Search results for: autonomous basin climbing

Authors: Tomasz Wejrzanowski, Łukasz Kaczmarek, Michał Maksimczuk

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High-resolution X-ray computed microtomography (µCT) is a non-destructive technique commonly used to determine the internal structure of reservoir rock sample. This study concerns µCT analysis of Silurian and Ordovician shales and mudstones from a borehole in the Baltic Basin, north of Poland. The spatial resolution of the µCT images obtained was 27 µm, which enabled the authors to create accurate 3-D visualizations and to calculate the ratio of pores and fractures volume to the total sample volume. A total of 1024 µCT slices were used to create a 3-D volume of sample structure geometry. These µCT slices were processed to obtain a clearly visible image and the volume ratio. A copper X-ray source filter was used to reduce image artifacts. Due to accurate technical settings of µCT it was possible to obtain high-resolution 3-D µCT images of low X-ray transparency samples. The presented results confirm the utility of µCT implementations in geoscience and show that µCT has still promising applications for reservoir exploration and characterization.

Keywords: fractures, material density, pores, structure

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Authors: Jianning Tang, Trevor Hocksun Kwan, Xiaofeng Wu

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With the increasing demand for space use in multiple sectors (navigation, telecommunication, imagery, etc.), the deployment and maintenance demand of satellites are growing. Considering the high launching cost and the restrictions on weight and size of the payload when using launch vehicle, the technique of on-orbit manufacturing has obtained more attention because of its significant potential to support future space missions. 3D printing is the most promising manufacturing technology that could be applied in space. However, due to the lack of autonomous quality assessment, the operation of conventional 3D printers still relies on human presence to supervise the printing process. This paper is proposed to develop an automatic 3D reconstruction system aiming at detecting failures on the 3D printed objects through application of point cloud technology. Based on the data obtained from the point cloud, the 3D printer could locate the failure and repair the failure. The system will increase automation and provide 3D printing with more feasibilities for space use without human interference.

Keywords: 3D printing, quality assessment, point cloud, on-orbit manufacturing

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Authors: Hyeongbok Kim, Lingling Zhao, Xiaohong Su

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Deep reinforcement learning has been applied to address various problems in robotics, such as autonomous driving and unmanned aerial vehicle. However, because of the sparse reward penalty for a collision with obstacles during the navigation mission, the agent fails to learn the optimal policy or requires a long time for convergence. Therefore, using obstacles and enemy agents, in this paper, we present a curriculum-based boost learning method to effectively train compound skills during multi-agent reinforcement learning. First, to enable the agents to solve challenging tasks, we gradually increased learning difficulties by adjusting reward shaping instead of constructing different learning environments. Then, in a benchmark environment with static obstacles and moving enemy agents, the experimental results showed that the proposed curriculum learning strategy enhanced cooperative navigation and compound collision avoidance skills in uncertain environments while improving learning efficiency.

Keywords: curriculum learning, hard exploration, multi-agent reinforcement learning, robotic navigation, sparse reward

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Authors: Ovye Yohanna Musah

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Shale formations of the Middle Benue Trough in North Central Nigeria present a variety of opportunities for the exploration, development and exploitation of unconventional natural gas. Prospective formations range in age from Albian through Coniacian; they include the Asu River Group, Awe, Ezeaku and the Awgu formations, however, the Keana and Lafia formations are thought to be of lesser importance. The Awgu formation presents the best prospect when compared to the Barnett Shales of Fort Worth Basin in Texa, United States with regards to the organic matter maturition, TOC content of formation and shale thicknesses which are key attributes that aid in determining the economic viability of any shale gas play. The vitrinite reflectance value from Rock Eval pyrolysis for Awe and Awgu formations are 0.89—1.34(%) and 0.83—1.13(%) respectively and are good and sufficiently mature to generate gas from the Benue Trough. The TOC value are good for Awgu formation which is 0.83—6.54(%) and closest to that of the Barnett at 1—4.5(%). Asu River and Ezeaku are less viable. Furthermore, the High to Medium Volatile bituminous coals found in the Awgu formation are characterized by high TOC contents which may enhance gas generation and this is good for further examination and possible development.

Keywords: shale gas, resource, unconventional, benue, TOC

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Authors: V. Sobotková, B. Šarapatka, M. Dumbrovský, J. Uhrová, M. Bednář

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The paper deals with the influence of implemented conservation measures on the quality of surface water resources. Recently, a new process of complex land consolidation in the Czech Republic has provided a unique opportunity to improve the quality of the environment and sustainability of crop production by means of better soil and water conservation. The most important degradation factor in our study area in the Hubenov drinking water reservoir catchment basin was water erosion together with loss of organic matter. Hubenov Reservoir water resources were monitored for twenty years (1990–2010) to collect water quality data for nitrate nitrogen (N-NO3-), total P, and undissolved substances. Results obtained from measurements taken before and after land consolidation indicated a decrease in the linear trend of N-NO3- and total P concentrations, this was achieved through implementation of conservation measures limiting soil degradation in the Hubenov reservoir catchment area.

Keywords: complex land consolidation, degradation, land use, soil and water conservation, surface water resources

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Authors: Mohammad Reza Dahmardeh Ghaleno, Mohammad Nohtani, Saeedeh Khaledi

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Hydrological models are applied to simulation and prediction floods in watersheds. WetSpa is a distributed, continuous and physically model with daily or hourly time step that explains of precipitation, runoff and evapotranspiration processes for both simple and complex contexts. This model uses a modified rational method for runoff calculation. In this model, runoff is routed along the flow path using Diffusion-Wave Equation which depend on the slope, velocity and flow route characteristics. Garmabrood watershed located in Mazandaran province in Iran and passing over coordinates 53° 10´ 55" to 53° 38´ 20" E and 36° 06´ 45" to 36° 25´ 30"N. The area of the catchment is about 1133 km2 and elevations in the catchment range from 213 to 3136 m at the outlet, with average slope of 25.77 %. Results of the simulations show a good agreement between calculated and measured hydrographs at the outlet of the basin. Drawing upon Nash-Sutcliffe Model Efficiency Coefficient for calibration periodic model estimated daily hydrographs and maximum flow rate with an accuracy up to 61% and 83.17 % respectively.

Keywords: watershed simulation, WetSpa, runoff, flood prediction

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Authors: Caroline Atef Shoukry Tadros

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Massive Urbanization growth threatens the sustainability of cities and the quality of city life. This raised the need for an alternate model of sustainability, so we need to plan the future cities in a smarter way with smarter mobility. Smart Mobility planning applications are solutions that use digital technologies and infrastructure advances to improve the efficiency, sustainability, and inclusiveness of urban transportation systems. They can contribute to meeting the needs of Urbanization growth by addressing the challenges of traffic congestion, pollution, accessibility, and safety in cities. Some example of a Smart Mobility planning application are Mobility-as-a-service: This is a service that integrates different transport modes, such as public transport, shared mobility, and active mobility, into a single platform that allows users to plan, book, and pay for their trips. This can reduce the reliance on private cars, optimize the use of existing infrastructure, and provide more choices and convenience for travelers. MaaS Global is a company that offers mobility-as-a-service solutions in several cities around the world. Traffic flow optimization: This is a solution that uses data analytics, artificial intelligence, and sensors to monitor and manage traffic conditions in real-time. This can reduce congestion, emissions, and travel time, as well as improve road safety and user satisfaction. Waycare is a platform that leverages data from various sources, such as connected vehicles, mobile applications, and road cameras, to provide traffic management agencies with insights and recommendations to optimize traffic flow. Logistics optimization: This is a solution that uses smart algorithms, blockchain, and IoT to improve the efficiency and transparency of the delivery of goods and services in urban areas. This can reduce the costs, emissions, and delays associated with logistics, as well as enhance the customer experience and trust. ShipChain is a blockchain-based platform that connects shippers, carriers, and customers and provides end-to-end visibility and traceability of the shipments. Autonomous vehicles: This is a solution that uses advanced sensors, software, and communication systems to enable vehicles to operate without human intervention. This can improve the safety, accessibility, and productivity of transportation, as well as reduce the need for parking space and infrastructure maintenance. Waymo is a company that develops and operates autonomous vehicles for various purposes, such as ride-hailing, delivery, and trucking. These are some of the ways that Smart Mobility planning applications can contribute to meeting the needs of the Urbanization growth. However, there are also various opportunities and challenges related to the implementation and adoption of these solutions, such as the regulatory, ethical, social, and technical aspects. Therefore, it is important to consider the specific context and needs of each city and its stakeholders when designing and deploying Smart Mobility planning applications.

Keywords: smart mobility planning, smart mobility applications, smart mobility techniques, smart mobility tools, smart transportation, smart cities, urbanization growth, future smart cities, intelligent cities, ICT information and communications technologies, IoT internet of things, sensors, lidar, digital twin, ai artificial intelligence, AR augmented reality, VR virtual reality, robotics, cps cyber physical systems, citizens design science

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Authors: Benjamin Aina Peter, Amos Wale Ogunsola

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In this paper, a mathematical model of malaria transmission was presented with the effect of seasonal shift, due to global fluctuation in temperature, on the increase of conveyor of the infectious disease, which probably alters the region transmission potential of malaria. A deterministic compartmental model was proposed and analyzed qualitatively. Both qualitative and quantitative approaches of the model were considered. The next-generation matrix is employed to determine the basic reproduction number of the model. Equilibrium points of the model were determined and analyzed. The numerical simulation is carried out using Excel Micro Software to validate and support the qualitative results. From the analysis of the result, the optimal temperature for the transmission of malaria is between and . The result also shows that an increase in temperature due to seasonal shift gives rise to the development of parasites which consequently leads to an increase in the widespread of malaria transmission in Kampala. It is also seen from the results that an increase in temperature leads to an increase in the number of infectious human hosts and mosquitoes.

Keywords: seasonal variation, indoor residual spray, efficacy of spray, temperature-dependent model

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Authors: Mohamad Abdullah

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Recent Advancements in technology have stimulated deep change in the language learning classroom. Flipped classroom as a new pedagogical method is at the center of this change. It turns the classroom into a student-centered environment and promotes interactive and autonomous learning. The present study is an attempt to examine the effectiveness of the Flipped Classroom Model (FCM) on students’ motivation level in English speaking performance. This study was carried out with 27 undergraduate female English majors who enrolled in the course of Advanced Communication Skills (ENGL 154) at Buraimi University College (BUC). Data was collected through Motivation in English Speaking Performance Questionnaire (MESPQ) which has been distributed among the participants of this study pre and post the implementation of FCM. SPSS was used for analyzing data. The Paired T-Test which was carried out on the pre-post of (MESPQ) showed a significant difference between them (p < .009) that revealed participants’ tendency to increase their motivation level in English speaking performance after the application of FCM. In addition, respondents of the current study reported positive views about the implementation of FCM.

Keywords: english speaking performance, motivation, flipped classroom model, learner-contentedness

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Authors: Erika Tatiana Ruiz, Wilson Adarme Jaimes

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This abstract presents the methodology for improving the logistics processes of agricultural production units belonging to the coffee, cocoa, and fruit sectors, starting from the fundamental concepts and detailing each of the phases to carry out the diagnosis, which will be the basis for the formulation of its action plan and implementation of the maturity model. As a result of this work, the maturity model is formulated to improve logistics processes. This model seeks to: generate a progressive model that is useful for all productive units belonging to these sectors at the national level, regardless of their initial conditions, focus on the improvement of logistics processes as a strategy that contributes to improving the competitiveness of the agricultural sector in Colombia and spread the implementation of good logistics practices in postharvest in all departments of the country through autonomous tools. This model has been built through a series of steps that allow the evaluation and improvement of the logistics dimensions or indicators. The potential improvements for each dimension provide the foundation on which to advance to the next level. Within the maturity model, a methodology is indicated for the design and execution of strategies to improve its logistics processes, taking into account the current state of each production unit.

Keywords: agroindustrial, characterization, logistics, maturity model, processes

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Authors: Dimitar Karastoyanov, Todor Penchev

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The paper presents the research of a kind of autonomous mobile robots, intended for work and adaptive perception in unknown and unstructured environment. The objective are robots, dedicated for multi-sensory environment perception and exploration, like measurements and samples taking, discovering and putting a mark on the objects as well as environment interactions–transportation, carrying in and out of equipment and objects. At that ground classification of the different types mobile robots in accordance with the way of locomotion (wheel- or chain-driven, walking, etc.), used drive mechanisms, kind of sensors, end effectors, area of application, etc. is made. Modular system for the mechanical construction of the mobile robots is proposed. Special PLC on the base of AtMega128 processor for robot control is developed. Electronic modules for the wireless communication on the base of Jennic processor as well as the specific software are developed. The methods, means and algorithms for adaptive environment behaviour and tasks realization are examined. The methods of group control of mobile robots and for suspicious objects detecting and handling are discussed too.

Keywords: mobile robots, wireless communications, environment investigations, group control, suspicious objects

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Authors: Cristina Costa-Lobo, Ana Campina, José Menezes

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Creativity implies originality, but originality does not imply the existence of creativity. Today, one of the challenges of the educational context is the development of educated, autonomous, prudent and competent citizens with a critical attitude, a well-founded questioning and a creative search for innovative alternatives and solutions. These supposedly cognitive capacities impose emotional analysis and decision making, and emotion is also considered as a creative act. Authors emphasize the importance of family and school in the creative manifestation of children and young people, and these agents can stimulate or impede creative expression. Thus, children entering the school system are faced with a barrier that blocks the externalization of this competence. This work deals with the implementation of specific strategies and promoters of an educational environment suitable for the development of creativity. The construct of creativity is discussed in a transdisciplinary perspective, and the importance of the construct is enhanced in psychoeducational practices, in challenging and multifaceted environments. It is assumed that the stimulation and early experience of creative thinking in an educational context are conditions that promote the development of problem-solving skills and future challenges.

Keywords: creativity, education, psychology, pedagogy

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Authors: Stefano Zappacosta, Cristiano Bove, Maria Carmela Marinelli, Paola di Lauro, Katarina Spasenovic, Lorenzo Ostano, Giuseppe Aiello, Marco Pietrosanto

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This paper proposes a novel neural network approach for assessing flood hazard mapping. The core of the model is a machine learning component fed by frequency ratios, namely statistical correlations between flood event occurrences and a selected number of topographic properties. The proposed hybrid model can be used to classify four different increasing levels of hazard. The classification capability was compared with the flood hazard mapping River Basin Plans (PAI) designed by the Italian Institute for Environmental Research and Defence, ISPRA (Istituto Superiore per la Protezione e la Ricerca Ambientale). The study area of Piemonte, an Italian region, has been considered without loss of generality. The frequency ratios may be used as a standalone block to model the flood hazard mapping. Nevertheless, the mixture with a neural network improves the classification power of several percentage points, and may be proposed as a basic tool to model the flood hazard map in a wider scope.

Keywords: flood modeling, hazard map, neural networks, hydrogeological risk, flood risk assessment

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Authors: Lidija Jevrić, Denis Kučević, Sanja Podunavac-Kuzmanović, Strahinja Kovačević, Milica Karadžić

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In the present study, the Hierarchical Cluster Analysis (HCA) was applied in order to determine the differences between the milk samples originating from a conventional dairy farm (CF) and an organic dairy farm (OF) in AP Vojvodina, Republic of Serbia. The clustering was based on the basis of the average values of saturated fatty acids (SFA) content and unsaturated fatty acids (UFA) content obtained for every season. Therefore, the HCA included the annual SFA and UFA content values. The clustering procedure was carried out on the basis of Euclidean distances and Single linkage algorithm. The obtained dendrograms indicated that the clustering of UFA in OF was much more uniform compared to clustering of UFA in CF. In OF, spring stands out from the other months of the year. The same case can be noticed for CF, where winter is separated from the other months. The results could be expected because the composition of fatty acids content is greatly influenced by the season and nutrition of dairy cows during the year.

Keywords: chemometrics, clustering, food engineering, milk quality

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Authors: Mingxin Li, Liya Ni

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Autonomous parking is a valuable feature applicable to many robotics applications such as tour guide robots, UV sanitizing robots, food delivery robots, and warehouse robots. With auto-parking, the robot will be able to park at the charging zone and charge itself without human intervention. As compared to self-driving vehicles, auto-parking is more challenging for a small-scale mobile robot only equipped with a front camera due to the camera view limited by the robot’s height and the narrow Field of View (FOV) of the inexpensive camera. In this research, auto-parking of a small-scale mobile robot with a front camera only was achieved in a four-step process: Firstly, transfer learning was performed on the AlexNet, a popular pre-trained convolutional neural network (CNN). It was trained with 150 pictures of empty parking slots and 150 pictures of occupied parking slots from the view angle of a small-scale robot. The dataset of images was divided into a group of 70% images for training and the remaining 30% images for validation. An average success rate of 95% was achieved. Secondly, the image of detected empty parking space was processed with edge detection followed by the computation of parametric representations of the boundary lines using the Hough Transform algorithm. Thirdly, the positions of the entrance point and center of available parking space were predicted based on the robot kinematic model as the robot was driving closer to the parking space because the boundary lines disappeared partially or completely from its camera view due to the height and FOV limitations. The robot used its wheel speeds to compute the positions of the parking space with respect to its changing local frame as it moved along, based on its kinematic model. Lastly, the predicted entrance point of the parking space was used as the reference for the motion control of the robot until it was replaced by the actual center when it became visible again by the robot. The linear and angular velocities of the robot chassis center were computed based on the error between the current chassis center and the reference point. Then the left and right wheel speeds were obtained using inverse kinematics and sent to the motor driver. The above-mentioned four subtasks were all successfully accomplished, with the transformed learning, image processing, and target prediction performed in MATLAB, while the motion control and image capture conducted on a self-built small scale differential drive mobile robot. The small-scale robot employs a Raspberry Pi board, a Pi camera, an L298N dual H-bridge motor driver, a USB power module, a power bank, four wheels, and a chassis. Future research includes three areas: the integration of all four subsystems into one hardware/software platform with the upgrade to an Nvidia Jetson Nano board that provides superior performance for deep learning and image processing; more testing and validation on the identification of available parking space and its boundary lines; improvement of performance after the hardware/software integration is completed.

Keywords: autonomous parking, convolutional neural network, image processing, kinematics-based prediction, transfer learning

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Authors: Artur Krukowski, Emmanouela Vogiatzaki

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The article presents an ongoing work in research projects such as SCAN4RECO or ARCH, both funded by the European Commission under Horizon 2020 program. The former one concerns multimodal and multispectral scanning of Cultural Heritage assets for their digitization and conservation via spatiotemporal reconstruction and 3D printing, while the latter one aims to better preserve areas of cultural heritage from hazards and risks. It co-creates tools that would help pilot cities to save cultural heritage from the effects of climate change. It develops a disaster risk management framework for assessing and improving the resilience of historic areas to climate change and natural hazards. Tools and methodologies are designed for local authorities and practitioners, urban population, as well as national and international expert communities, aiding authorities in knowledge-aware decision making. In this article we focus on 3D modelling of object geometry using primarily photogrammetric methods to achieve very high model accuracy using consumer types of devices, attractive both to professions and hobbyists alike.

Keywords: 3D modelling, UAS, cultural heritage, preservation

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Authors: A. Bahar Ganiyeva, M. Sabuhi Tanriverdiyev

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The article analyzes state support and policy mechanisms aimed at driving tourism as one of the vibrant and rapidly developing economies. State programs and long-range strategic roadmaps and previous programs execution, results and their impact on the particular countries economy have been raised during the research. This theme provides a useful framework for discussions with a wider range of stakeholders as the implications arising are of importance both for academics and practitioners engaged in hospitality and tourism development and research. The impact that tourism has on sustainable regional development in emerging markets is highly substantial. For Azerbaijan, Turkey, Georgia, and Russia, with their rich natural resources and cultural heritage, tourism can be an important basis for economic expansion, and a way to form an acceptable image of the countries as safe, open, hospitable, and complex.

Keywords: Sustainable tourism, hospitality, destination, strategic roadmap, tourism, economy, growth, state support, mechanism, policy formation, state program

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Authors: Keshek M.H, Mohamed M.A, El-Shafey M.A

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The aim of this research was increasing the productivity of solar distillation. In order to reach this aim, a solar distiller was created with three glass sides sloping 30o at the horizontal level, and the experiments were carried out on the solar distillation unit during the period from 24th August, 2016 till 24th May, 2017 at the Agricultural Engineering and Bio Systems Department, Faculty of Agriculture, Menoufia University. Three gap lengths were used between the water level and the inner glass cover, those were 3, 6, and 9 cm. As the result of change the gap length between the water level and the inner glass cover the total volume of basins were changed from 15.5, 13, and 11 L, respectively. The total basin volume was divided to three sections, to investigate the effect of water volume. The three water volumes were 100%, 75%, and 50%. Every section was supplied with one, two, or three heaters. The one heater power was 15 W. The results showed that, by increasing the distance between the basins edge and the inner edge of the glass cover, an increase occurs in the percentage of temperature difference with maximum value was 52% at distance 9 cm from each edge, an increase occurs in the productivity with maximum productivity was 3.3 L/m2 at distance 9 cm from each edge and an increase occurs in the efficiency with maximum efficiency was 70% at distance 9 cm from each edge.

Keywords: distillation, solar energy, still productivity, efficiency

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Authors: M. V. Chidananda Murthy, M. Z. Kurian, H. S. Guruprasad

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Image restoration in the process of communication is one of the emerging fields in the image processing. The motion analysis processing is the simplest case to detect motion in an image. Applications of motion analysis widely spread in many areas such as surveillance, remote sensing, film industry, navigation of autonomous vehicles, etc. The scene may contain multiple moving objects, by using motion analysis techniques the blur caused by the movement of the objects can be enhanced by filling-in occluded regions and reconstruction of transparent objects, and it also removes the motion blurring. This paper presents the design and comparison of various motion detection and enhancement filters. Median filter, Linear image deconvolution, Inverse filter, Pseudoinverse filter, Wiener filter, Lucy Richardson filter and Blind deconvolution filters are used to remove the blur. In this work, we have considered different types and different amount of blur for the analysis. Mean Square Error (MSE) and Peak Signal to Noise Ration (PSNR) are used to evaluate the performance of the filters. The designed system has been implemented in Matlab software and tested for synthetic and real-time images.

Keywords: image enhancement, motion analysis, motion detection, motion estimation

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Authors: Ho Young Son, Bu Seog Ju, Woo Young Jung

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This study presents the seismic safety evaluation of weir structure subjected to strong earthquake ground motions, as a flood defense structure in civil engineering structures. The seismic safety analysis procedure was illustrated through development of Finite Element (FE) and InFinite Element (IFE) method in ABAQUS platform. The IFE model was generated by CINPS4, 4-node linear one-way infinite model as a sold continuum infinite element in foundation areas of the weir structure and then nonlinear FE model using friction model for soil-structure interactions was applied in this study. In order to understand the complex behavior of weir structures, nonlinear time history analysis was carried out. Consequently, it was interesting to note that the compressive stress gave more vulnerability to the weir structure, in comparison to the tensile stress, during an earthquake. The stress concentration of the weir structure was shown at the connection area between the weir body and stilling basin area. The stress both tension and compression was reduced in IFE model rather than FE model of weir structures.

Keywords: seismic, numerical analysis, FEM, weir, boundary condition

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Authors: Sibo Lu, Zhongkai Qian, Haotian Zhang

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This article examines the phenomenon of micro-sovereignty in the context of property management and its implications for biopolitics and urban governance in mainland China. It explores the transformation of urban spaces into privatized communities managed by property companies, leading to the reterritorialization of urban areas and the segmentation of urban populations. Drawing on legal frameworks, we analyze how commercial real estate development and property management have reshaped the urban landscape, placing nearly all urban residents within service areas of property management firms, thus establishing micro-sovereign entities that exercise control over residential spaces. Through a critique of property management's sovereign effects on social organization and the exploration of autonomous, democratic alternatives in community governance, this article contributes to the broader discourse on sovereignty, governance, and resistance within the urban milieu of contemporary China. It underscores the urgent need for more democratic forms of community management that can transcend the capitalist logic of property management companies and foster genuine participatory governance at the grassroots level.

Keywords: biopolitic, critical theory, political sociology, political philosophy

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Authors: A. Casale, J. Alessi, C. N. Bianchi, G. Bozzini, M. Brunoldi, V. Cappanera, P. Corvisiero, G. Fanciulli, D. Grosso, N. Magnoli, A. Mandich, C. Melchiorre, C. Morri, P. Povero, N. Stasi, M. Taiuti, G. Viano, M. Wurtz

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This work describes a real-time algorithm for detecting, tracking and classifying single motorboats, developed using the acoustic data recorded by a hydrophone array within the framework of EU LIFE + project ARION (LIFE09NAT/IT/000190). The project aims to improve the conservation status of bottlenose dolphins through a real-time simultaneous monitoring of their population and surface ship traffic. A Passive Acoustic Monitoring (PAM) system is installed on two autonomous permanent marine buoys, located close to the boundaries of the Marine Protected Area (MPA) of Portofino (Ligurian Sea- Italy). Detecting surface ships is also a necessity in many other sensible areas, such as wind farms, oil platforms, and harbours. A PAM system could be an effective alternative to the usual monitoring systems, as radar or active sonar, for localizing unauthorized ship presence or illegal activities, with the advantage of not revealing its presence. Each ARION buoy consists of a particular type of structure, named meda elastica (elastic beacon) composed of a main pole, about 30-meter length, emerging for 7 meters, anchored to a mooring of 30 tons at 90 m depth by an anti-twist steel wire. Each buoy is equipped with a floating element and a hydrophone tetrahedron array, whose raw data are send via a Wi-Fi bridge to a ground station where real-time analysis is performed. Bottlenose dolphin detection algorithm and ship monitoring algorithm are operating in parallel and in real time. Three modules were developed and commissioned for ship monitoring. The first is the detection algorithm, based on Time Difference Of Arrival (TDOA) measurements, i.e., the evaluation of angular direction of the target respect to each buoy and the triangulation for obtaining the target position. The second is the tracking algorithm, based on a Kalman filter, i.e., the estimate of the real course and speed of the target through a predictor filter. At last, the classification algorithm is based on the DEMON method, i.e., the extraction of the acoustic signature of single vessels. The following results were obtained; the detection algorithm succeeded in evaluating the bearing angle with respect to each buoy and the position of the target, with an uncertainty of 2 degrees and a maximum range of 2.5 km. The tracking algorithm succeeded in reconstructing the real vessel courses and estimating the speed with an accuracy of 20% respect to the Automatic Identification System (AIS) signals. The classification algorithm succeeded in isolating the acoustic signature of single vessels, demonstrating its temporal stability and the consistency of both buoys results. As reference, the results were compared with the Hilbert transform of single channel signals. The algorithm for tracking multiple targets is ready to be developed, thanks to the modularity of the single ship algorithm: the classification module will enumerate and identify all targets present in the study area; for each of them, the detection module and the tracking module will be applied to monitor their course.

Keywords: acoustic-noise, bottlenose-dolphin, hydrophone, motorboat

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Authors: Abdulah Fajar

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Electronic Procurement System has been implemented at government institution in Indonesia. This system has been developed centrally at Institution of National Procurement Policy (LKPP) and implemented autonomously at either local or national government institution. The lack of competency at many institution on Information Technology Management arise several major problems. The main concern of LKPP to local administrator is assured that the system is running normally and always be able to serve the needs of its users. Monitoring system has been identified as the one of solution to prevent the problems appeared. Monitoring system is developed using Simple Network Management Protocol (SNMP) and implemented at LKPP. There are two modules; Main Dashboard and Local Agent. Main Dashboard is intended for LKPP and Local Agent is intended to implement at local autonomous e-procurement system (LPSE). There are several resources that must be monitored such as computation, memory and network traffic. Agile paradigm is applied to this project to assure user and system requirement is met. The length of project is the one of reason why agile paradigm has been chosen. The system has been successfully delivered to LKPP.

Keywords: procurement system, SNMP, LKPP, LPSE

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Authors: Eleni Tsangouri, Xander Hillewaere, David Garoz Gómez, Dimitrios Aggelis, Filip Du Prez, Danny Van Hemelrijck

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Tapered Double Cantilever Beam (TDCB) is the most commonly used test set-up to evaluate the self-healing feature of thermoset polymers autonomously activated in the presence of crack. TDCB is a modification of the established fracture mechanics set-up of Double Cantilever Beam and is designed to provide constant strain energy release rate with crack length under stable load evolution (mode-I). In this study, the damage of virgin and autonomously healed TDCB polymer samples is evaluated considering the load-crack opening diagram, the strain maps provided by Digital Image Correlation technique and the fractography maps given by optical microscopy. It is shown that the pre-crack introduced prior to testing (razor blade tapping), the loading rate and the length of the side groove are the features that dominate the crack propagation and lead to inconstant fracture energy release rate.

Keywords: polymers, autonomous healing, fracture, tapered double cantilever beam

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Authors: Diksha Kadam

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The study of images of women in literature and women writers has been a significant area of concern for the last four decades because it is as ‘the study of signification and meaning production’ play a vital role in shaping the perceptions and consciousness of various segment of society in relation to the lives, roles, problems and experiences of different categories of women as women and as autonomous citizen of society. In the history of worlds English literature the status of women and representation of her in the writings is an issue of discussion always. The essence of her existence in the literature is felt; the ecstasy of her feelings is always seen. The literature is full of facts and figures. She is one of them. Her contribution to the literature is undoubtedly a beginning of a new era. Multiple challenges and multiple identities as represented in majority of the literary texts and in real provide much hope and assurance to the new generation of mothers and daughters in the direction of transformation of the individual and collective consciousness of society paving way for the emergence of an actually empowered new woman. This paper will focus on some of the prominent Indian and American women writers in English literature and the various dimensions of her image through some of the prominent works. This attempt of mine will be merely a salute to those women who have struggled to prove their identity as one of the members of society.

Keywords: role of women’s writing, new era, contribution to the literature, consciousness, existence

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Authors: Miguel Cañon, Darwin Mena, Ivan Cabeza

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In this work was compared and evaluated the applicability of statistical methods for the estimation of missing precipitations data in the basin of the river Lenguazaque located in the departments of Cundinamarca and Boyacá, Colombia. The methods used were the method of simple linear regression, distance rate, local averages, mean rates, correlation with nearly stations and multiple regression method. The analysis used to determine the effectiveness of the methods is performed by using three statistical tools, the correlation coefficient (r2), standard error of estimation and the test of agreement of Bland and Altmant. The analysis was performed using real rainfall values removed randomly in each of the seasons and then estimated using the methodologies mentioned to complete the missing data values. So it was determined that the methods with the highest performance and accuracy in the estimation of data according to conditions that were counted are the method of multiple regressions with three nearby stations and a random application scheme supported in the precipitation behavior of related data sets.

Keywords: statistical comparison, precipitation data, river subbasin, Bland and Altmant

Procedia PDF Downloads 462

Authors: Christopher Viens, Bosko Gajic, Steve Krase

Abstract:

Stick-Slip is a term that is often overused and commonly diagnosed from surface drilling parameters of torque and differential pressure, but the actual magnitude of the condition is rarely captured at the BHA level as the necessary measurements are seldom deployed. Deployment of an accurate stick-slip measurement downhole has led to an interesting discovery that goes against long held traditional drilling lore. A divide has been identified between stick-slip as independent bit and BHA conditions. This phenomenon in horizontal laterals is common, but few M/LWD systems have been able to capture it. Utilizing measurements of downhole RPM bore pressure, high-speed magnetometer data, bending moment, and continuous inclination, the wellbore spiraling phenomenon is able to be captured, quantified, and intimately tied back to systematic effects of BHA stalling and micro-sliding. An operator in the Permian Basin has identified that this phenomenon is contributing to increased tortuosity and drag. Utilizing downhole torque measurements the root causes of the stick-slip and spiraling phenomenon were identified and able to engineered out of the system.

Keywords: bending moment, downhole dynamics measurements, micro sliding, wellbore spiraling

Procedia PDF Downloads 238

Authors: Haozhe Xiang

Abstract:

With the rise of the Internet of Things era, intelligent products are gradually integrating into people's lives. Pedestrian trajectory prediction has become a key issue, which is crucial for the motion path planning of intelligent agents such as autonomous vehicles, robots, and drones. In the current technological context, deep learning technology is becoming increasingly sophisticated and gradually replacing traditional models. The pedestrian trajectory prediction algorithm combining neural networks and attention mechanisms has significantly improved prediction accuracy. Based on in-depth research on deep learning and pedestrian trajectory prediction algorithms, this article focuses on physical environment modeling and learning of historical trajectory time dependence. At the same time, social interaction between pedestrians and scene interaction between pedestrians and the environment were handled. An improved pedestrian trajectory prediction algorithm is proposed by analyzing the existing model architecture. With the help of these improvements, acceptable predicted trajectories were successfully obtained. Experiments on public datasets have demonstrated the algorithm's effectiveness and achieved acceptable results.

Keywords: deep learning, graph convolutional network, attention mechanism, LSTM

Procedia PDF Downloads 56

Authors: Dongkwon Han, Sangho Kim, Sunil Kwon

Abstract:

Unconventional gas resources have dramatically changed the future energy landscape. Unlike conventional gas resources, the key challenges in unconventional gas have been the requirement that applies to advanced approaches for production forecasting due to uncertainty and complexity of fluid flow. In this study, artificial neural network (ANN) model which integrates machine learning and data-driven approach was developed to predict productivity in shale gas. The database of 129 wells of Eagle Ford shale basin used for testing and training of the ANN model. The Input data related to hydraulic fracturing, well completion and productivity of shale gas were selected and the output data is a cumulative production. The performance of the ANN using all data sets, clustering and variables importance (VI) models were compared in the mean absolute percentage error (MAPE). ANN model using all data sets, clustering, and VI were obtained as 44.22%, 10.08% (cluster 1), 5.26% (cluster 2), 6.35%(cluster 3), and 32.23% (ANN VI), 23.19% (SVM VI), respectively. The results showed that the pre-trained ANN model provides more accurate results than the ANN model using all data sets.

Keywords: unconventional gas, artificial neural network, machine learning, clustering, variables importance

Procedia PDF Downloads 187

Authors: R. M. López-Gutiérrez, J. A. Michel-Macarty, H. Cervantes-De Avila, J. I. Nieto-Hipólito, C. Cruz-Hernández, L. Cardoza-Avendaño, S. Cortiant-Velez

Abstract:

It is well know that mankind benefits from the application of robot control by virtual handlers in industrial environments. In recent years, great interest has emerged in the control of multiple robots in order to carry out collective tasks. One main trend is to copy the natural organization that some organisms have, such as, ants, bees, school of fish, birds’ migration, etc. Surely, this collaborative work, results in better outcomes than those obtain in an isolated or individual effort. This topic has a great drive because collaboration between several robots has the potential capability of carrying out more complicated tasks, doing so, with better efficiency, resiliency and fault tolerance, in cases such as: coordinate navigation towards a target, terrain exploration, and search-rescue operations. In this work, synchronization of multiple autonomous robots is shown over a variety of coupling topologies: star, ring, chain, and global. In all cases, collective synchronous behavior is achieved, in the complex networks formed with mobile robots. Nodes of these networks are modeled by a mass using Matlab to simulate them.

Keywords: robots, synchronization, bidirectional, coordinate navigation

Procedia PDF Downloads 346