trend was determined using the basic density as well as density obtained by the X-ray densitometry method in order to assess the validation of X-ray technique in wood density radial variation determination. The results showed that the pattern of radial trend of density obtained by X-ray technique is very similar to that achieved by basic density. These results confirmed the validation of using the X-ray technique for Acacia seyal var. seyal density radial trend determination. It also promotes the suitability of using this method in other hardwood species.

Keywords: x-ray densitometry, wood density, Acacia seyal var. seyal, radial variation

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Authors: Ruby Jean Hornsby

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In our rapidly advancing techno-moral world, human-robot relationships are increasingly becoming a part of intimate human life. Indeed, social robots - that is, autonomous or semi-autonomous embodied artificial agents that generally possess human or animal-like qualities (such as responding to environmental stimuli, communicating, learning, performing human tasks, and making autonomous decisions) - have been designed to function as human friends. In light of such advances, immediate philosophical scrutiny is imperative in order to examine the extent to which human-robot interactions constitute genuine friendship and therefore contribute towards the good human life. Aristotle's conception of friendship is philosophically illuminating and sufficiently broad in scope to guide such analysis. On his account, it is necessary (though not sufficient) that for a friendship to exist between two agents - A and B - both agents must have a mutual love for one another. Aristotle claims that A loves B if: Condition 1: A desires those apparent good (qua pleasant, useful, or virtuous) properties attributable to B, and Condition 2: A has goodwill (wishes what is best) for B. This paper argues that human-robot interaction can (and does) successfully meet both conditions; as such, it demonstrates that robots and humans can reciprocally love one another. It will argue for this position by first justifying the claim that a human can desire apparent good features attributable to a robot (i.e., by taking them to be pleasant and/or useful) and outlining how it is that a human can wish a robot well in light of that robot's (quasi-) interests. Next, the paper will argue that a robot can (quasi-)desire certain properties that are attributable to a human before elucidating how it is possible for a robot to act in the interests of a human. Accordingly, this paper will conclude that it is already the case that humans can formulate relationships with robots that involve reciprocated love. This is significant because it suggests that social robots are candidates for human friendship and can therefore contribute toward flourishing human futures.

Keywords: ancient philosophy, friendship, inter-disciplinary applied ethics, love, social robotics

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Authors: Hung-Yuan Chang, Wen-Lung Chiang, Kuo-Liang Wu, Chen-Tsung Lin

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National Space Organization (NSPO) has completed in 2014 the development of a space-borne GPS receiver, including design, manufacture, comprehensive functional test, environmental qualification test and so on. The main performance of this receiver include 8-meter positioning accuracy, 0.05 m/sec speed-accuracy, the longest 90 seconds of cold start time, and up to 15g high dynamic scenario. The receiver will be integrated in the autonomous FORMOSAT-7 NSPO-Built satellite scheduled to be launched in 2019 to execute pre-defined scientific missions. The flight model of this receiver manufactured in early 2015 will pass comprehensive functional tests and environmental acceptance tests, etc., which are expected to be completed by the end of 2015. The space-borne GPS receiver is a pure software design in which all GPS baseband signal processing are executed by a digital signal processor (DSP), currently only 50% of its throughput being used. In response to the booming global navigation satellite systems, NSPO will gradually expand this receiver to become a multi-mode, multi-band, high-precision navigation receiver, and even a science payload, such as the reflectometry receiver of a global navigation satellite system. The fundamental purpose of this extension study is to port some software algorithms such as signal acquisition and correlation, reused code and large amount of computation load to the FPGA whose processor is responsible for operational control, navigation solution, and orbit propagation and so on. Due to the development and evolution of the FPGA is pretty fast, the new system architecture upgraded via an FPGA should be able to achieve the goal of being a multi-mode, multi-band high-precision navigation receiver, or scientific receiver. Finally, the results of tests show that the new system architecture not only retains the original overall performance, but also sets aside more resources available for future expansion possibility. This paper will explain the detailed DSP/FPGA architecture, development, test results, and the goals of next development stage of this receiver.

Keywords: space-borne, GPS receiver, DSP, FPGA, multi-mode multi-band

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Authors: Divya Agarwal, Pushpendra S. Bharti

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Autonomous mobile robots (AMR) are expected as smart tools for operations in every automation industry. Path planning and obstacle avoidance is the backbone of AMR as robots have to reach their goal location avoiding obstacles while traversing through optimized path defined according to some criteria such as distance, time or energy. Path planning can be classified into global and local path planning where environmental information is known and unknown/partially known, respectively. A number of sensors are used for data collection. A number of algorithms such as artificial potential field (APF), rapidly exploring random trees (RRT), bidirectional RRT, Fuzzy approach, Purepursuit, A* algorithm, vector field histogram (VFH) and modified local path planning algorithm, etc. have been used in the last three decades for path planning and obstacle avoidance for AMR. This paper makes an attempt to review some of the path planning and obstacle avoidance algorithms used in the field of AMR. The review includes comparative analysis of simulation and mathematical computations of path planning and obstacle avoidance algorithms using MATLAB 2018a. From the review, it could be concluded that different algorithms may complete the same task (i.e. with a different set of instructions) in less or more time, space, effort, etc.

Keywords: path planning, obstacle avoidance, autonomous mobile robots, algorithms

Procedia PDF Downloads 200

Authors: Yangzhi Li

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Network transfer of information and performance customization is now a viable method of digital industrial production in the era of Industry 4.0. Robot platforms and network platforms have grown more important in digital design and construction. The pressing need for novel building techniques is driven by the growing labor scarcity problem and increased awareness of construction safety. Robotic approaches in construction research are regarded as an extension of operational and production tools. Several technological theories related to robot autonomous recognition, which include high-performance computing, physical system modeling, extensive sensor coordination, and dataset deep learning, have not been explored using intelligent construction. Relevant transdisciplinary theory and practice research still has specific gaps. Optimizing high-performance computing and autonomous recognition visual guidance technologies improves the robot's grasp of the scene and capacity for autonomous operation. Intelligent vision guidance technology for industrial robots has a serious issue with camera calibration, and the use of intelligent visual guiding and identification technologies for industrial robots in industrial production has strict accuracy requirements. It can be considered that visual recognition systems have challenges with precision issues. In such a situation, it will directly impact the effectiveness and standard of industrial production, necessitating a strengthening of the visual guiding study on positioning precision in recognition technology. To best facilitate the handling of complicated components, an approach for the visual recognition of parts utilizing machine learning algorithms is proposed. This study will identify the position of target components by detecting the information at the boundary and corner of a dense point cloud and determining the aspect ratio in accordance with the guidelines for the modularization of building components. To collect and use components, operational processing systems assign them to the same coordinate system based on their locations and postures. The RGB image's inclination detection and the depth image's verification will be used to determine the component's present posture. Finally, a virtual environment model for the robot's obstacle-avoidance route will be constructed using the point cloud information.

Keywords: robotic construction, robotic assembly, visual guidance, machine learning

Procedia PDF Downloads 54

Authors: Shakirat Abimbola Adesola, Shuaib Akintunde Asifat, Jelili Olalekan Amoo

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This paper presented the impact of students’ emotions on learning when receiving lectures and when taking tests. It was observed that students experience different types of emotions during the study, and this was found to have a significant effect on their academic performance. A total of one thousand six hundred and seventy-five (1675) students from the department of Computer Science in two Colleges of Education in South-West Nigeria took part in this study. The students were randomly selected for the research. Sample comprises of 968 males representing 58%, and 707 females representing 42%. A structured questionnaire, of Motivated Strategies for Learning Questionnaire (MSLQ) was distributed to the participants to obtain their opinions. Data gathered were analyzed using the IBM SPSS 20 to obtain ANOVA, descriptive analysis, stepwise regression, and reliability tests. The results revealed that emotion moderately shape students’ motivation and engagement in learning; and that self-regulation and self-determination do have significant impact on academic performance. It was further revealed that test anxiety has a significant correlation with academic performance.

Keywords: motivation, self-determination, test anxiety, academic performance, and academic engagement

Procedia PDF Downloads 56

Authors: R. B. Mishra

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Hidden Markov Model (HMM) has been used in prediction and determination of states that generate different neural activations as well as mental working conditions. This paper addresses two applications of HMM; one to determine the optimal sequence of states for two neural states: Active (AC) and Inactive (IA) for the three emission (observations) which are for No Working (NW), Waiting (WT) and Working (W) conditions of human beings. Another is for the determination of optimal sequence of intentionality i.e. Believe (B), Desire (D), and Intention (I) as the states and three observational sequences: NW, WT and W. The computational results are encouraging and useful.

Keywords: hiden markov model, believe desire intention, neural activation, simulation

Procedia PDF Downloads 349

Authors: Loha Hashimy, Isabella Castillo

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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 49

Authors: Chi C. Lin, Chih. H. Hsieh, Chi H. Lin

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The present study attempted to develop and test a self-determination theory dual-process model among teachers’ need supportive teaching, need thwarting teaching, and students’ need satisfaction, need frustration, and motivation regulation on vocational high school learners. This study adopted a survey questionnaire method. Participants were 736 (472 males, 264 females) vocational high school students in Taiwan. The instrument included five sets: the Teachers’ Need Supportive Teaching Scale, the Teachers’ Need Thwart Teaching Scale, the Need Satisfaction Scale, the Need Frustration Scale, and the Motivational Regulation Scale. A Structural equation modeling was used for the data analyses, results indicated that (1) teachers’ need supportive teaching had direct effects on students’ need satisfaction; (2) teachers’ thwarting teaching also had a direct effect on students’ need frustration; (3) teachers’ need supportive teaching had a negative direct effect on students’ need frustration; (4) students’ need satisfaction had direct effects on their autonomous motivation and control motivation, respectively; (5) students’ need frustration also had direct effects on their control motivation and motivation, respectively; (6) the model proposed in this study fit mostly with the empirical data.

Keywords: motivational regulation, need satisfaction, need frustration, supportive teaching, thwart teaching, vocational high school students

Procedia PDF Downloads 106

Authors: Ebrahim Behrouzian Nejad, Rezvan Alipoor Sabzevari

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Cloud computing systems are large-scale distributed systems, so that they focus more on large scale resource sharing, cooperation of several organizations and their use in new applications. One of the main challenges in this realm is resource allocation. There are many different ways to resource allocation in cloud computing. One of the common methods to resource allocation are economic methods. Among these methods, the auction-based method has greater prominence compared with Fixed-Price method. The double combinatorial auction is one of the proper ways of resource allocation in cloud computing. This method includes two phases: winner determination and resource allocation. In this paper a new method has been presented to determine winner in double combinatorial auction-based resource allocation using Imperialist Competitive Algorithm (ICA). The experimental results show that in our new proposed the number of winner users is higher than genetic algorithm. On other hand, in proposed algorithm, the number of winner providers is higher in genetic algorithm.

Keywords: cloud computing, resource allocation, double auction, winner determination

Procedia PDF Downloads 334

Authors: Mohammad Y. Abualhoul, Edgar Talavera Munoz, Fawzi Nashashibi

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The new emerging Visible Light Communication (VLC) technology has been subjected to intensive investigation, evaluation, and lately, deployed in the context of convoy-based applications for Intelligent Transportations Systems (ITS). The technology limitations were defined and supported by different solutions proposals to enhance the crucial alignment and mobility limitations. In this paper, we propose the incorporation of VLC technology and Lane-Centering (LC) technique to assure the VLC-connectivity by keeping the autonomous vehicle aligned to the lane center using vision-based lane detection in a convoy-based formation. Such combination can ensure the optical communication connectivity with a lateral error less than 30 cm. As soon as the road lanes are detectable, the evaluated system showed stable behavior independently from the inter-vehicle distances and without the need for any exchanged information of the remote vehicles. The evaluation of the proposed system is verified using VLC prototype and an empirical result of LC running application over 60 km in Madrid M40 highway.

Keywords: visible light communication, lane-centerin, platooning, intelligent transportation systems, road safety applications

Procedia PDF Downloads 142

Authors: Michael Naderhirn, Marco Pavone

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Problem statement, motivation, and aim of work: So far, the development of control algorithms was done by control engineers in a way that the controller would fit a specification by testing. When it comes to the certification of an autonomous car in highly complex scenarios, the challenge is much higher since such a controller must mathematically guarantee to implement the rules of the road while on the other side guarantee aspects like safety and real time executability. What if it becomes reality to solve this demanding problem by combining Formal Verification and System Theory? The aim of this work is to present a workflow to solve the above mentioned problem. Summary of the presented results / main outcomes: We show the usage of an English like language to transform the rules of the road into system specification for an autonomous car. The language based specifications are used to define system functions and interfaces. Based on that a formal model is developed which formally correctly models the specifications. On the other side, a mathematical model describing the systems dynamics is used to calculate the systems reachability set which is further used to determine the system input boundaries. Then a motion planning algorithm is applied inside the system boundaries to find an optimized trajectory in combination with the formal specification model while satisfying the specifications. The result is a control strategy which can be applied in real time independent of the scenario with a mathematical guarantee to satisfy a predefined specification. We demonstrate the applicability of the method in simulation driving scenarios and a potential certification. Originality, significance, and benefit: To the authors’ best knowledge, it is the first time that it is possible to show an automated workflow which combines a specification in an English like language and a mathematical model in a mathematical formal verified way to synthesizes a controller for potential real time applications like autonomous driving.

Keywords: formal system verification, reachability, real time controller, hybrid system

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Authors: Ahmad Almutairi

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Kuwait lies to the northwest of the Arabian Gulf. The levels of radionuclides are unknown in this area. Radionuclide like ²¹⁰Po, ²²⁶Ra, and ⁹⁰Sr accumulated in certain body tissues and bones, relate primarily to dietary uptake and inhalation. A large fraction of radiation exposure experienced by individuals comes from food chain transfer. In this study, some types of Kuwait fish were studied for radionuclide determination. These fish were taken from the Kuwaiti water territory during May. The study is to determine the radiation exposure for ²¹⁰Po in some fish species in Kuwait the ²¹⁰Po concentration was found to be between 0.089 and 2.544 Bq/kg the highs was in Zubaidy and the lowest was in Hamour.

Keywords: the radionuclide, radiation exposure, fish species, Zubaida, Hamour

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Authors: Miriam Sosa-Díaz, Faustino Sánchez-Garduño

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In population dynamics the study of both, the abundance and the spatial distribution of the populations in a given habitat, is a fundamental issue a From ecological point of view, the determination of the factors influencing such changes involves important problems. In this paper a mathematical model to describe the temporal dynamic and the spatiotemporal dynamic of the interaction of three populations (pollinators, plants and herbivores) is presented. The study we present is carried out by stages: 1. The temporal dynamics and 2. The spatio-temporal dynamics. In turn, each of these stages is developed by considering three cases which correspond to the dynamics of each type of interaction. For instance, for stage 1, we consider three ODE nonlinear systems describing the pollinator-plant, plant-herbivore and plant-pollinator-herbivore, interactions, respectively. In each of these systems different types of dynamical behaviors are reported. Namely, transcritical and pitchfork bifurcations, existence of a limit cycle, existence of a heteroclinic orbit, etc. For the spatiotemporal dynamics of the two mathematical models a novel factor are introduced. This consists in considering that both, the pollinators and the herbivores, move towards those places of the habitat where the plant population density is high. In mathematical terms, this means that the diffusive part of the pollinators and herbivores equations depend on the plant population density. The analysis of this part is presented by considering pairs of populations, i. e., the pollinator-plant and plant-herbivore interactions and at the end the two mathematical model is presented, these models consist of two coupled nonlinear partial differential equations of reaction-diffusion type. These are defined on a rectangular domain with the homogeneous Neumann boundary conditions. We focused in the role played by the density dependent diffusion term into the coexistence of the populations. For both, the temporal and spatio-temporal dynamics, a several of numerical simulations are included.

Keywords: bifurcation, heteroclinic orbits, steady state, traveling wave

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Authors: Rajasekar Elangopandian, Anand Shanmugam

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In order to reduce the cost of launching satellite and payloads to the orbit this project envisages some immense combined technology. This new technology in space odyssey contains literally four concepts. The first mode in this innovation is flight mission characteristics which, says how the mission will induct. The conventional technique of magnetic levitation will help us to produce the initial thrust. The name states reusable launch vehicle shows its viability of reuseness. The flight consists miniature rocket which produces the required thrust and the two JATO (jet assisted takeoff) boosters which gives the initial boost for the vehicle. The vehicle ostensibly looks like an airplane design and will be located on the super conducting rail track. When the high power electric current given to the rail track, the vehicle starts floating as per the principle of magnetic levitation. If the flight reaches the particular takeoff distance the two boosters gets starts and will give the 48KN thrust each. Obviously it`ll follow the vertical path up to the atmosphere end/start to space. As soon as it gets its speed the two boosters will cutoff. Once it reaches the space the inbuilt spacecraft keep the satellite in the desired orbit. When the work finishes, the apogee motors gives the initial kick to the vehicle to come in to the earth’s atmosphere with 22N thrust and automatically comes to the ground by following the free fall, the help of gravitational force. After the flying region it makes the spiral flight mode then gets landing where the super conducting levitated rail track located. It will catch up the vehicle and keep it by changing the poles of magnets and varying the current. Initial cost for making this vehicle might be high but for the frequent usage this will reduce the launch cost exactly half than the now-a-days technology. The incorporation of such a mechanism gives `hybrid` and the reusability gives `reusable launch vehicle` and ultimately Hybrid reusable launch vehicle.

Keywords: the two JATO (jet assisted takeoff) boosters, magnetic levitation, 48KN thrust each, 22N thrust and automatically comes to the ground

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Authors: Waqar Ahmad Butt, Gholamreza Vakili Nezhaad, Ali Soud Al Bemani, Yahya Al Wahaibi

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Minimum miscibility pressure (MMP) plays a great role in determining the displacement efficiency of different gas injection processes. Experimental techniques for MMP determination include industrially recommended slim tube, vanishing interfacial tension (VIT) and rising bubble apparatus (RBA). In this paper, MMP measurement study using slim tube and VIT experimental techniques for two different crude oil samples (M and N) both in live and stock tank oil forms is being presented. VIT measured MMP values for both 'M' and 'N' live crude oils were close to slim tube determined MMP values with 6.4 and 5 % deviation respectively. Whereas for both oil samples in stock tank oil form, VIT measured MMP showed a higher unacceptable deviation from slim tube determined MMP. This higher difference appears to be related to high stabilized crude oil heavier fraction and lack of multiple contacts miscibility. None of the different nine deployed crude oil and CO2 MMP computing correlations could result in reliable MMP, close to slim tube determined MMP. Since VIT determined MMP values for both considered live crude oils are in close match with slim tube determined MMP values, it confirms reliable, reproducible, rapid and cheap alternative for live crude oil MMP determination. Whereas VIT MMP determination for stock tank oil case needed further investigation about stabilization / destabilization mechanism of oil heavier ends and multiple contacts miscibility development issues.

Keywords: minimum miscibility pressure, interfacial tension, multiple contacts miscibility, heavier ends

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Authors: Shashikant R. Kuchekar, Shivaji D. Pulate, Vishwas B. Gaikwad

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A simple and selective method is developed for solvent extraction spectrophotometric determination of antimony(III) using O-Methylphenyl Thiourea (OMPT) as a sensitive chromogenic chelating agent. The basis of proposed method is formation of antimony(III)-OMPT complex was extracted with 0.0025 M OMPT in chloroform from aqueous solution of antimony(III) in 1.0 M perchloric acid. The absorbance of this complex was measured at 297 nm against reagent blank. Beer’s law was obeyed up to 15µg mL-1 of antimony(III). The Molar absorptivity and Sandell’s sensitivity of the antimony(III)-OMPT complex in chloroform are 16.6730 × 103 L mol-1 cm-1 and 0.00730282 µg cm-2 respectively. The stoichiometry of antimony(III)-OMPT complex was established from slope ratio method, mole ratio method and Job’s continuous variation method was 1:2. The complex was stable for more than 48 h. The interfering effect of various foreign ions was studied and suitable masking agents are used wherever necessary to enhance selectivity of the method. The proposed method is successfully applied for determination of antimony(III) from real samples alloy and synthetic mixtures. Repetition of the method was checked by finding relative standard deviation (RSD) for 10 determinations which was 0.42%.

Keywords: solvent extraction, antimony, spectrophotometry, real sample analysis

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Authors: Richard O’Riordan, Saritha Unnikrishnan

Abstract:

Autonomous Vehicles (AVs) are incorporating an increasing number of ADAS features, including automated lane-keeping systems. In recent years, many research papers into lane detection algorithms have been published, varying from computer vision techniques to deep learning methods. The transition from lower levels of autonomy defined in the SAE framework and the progression to higher autonomy levels requires increasingly complex models and algorithms that must be highly reliable in their operation and functionality capacities. Furthermore, these algorithms have no room for error when operating at high levels of autonomy. Although the current research details existing computer vision and deep learning algorithms and their methodologies and individual results, the research also details challenges faced by the algorithms and the resources needed to operate, along with shortcomings experienced during their detection of lanes in certain weather and lighting conditions. This paper will explore these shortcomings and attempt to implement a lane detection algorithm that could be used to achieve improvements in AV lane detection systems. This paper uses a pre-trained LaneNet model to detect lane or non-lane pixels using binary segmentation as the base detection method using an existing dataset BDD100k followed by a custom dataset generated locally. The selected roads will be modern well-laid roads with up-to-date infrastructure and lane markings, while the second road network will be an older road with infrastructure and lane markings reflecting the road network's age. The performance of the proposed method will be evaluated on the custom dataset to compare its performance to the BDD100k dataset. In summary, this paper will use Transfer Learning to provide a fast and robust lane detection algorithm that can handle various road conditions and provide accurate lane detection.

Keywords: ADAS, autonomous vehicles, deep learning, LaneNet, lane detection

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Authors: Jianyong Xue, Olivier L. Georgeon, Salima Hassas

Abstract:

During the initial phase of cognitive development, infants exhibit amazing abilities to generate novel behaviors in unfamiliar situations, and explore actively to learn the best while lacking extrinsic rewards from the environment. These abilities set them apart from even the most advanced autonomous robots. This work seeks to contribute to understand and replicate some of these abilities. We propose the Bottom-up hiErarchical sequential Learning algorithm with Constructivist pAradigm (BEL-CA) to design agents capable of learning autonomously and continuously through interactions. The algorithm implements no assumption about the semantics of input and output data. It does not rely upon a model of the world given a priori in the form of a set of states and transitions as well. Besides, we propose a toolkit to analyze the learning process at run time called GAIT (Generating and Analyzing Interaction Traces). We use GAIT to report and explain the detailed learning process and the structured behaviors that the agent has learned on each decision making. We report an experiment in which the agent learned to successfully interact with its environment and to avoid unfavorable interactions using regularities discovered through interaction.

Keywords: cognitive development, constructivist learning, hierarchical sequential learning, self-adaptation

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Authors: Chinnawat Satsananan

Abstract:

The amount of heavy metals in our environment has been of great concern because of their toxicity when their concentration is more than the permissible level. These metals enter the environment by different ways such as industrial activities, soil pollution. We have used flame atomic absorption spectrometry technique for determination of the concentration of Co, Cd and Pb in different tissues of five samples of seafoods (mackerel, squid, mussels, scallops and shrimp). The concentrations of Co, Cd and Pb in all examined seafoods were less than the reported literature values (WHO). The results mentioned that the seafoods obtained from Thewet Market were safety to consumption and make the quality of life of people in the community look better.

Keywords: heavy metals, seafood, atomic absorption spectrometry, Bangkok

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Authors: Sherif Keddis, Mohamed Azzam, Norbert Schwesinger

Abstract:

Harvesting mechanical energy from footsteps or other impacts is a possibility to enable wireless autonomous sensor nodes. These can be used for a highly efficient control of connected devices such as lights, security systems, air conditioning systems or other smart home applications. They can also be used for accurate location or occupancy monitoring. Converting the mechanical energy into useful electrical energy can be achieved using the piezoelectric effect offering simple harvesting setups and low deflections. The challenge facing piezoelectric transducers is the achievable amount of energy per impact in the lower mJ range and the management of such low energies. Simple setups for energy extraction such as a full wave bridge connected directly to a capacitor are problematic due to the mismatch between high impedance sources and low impedance storage elements. Efficient energy circuits for piezoelectric harvesters are commonly designed for vibration harvesters and require periodic input energies with predictable frequencies. Due to the sporadic nature of impact harvesters, such circuits are not well suited. This paper presents a self-powered circuit that avoids the impedance mismatch during energy extraction by disconnecting the load until the source reaches its charge peak. The switch is implemented with passive components and works independent from the input frequency. Therefore, this circuit is suited for impact harvesting and sporadic inputs. For the same input energy, this circuit stores 150% of the energy in comparison to a directly connected capacitor to a bridge rectifier. The total efficiency, defined as the ratio of stored energy on a capacitor to available energy measured across a matched resistive load, is 63%. Although the resulting energy is already sufficient to power certain autonomous applications, further optimization of the circuit are still under investigation in order to improve the overall efficiency.

Keywords: autonomous sensors, circuit design, energy harvesting, energy management, impact harvester, piezoelectricity

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Authors: Ebasa Girma, Nathnael Minyelshowa, Lebsework Negash

Abstract:

The use of unmanned aerial vehicles (UAVs) in precision agriculture has seen a huge increase recently. As such, systems that aim to apply various algorithms on the field need a structured framework of abstractions. This paper defines the various tasks of the UAVs in precision agriculture and models them into an architectural framework. The presented architecture is built on the context that there will be minimal physical intervention to do the tasks defined with multiple coordinated and cooperative UAVs. Various tasks such as image processing, path planning, communication, data acquisition, and field mapping are employed in the architecture to provide an efficient system. Besides, different limitation for applying Multi-UAVs in precision agriculture has been considered in designing the architecture. The architecture provides an autonomous end-to-end solution, starting from mission planning, data acquisition, and image processing framework that is highly efficient and can enable farmers to comprehensively deploy UAVs onto their lands. Simulation and field tests show that the architecture offers a number of advantages that include fault-tolerance, robustness, developer, and user-friendliness.

Keywords: deep learning, multi-UAVs, precision agriculture, UAVs architecture

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Authors: Ugur Cihat Sakarya

Abstract:

This research focuses on psychedelic trance music events in Turkey in the context of altered states of consciousness (ASC). The fieldwork that was conducted from 2018 to 2019 is the main source of the research. Participant observation method was followed in 15 selected events. To direct the musical experiences of participants, performances were also presented as a Dj. Ten of these events are open-air festivals. Five of them are indoor parties. The observations made during fieldwork and suitable answers for inference from the interviews with participants, artists, DJs, and volunteers were selected, compiled, and presented. In the result, findings showed that these activities are perceived as temporary autonomous areas by the participants both in time and space and that these activities are suitable areas for expressing themselves as a group (psyfamily) against mainstream culture. It has been observed that the elements that complement the altered states of consciousness in these events are music, visual arts, drug use, and desire to experience spiritual experiences. It is thought that this first academic study -about this topic in Turkey- will open a door for future researches.

Keywords: consciousness, psychedelic, psytrance, rave, Turkey

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Authors: Moohyun Lee, Soojung Hur, Yongwan Park

Abstract:

In this paper is proposed a method uses only LIDAR system to classification an obstacle and determine its type by establishing database for classifying obstacles based on LIDAR. The existing LIDAR system, in determining the recognition of obstruction in an autonomous vehicle, has an advantage in terms of accuracy and shorter recognition time. However, it was difficult to determine the type of obstacle and therefore accurate path planning based on the type of obstacle was not possible. In order to overcome this problem, a method of classifying obstacle type based on existing LIDAR and using the width of obstacle materials was proposed. However, width measurement was not sufficient to improve accuracy. In this research, the width data was used to do the first classification; database for LIDAR intensity data by four major obstacle materials on the road were created; comparison is made to the LIDAR intensity data of actual obstacle materials; and determine the obstacle type by finding the one with highest similarity values. An experiment using an actual autonomous vehicle under real environment shows that data declined in quality in comparison to 3D LIDAR and it was possible to classify obstacle materials using 2D LIDAR.

Keywords: obstacle, classification, database, LIDAR, segmentation, intensity

Procedia PDF Downloads 311