Search results for: deep space navigation

Authors: Valentina Zhang

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While facial expression is a complex and individualized behavior, all facial emotion recognition (FER) systems known to us rely on a single facial representation and are trained on universal data. We conjecture that: (i) different facial representations can provide different, sometimes complementing views of emotions; (ii) when employed collectively in a discussion group setting, they enable more accurate emotion reading which is highly desirable in autism care and other applications context sensitive to errors. In this paper, we first study FER using pixel-based DL vs semantics-based DL in the context of deepfake videos. Our experiment indicates that while the semantics-trained model performs better with articulated facial feature changes, the pixel-trained model outperforms on subtle or rare facial expressions. Armed with these findings, we have constructed an adaptive FER system learning from both types of models for dyadic or small interacting groups and further leveraging the synthesized group emotions as the ground truth for individualized FER training. Using a collection of group conversation videos, we demonstrate that FER accuracy and personalization can benefit from such an approach.

Keywords: neurodivergence care, facial emotion recognition, deep learning, ground truth for supervised learning

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Authors: Agastya Pratap Singh

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This review paper examines the emerging applications of generative adversarial networks (GANs) in the fields of image recognition and anomaly detection. With the rapid growth of digital image data, the need for efficient and accurate methodologies to identify and classify images has become increasingly critical. GANs, known for their ability to generate realistic data, have gained significant attention for their potential to enhance traditional image recognition systems and improve anomaly detection performance. The paper systematically analyzes various GAN architectures and their modifications tailored for image recognition tasks, highlighting their strengths and limitations. Additionally, it delves into the effectiveness of GANs in detecting anomalies in diverse datasets, including medical imaging, industrial inspection, and surveillance. The review also discusses the challenges faced in training GANs, such as mode collapse and stability issues, and presents recent advancements aimed at overcoming these obstacles.

Keywords: generative adversarial networks, image recognition, anomaly detection, synthetic data generation, deep learning, computer vision, unsupervised learning, pattern recognition, model evaluation, machine learning applications

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Authors: Albert Bou, Sebastian Dittert, Gianni de Fabritiis

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Advancing reinforcement learning (RL) requires tools that are flexible enough to easily prototype new methods while avoiding impractically slow experimental turnaround times. To match the first requirement, the most popular RL libraries advocate for highly modular agent composability, which facilitates experimentation and development. To solve challenging environments within reasonable time frames, scaling RL to large sampling and computing resources has proved a successful strategy. However, this capability has been so far difficult to combine with modularity. In this work, we explore design choices to allow agent composability both at a local and distributed level of execution. We propose a versatile approach that allows the definition of RL agents at different scales through independent, reusable components. We demonstrate experimentally that our design choices allow us to reproduce classical benchmarks, explore multiple distributed architectures, and solve novel and complex environments while giving full control to the user in the agent definition and training scheme definition. We believe this work can provide useful insights to the next generation of RL libraries.

Keywords: deep reinforcement learning, Python, PyTorch, distributed training, modularity, library

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Authors: Chatarina Muryani, Sarwono, Sugiyanto Heribentus

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Major part of Grobogan District, Central Java Province, Indonesia, always suffers from drought every year. The drought has implications toward almost all of the community activities, both domestic, agriculture, livestock, and industrial. The aim of this study was to determine (1) the drought distribution area in Grobogan District in 2015; (2) the impact of drought; and (3) the community adaptation toward the drought. The subject of the research was people who were impacted by the drought, purposive sampling technique was used to draw the sample. The data collection method was using field observation and in-depth interview while the data analysis was using descriptive analysis. The results showed that (1) in 2015, there were 14 districts which were affected by the drought and only 5 districts which do not suffer from drought, (2) the drought impacted to the reduction of water for domestic compliance, reduction of agricultural production, reduction of public revenue, (3) community adaptation to meet domestic water need was by making collective deep-wells and building water storages, adaptation in agriculture was done by setting the cropping pattern, while adaptation on economics was by allocating certain amount of funds for the family in anticipation of drought, which was mostly to purchase water.

Keywords: adaptation, distribution, drought, impacts

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Authors: M. Akhlaque Ahmed, Maliha Afshan Siddiqui

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A study has been carried out to see the prospect of wind power potential of southern Sindh namely Karachi, Hawksbay, Norriabad, Hyderabad, Ketibander and Shahbander using local wind speed data. The monthly average wind speed for these area ranges from 4.5m/sec to 8.5m/sec at 30m height from ground. Extractable wind power, wind energy and Weibul parameter for above mentioned areas have been examined. Furthermore, the power output using fast and slow wind machine using different blade diameter along with the 4Kw and 20 Kw aero-generator were examined to see the possible use for deep well pumping and electricity supply to remote villages. The analysis reveals that in this wind corridor of southern Sindh Hawksbay, Ketibander and Shahbander belongs to wind power class-3 Hyderabad and Nooriabad belongs to wind power class-5 and Karachi belongs to wind power class-2. The result shows that the that higher wind speed values occur between June till August. It was found that considering maximum wind speed location, Hawksbay,Noriabad are the best location for setting up wind machines for power generation.

Keywords: wind energy generation, Southern Sindh, seasonal change, Weibull parameter, wind machines

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Authors: Edgard Barki, Tânia Modesto Veludo-de-Oliveira, Felipe Zambaldi

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The social enterprise sector can be characterized as organizations that aim to solve social problems with financial sustainability and using market mechanisms. This sector has shown an increasing interest worldwide. Despite the growth and relevance of the sector, there is still a gap regarding the assessment of the social impact resulting from the initiatives of the organizations in this field. A number of metrics have been designed worldwide to evaluate the impact of social enterprises (e.g., IRIS, GIIRS, BACO), as well as some ad hoc studies that have been carried out, mainly in the microcredit sector, but there is still a gap to be filled in the development of research in social impact evaluation. Therefore, this research seeks to evaluate the social impact of two social enterprises (Terra Nova and Vivenda) in the area of housing in Brazil. To evaluate these impacts and their dimensions, we conducted an exploratory research, through three focus groups, thirty in-depth interviews and a survey with beneficiaries of both organizations. The results allowed us to evaluate how the two organizations were able to create a deep social impact in the populations served. Terra Nova has a more collective perspective, with a clear benefit of social inclusion and improvement of the community’s infrastructure, while Vivenda has a more individualized perspective, improving self-esteem, sociability and family coexistence.

Keywords: Brazil, housing, social enterprise, social impact evaluation

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Authors: Jaime E. Salazar Lagos

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Chongqing is located in southwest China and is becoming one of the most significant cities in the world. Its urban territories and metropolitan-related areas have one of the largest urban populations in China and are partitioned and shaped by two of the biggest and longest rivers on Earth, the Yangtze and Jialing Rivers, making Chongqing a megalopolis intersected by rivers. Historically, Chongqing City enjoyed fundamental connections with its rivers; however, current urban development of Chongqing City has lost effective integration of the riverbanks within the urban space and structural dynamics of the city. Therefore, there exists a critical lack of physical and urban space conjoined with the rivers, which diminishes the economic, tourist, and environmental development of Chongqing. Using multi-scale satellite-map site verification the study confirmed the hypothesis and urban-waterside disconnect. Collected data demonstrated that the Chongqing urban zone, an area of 5292 square-kilometers and a water front of 203.4 kilometers, has only 23.49 kilometers of extension (just 11.5%) with high-quality physical and spatial urban-waterside connection. Compared with other metropolises around the world, this figure represents a significant lack of spatial development along the rivers, an issue that has not been successfully addressed in the last 10 years of urban development. On a macro scale, the study categorized the different kinds of relationships between the city and its riverbanks. This data was then utilized in the creation of an urban-waterfront relationship map that can be a tool for future city planning decisions and real estate development. On a micro scale, we discovered there are three primary elements that are causing the urban-waterside disconnect: extensive highways along the most dense areas and city center, large private real estate developments that do not provide adequate riverside access, and large industrial complexes that almost completely lack riverside utilization. Finally, as part of the suggested strategies, the study concludes that the most efficient and practical way to improve this situation is to follow the historic master-planning of Chongqing and create connective nodes in critical urban locations along the river, a strategy that has been used for centuries to handle the same urban-waterside relationship. Reviewing and implementing this strategy will allow the city to better connect with the rivers, reducing the various impacts of disconnect and urban transformation.

Keywords: Chongqing City, megalopolis, nodes, riverbanks disconnection, urban

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Authors: Wilson P. R. Malebye, Solly M. Seeletse

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Applicants for space in selection problems are usually compared subjectively, and the selection made are not reliable and often cannot be verified scientifically. The paper illustrates objective selection by involving a mathematical measure in selecting a candidate applying for a job, and then using other two independent measures, validates the choice made. The scientific process followed is SToR (SAW, TOPSIS, WP) in which Simple Additive Weighting (SAW) is used to select, and the TOPSIS (technique for order preference by similarity to ideal solution) and weighted product (WP) are used to validate. A practical exercise was obtained from a factual selection problem in a recruitment task undertaken in an organization in which the authors consulted, and their Human Resources (HR) department wanted to check if their selection was justifiable. The result was that our approach was consistent and convincing to that HR, and theirs was not because our selection was satisfactory while theirs could not be corroborated using any method.

Keywords: candidate selection, SToR, SW, TOPSIS, WP

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Authors: Zixuan Yang

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This paper presents an analysis of the necessary consideration culture in distributed design through a thorough literature review and case study. The literature review has identified that the need for understanding cultural differences in product design and user evaluations is highlighted by analyzing cross-cultural influences; culture plays a significant role in distributed work, particularly in establishing team cohesion, trust, and credibility early in the project. By applying approaches of Geert Hofstede's dimensions and Fukuyama's trust analysis, a case study of a global design project, i.e., multicultural distributed teamwork solving the problem in terms of reducing the risk of deep vein thrombosis, showcases cultural dynamics, emphasizing trust-building and decision-making. The lessons learned emphasized the importance of cultural awareness, adaptability, and the utilization of scientific theories to enable effective cross-cultural collaborations in global design, providing valuable insights into navigating cultural diversity within design practices.

Keywords: culture, distributed design, global design, Geert Hofstede's dimensions, Fukuyama's trust analysis

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Authors: Chieh-Fu Chang, Wan-Hsin Hsieh

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We have proposed a novel scheme— iterative word-extension (IWE) to enhance the cliff effect of Reed-Solomon codes regarding the error performance at a specific Eb/N0. The scheme can be readily extended to block codes and the important properties of IWE are further investigated here. In order to select proper block codes specifying the desired cliff Eb/N0, the associated features of IWE are explored. These properties and features grant IWE ability to enhance security regarding the received Eb/N0 in physical layer so that IWE scheme can cooperate with the traditional presentation layer approach — cryptography, to meet the secure requirements in diverse applications. The features and feasibility of IWE scheme in satellite communication are finally discussed.

Keywords: security, IWE, cliff effect, space communications

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Authors: Leila Maleki, Ahmad Esmali Kooraneh, Hossein Taghi Derakhshi

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Neural activity in the human brain starts from the early stages of prenatal development. This activity or signals generated by the brain are electrical in nature and represent not only the brain function but also the status of the whole body. At the present moment, three methods can record functional and physiological changes within the brain with high temporal resolution of neuronal interactions at the network level: the electroencephalogram (EEG), the magnet oencephalogram (MEG), and functional magnetic resonance imaging (fMRI); each of these has advantages and shortcomings. EEG recording with a large number of electrodes is now feasible in clinical practice. Multichannel EEG recorded from the scalp surface provides a very valuable but indirect information about the source distribution. However, deep electrode measurements yield more reliable information about the source locations، Intracranial recordings and scalp EEG are used with the source imaging techniques to determine the locations and strengths of the epileptic activity. As a source localization method, Low Resolution Electro-Magnetic Tomography (LORETA) is solved for the realistic geometry based on both forward methods, the Boundary Element Method (BEM) and the Finite Difference Method (FDM). In this paper, we review The findings EEG- LORETA about epilepsy.

Keywords: epilepsy, EEG, EEG-LORETA

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Authors: Sijo Varghese

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A space craft (E. M. Tractor) which is intended to deflect or tug the asteroids which possesses threat towards the planets is the whole idea behind this paper. In this case "Electro Magnetic Induction" is used where it is known that when two separate circuits are connected to the electro magnet and on application of electric current through the one circuit in to the coil induces magnetic fields which repels the other circuit.( Faraday's law of Electromagnetic Induction). Basically a Spacecraft is used to attach a large sheet of aluminum on to the surface of the asteroid, the Spacecraft acts as an electro magnet and the induced magnetic field would eventually repel the aluminum intern repelling the asteroid. This method would take less time as compared to use of gravity( which requires a larger spacecraft and process will take a long time).

Keywords: asteroids, electro magnetic induction, gravity, electro magnetic tractor

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Authors: Seyed Abolhassan Naeini, Hamed Yekehdehghan

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One of the factors that affect the constructions adjacent to a slope is stability. There are various methods for the stability of the slopes, one of which is the use of concrete group piles. This study, using FLAC3D software, has tried to investigate the changes in safety coefficient because of the use of concrete group piles. In this research, furthermore, the optimal position of the piles has been investigated and the results show that the group pile does not affect the toe of the slope. In addition, the effect of the piles' burial depth on the slope has been studied. Results show that by increasing the piles burial depth on a slope, the level of stability and as a result the safety coefficient increases. In the investigation of reducing the distance between the piles and increasing the depth of underground water, it was observed that the obtained safety coefficient increased. Finally, the effect of the resistance of the lower stabilizing layer of the slope on stabilization was investigated by the pile group. The results showed that due to the behavior of the pile as a deep foundation, the stronger the soil layers are in the stable part of a stronger slope (in terms of resistance parameters), the more influential the piles are in enhancing the coefficient of safety.

Keywords: safety coefficient, group pile, slope, stability, FLAC3D software

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Authors: S. Bouchami, M.N. Lakhoua

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The automotive market is a dynamic market that continues to grow. That’s why several companies belonging to this sector adopt a quality improvement approach. Wanting to be competitive and successful in the environment in which they operate, these companies are dedicated to establishing a system of quality management to ensure the achievement of the objective quality, improving the products and process as well as the satisfaction of the customers. In this paper, the management of the quality and the improvement of a production line in an industrial company is presented. In fact, the project is divided into two essential parts: the creation of the technical line documentation and the quality assurance documentation and the resolution of defects at the line, as well as those claimed by the customer. The creation of the documents has required a deep understanding of the manufacturing process. The analysis and problem solving were done through the implementation of PDCA (Plan Do Check Act) and FTA (Fault Tree Analysis). As perspective, in order to better optimize production and improve the efficiency of the production line, a study on the problems associated with the supply of raw materials should be made to solve the problems of stock-outs which cause delays penalizing for the industrial company.

Keywords: quality management, documentary system, Plan Do Check Act (PDCA), fault tree analysis (FTA) method

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Authors: Elham Shirvani–Ghadikolaei, Seyed Mahdi Sajjadi

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State of the art technology has the tremendous impact on our life, in this situation education system have been influenced as well as. In this paper, tried to compare two space of learning text and hypertext with each other, and some challenges of using hypertext in religious education. Regarding the fact that, hypertext is an undeniable part of learning in this world and it has highly beneficial for the education process from class to office and home. In this paper tried to solve this question: the consequences and challenges of applying hypertext in religious education. Also, the consequences of this survey demonstrate the role of curriculum designer and planner of education to solve this problem.

Keywords: Hyper-textual, learning, religious education, learning text

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Authors: R. Mellah, R. Toumi

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This paper presents a new adaptive neuro-fuzzy controller equipped with compensatory fuzzy control (CNFI) in order to not only adjusts membership functions but also to optimize the adaptive reasoning by using a compensatory learning algorithm. The proposed control structure includes both CNFI controllers for which one is used to control in force the master robot and the second one for controlling in position the slave robot. The experimental results obtained, show a fairly high accuracy in terms of position and force tracking under free space motion and hard contact motion, what highlights the effectiveness of the proposed controllers.

Keywords: compensatory fuzzy, neuro-fuzzy, control adaptive, teleoperation

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Authors: Hassan J. Al Salman, Ahmed A. Al Ghafli

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In this study, we consider a nonlinear in time finite element approximation of a reaction diffusion system of lambda-omega type. We use a fixed-point theorem to prove existence of the approximations at each time level. Then, we derive some essential stability estimates and discuss the uniqueness of the approximations. In addition, we employ Nochetto mathematical framework to prove an optimal error bound in time for d= 1, 2 and 3 space dimensions. Finally, we present some numerical experiments to verify the obtained theoretical results.

Keywords: reaction diffusion system, finite element approximation, stability estimates, error bound

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Authors: Xu Rumin, Chen Jianyi, Yue Ti, Wang Yaan

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With the rapid development of subsea oil and gas exploitation, the demand for the related underwater process equipment is increasing fast. In order to reduce the energy consuming, people tend to separate the gas and oil phase directly on the seabed. Accordingly, an advanced separator is needed. In this paper, the pressure drop of a new type of separator named Gas Liquid Cylindrical Cyclone (GLCC) which is used in the subsea system is investigated by both experiments and numerical simulation. In the experiments, the single phase flow and gas-liquid two phase flow in GLCC were tested. For the simulation, the performance of GLCC under both laboratory and industrial conditions was calculated. The Eulerian model was implemented to describe the mixture flow field in the GLCC under experimental conditions and industrial oil-natural gas conditions. Furthermore, a relationship among Euler number (Eu), Reynolds number (Re), and Froude number (Fr) is generated according to similarity analysis and simulation data, which can present the GLCC separation performance of pressure drop. These results can give reference to the design and application of GLCC in deep sea.

Keywords: dimensionless analysis, gas-liquid cylindrical cyclone, numerical simulation, pressure drop

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Authors: Wajeeh Daher, Nimer Baya'a

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High Order Thinking Skills (HOTS) are suggested today as essential for the cognitive development of students and as preparing them for real life skills. Teachers are encouraged to use HOTS activities in the classroom to help their students develop higher order skills and deep thinking. So it is essential to prepare pre-service teachers to write and use HOTS activities for their students. This paper describes a model for integrating HOTS activities with GeoGebra in pre-service teachers’ preparation. This model describes four aspects of HOTS activities and working with them: Activity components, preparation procedure, strategies and processes used in writing a HOTS activity and types of the HOTS activities. In addition, the paper describes the pre-service teachers' difficulties in preparing and working with HOTS activities, as well as their perceptions regarding the use of these activities and GeoGebra in the mathematics classroom. The paper also describes the contribution of a HOTS activity to pupils' learning of mathematics, where this HOTS activity was prepared and taught by one pre-service teacher.

Keywords: high order thinking skills, HOTS activities, pre-service teachers, professional development

Procedia PDF Downloads 347

Authors: Payel Datta, Abhishek Das, Abhishek Roychoudhury, Dhiman Chattopadhyay, Tanushyam Chattopadhyay

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Machine learning (ML) and deep learning (DL) is most predominantly used in image/video processing, natural language processing (NLP), audio and speech recognition but not that much used in system performance evaluation. In this paper, authors are going to describe the architecture of an abstraction layer constructed using ML/DL to detect the system failure. This proposed system is used to detect the system failure by evaluating the performance metrics of an IoT service deployment under constrained infrastructure environment. This system has been tested on the manually annotated data set containing different metrics of the system, like number of threads, throughput, average response time, CPU usage, memory usage, network input/output captured in different hardware environments like edge (atom based gateway) and cloud (AWS EC2). The main challenge of developing such system is that the accuracy of classification should be 100% as the error in the system has an impact on the degradation of the service performance and thus consequently affect the reliability and high availability which is mandatory for an IoT system. Proposed ML/DL classifiers work with 100% accuracy for the data set of nearly 4,000 samples captured within the organization.

Keywords: machine learning, system performance, performance metrics, IoT, edge

Procedia PDF Downloads 195

Authors: Titilope F. Onaolapo, Christiana A. Breed, Maya Pasgaard, Kristine E. Jensen, Peta Brom

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In the face of fast-growing urbanization in most of the world's developing countries, there is a need to understand and address the risk and consequences involved in the indiscriminate use of urban green space. Tshwane city in South Africa has the potential to become one of the world's top biodiversity cities as South Africa is ranked one of the mega countries in biodiversity conservation, and Tshwane metropolitan municipality is the city with the wealthiest biodiversity with grassland biomes. In this study, we focus on the potentials and challenges of urban green transitioning from the Global South perspective with Tshwane city as the case study. We also address the issue of management conflicts that have resulted in informal and illegal activities in and around green spaces, with consequences such as land degradation, loss of livelihoods and biodiversity, and socio-ecological imbalances. A desk study review of eight policy frameworks related to green urban planning and development was done based on four GI principles: multifunctionality, connectivity, interdisciplinary and social inclusion. We interviewed 15 key informants in related departments in the city and administered 200 survey questionnaires among residents. We also had several workshops the other researchers and experts on biodiversity and ecosystem. We found out there is no specific document dedicated to green space management, and where green infrastructure was mentioned, it was focused on as an approach to climate mitigation and adaptation. Also, residents perceive green and open spaces as extra land that could be developed at will. We demonstrated the use of collaborative learning approaches in ecological and development research and the tying research to the existing frameworks, programs, and strategies. Based on this understanding. We outlined the need to incorporate principles of green infrastructure in policy frameworks on spatial planning and environmental development. Furthermore, we develop a model for co-management of green infrastructures by stakeholders, such as residents, developers, policymakers, and decision-makers, to maximize benefits. Our collaborative, interdisciplinary projects pursue SDG multifunctionality of goals 11 and 15 by simultaneously addressing issues around Sustainable Cities and Communities, Climate Action, Life on Land, and Strong Institutions, and halt and reverse land degradation and biodiversity.

Keywords: governance, green infrastructure, South Africa, sustainable development, urban planning, Tshwane

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Authors: Farshad Ghassemi Toosi, Nikola S. Nikolov

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We present a visualization technique for radial drawing of trees consisting of two slightly different algorithms. Both of them make use of node-link diagrams for visual encoding. This visualization creates clear drawings without edge crossing. One of the algorithms is suitable for real-time visualization of large trees, as it requires minimal recalculation of the layout if leaves are inserted or removed from the tree; while the other algorithm makes better utilization of the drawing space. The algorithms are very similar and follow almost the same procedure but with different parameters. Both algorithms assign angular coordinates for all nodes which are then converted into 2D Cartesian coordinates for visualization. We present both algorithms and discuss how they compare to each other.

Keywords: Radial drawing, Visualization, Algorithm, Use of node-link diagrams

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Authors: Sirapop Nuannimnoi, Hojjat Baghban, Ching-Yao Huang

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Over the past decade, with the fast development of blockchain technology since the birth of Bitcoin, there has been a massive increase in the usage of Cryptocurrencies. Cryptocurrencies are not seen as an investment opportunity due to the market’s erratic behavior and high price volatility. With the recent success of deep reinforcement learning (DRL), portfolio management can be modeled and automated. In this paper, we propose a novel DRL-based multi-agent system to automatically make proper trading decisions on multiple cryptocurrencies and gain profits in the highly volatile cryptocurrency market. We also extend this multi-agent system with horizontal federated transfer learning for better adapting to the inclusion of new cryptocurrencies in our portfolio; therefore, we can, through the concept of diversification, maximize our profits and minimize the trading risks. Experimental results through multiple simulation scenarios reveal that this proposed algorithmic trading system can offer three promising key advantages over other systems, including maximized profits, minimized risks, and adaptability.

Keywords: cryptocurrency portfolio management, algorithmic trading, federated learning, multi-agent reinforcement learning

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Authors: Hsiao-Ting Huang, Chang Hsueh-Sheng

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Taiwan is an island country which is affected by the monsoon deeply. Under the climate change, the frequency of extreme rainstorm by typhoon becomes more and more often Since 2000. When the extreme rainstorm comes, it will cause serious damage in Taiwan, especially in urban area. It is suffered by the flooding and the government take it as the urgent issue. On the past, the land use of urban planning does not take flood-detention into consideration. With the development of the city, the impermeable surface increase and most of the people live in urban area. It means there is the highly vulnerability in the urban area, but it cannot deal with the surface runoff and the flooding. However, building the detention pond in hydraulic engineering way to solve the problem is not feasible in urban area. The land expropriation is the most expensive construction of the detention pond in the urban area, and the government cannot afford it. Therefore, the management strategy of flooding in urban area should use the existing resource, public facilities land. It can archive the performance of flood-detention through providing the public facilities land with the detention function. As multi-use public facilities land, it also can show the combination of the land use and water agency. To this purpose, this research generalizes the factors of multi-use for public facilities land as flood-detention space with literature review. The factors can be divided into two categories: environmental factors and conditions of public facilities. Environmental factors including three factors: the terrain elevation, the inundation potential and the distance from the drainage system. In the other hand, there are six factors for conditions of public facilities, including area, building rate, the maximum of available ratio etc. Each of them will be according to it characteristic to given the weight for the land use suitability analysis. This research selects the rules of combination from the logical combination. After this process, it can be classified into three suitability levels. Then, three suitability levels will input to the physiographic inundation model for simulating the evaluation of flood-detention respectively. This study tries to respond the urgent issue in urban area and establishes a model of multi-use for public facilities land as flood-detention through the systematic research process of this study. The result of this study can tell which combination of the suitability level is more efficacious. Besides, The model is not only standing on the side of urban planners but also add in the point of view from water agency. Those findings may serve as basis for land use indicators and decision-making references for concerned government agencies.

Keywords: flooding management strategy, land use suitability analysis, multi-use for public facilities land, physiographic inundation model

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Authors: Justin Reverdi, Sixin Zhang, Saïd Aoues, Fabrice Gamboa, Serge Gratton, Thomas Pellegrini

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In vapor cycle systems, the mass flow sensor plays a key role for different monitoring and control purposes. However, physical sensors can be inaccurate, heavy, cumbersome, expensive, or highly sensitive to vibrations, which is especially problematic when embedded into an aircraft. The conception of a virtual sensor, based on other standard sensors, is a good alternative. This paper has two main objectives. Firstly, a data-driven model using a convolutional neural network is proposed to estimate the mass flow of the compressor. We show that it significantly outperforms the standard polynomial regression model (thermodynamic maps) in terms of the standard MSE metric and engineer performance metrics. Secondly, a semi-automatic segmentation method is proposed to compute the engineer performance metrics for real datasets, as the standard MSE metric may pose risks in analyzing the dynamic behavior of vapor cycle systems.

Keywords: deep learning, convolutional neural network, vapor cycle system, virtual sensor

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Authors: S. J. Addinell, A. F. Grabsch, P. D. Fawell, B. Evans

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The Deep Exploration Technologies Cooperative Research Centre (DET CRC) is researching and developing a new coiled tubing based greenfields mineral exploration drilling system utilising down-hole water-powered percussive drill tooling. This new drilling system is aimed at significantly reducing the costs associated with identifying mineral resource deposits beneath deep, barren cover. This system has shown superior rates of penetration in water-rich, hard rock formations at depths exceeding 500 metres. With fluid flow rates of up to 120 litres per minute at 200 bar operating pressure to energise the bottom hole tooling, excessive quantities of high quality drilling fluid (water) would be required for a prolonged drilling campaign. As a result, drilling fluid recovery and recycling has been identified as a necessary option to minimise costs and logistical effort. While the majority of the cuttings report as coarse particles, a significant fines fraction will typically also be present. To maximise tool life longevity, the percussive bottom hole assembly requires high quality fluid with minimal solids loading and any recycled fluid needs to have a solids cut point below 40 microns and a concentration less than 400 ppm before it can be used to reenergise the system. This paper presents experimental results obtained from the research program during laboratory and field testing of the prototype drilling system. A study of the morphological aspects of the cuttings generated during the percussive drilling process shows a strong power law relationship for particle size distributions. This data is critical in optimising solids control strategies and cuttings dewatering techniques. Optimisation of deployable solids control equipment is discussed and how the required centrate clarity was achieved in the presence of pyrite-rich metasediment cuttings. Key results were the successful pre-aggregation of fines through the selection and use of high molecular weight anionic polyacrylamide flocculants and the techniques developed for optimal dosing prior to scroll decanter centrifugation, thus keeping sub 40 micron solids loading within prescribed limits. Experiments on maximising fines capture in the presence of thixotropic drilling fluid additives (e.g. Xanthan gum and other biopolymers) are also discussed. As no core is produced during the drilling process, it is intended that the particle laden returned drilling fluid is used for top-of-hole geochemical and mineralogical assessment. A discussion is therefore presented on the biasing and latency of cuttings representivity by dewatering techniques, as well as the resulting detrimental effects on depth fidelity and accuracy. Data pertaining to the sample biasing with respect to geochemical signatures due to particle size distributions is presented and shows that, depending on the solids control and dewatering techniques used, it can have unwanted influence on top-of-hole analysis. Strategies are proposed to overcome these effects, improving sample quality. Successful solids control and cuttings dewatering for water-powered percussive drilling is presented, contributing towards the successful advancement of coiled tubing based greenfields mineral exploration.

Keywords: cuttings, dewatering, flocculation, percussive drilling, solids control

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Authors: William Whiteley, Jens Gregor

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In recent developments of direct neural network based positron emission tomography (PET) reconstruction, two prominent architectures have emerged for converting measurement data into images: 1) networks that contain fully-connected layers; and 2) networks that primarily use a convolutional encoder-decoder architecture. In this paper, we present a multi-modal direct PET reconstruction method called MDPET, which is a hybrid approach that combines the advantages of both types of networks. MDPET processes raw data in the form of sinograms and histo-images in concert with attenuation maps to produce high quality multi-slice PET images (e.g., 8x440x440). MDPET is trained on a large whole-body patient data set and evaluated both quantitatively and qualitatively against target images reconstructed with the standard PET reconstruction benchmark of iterative ordered subsets expectation maximization. The results show that MDPET outperforms the best previously published direct neural network methods in measures of bias, signal-to-noise ratio, mean absolute error, and structural similarity.

Keywords: deep learning, image reconstruction, machine learning, neural network, positron emission tomography

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Authors: Naman Solanki, Souraj Mondal

Abstract:

With the world moving towards online communication, the video datastore has exploded in the past few years. Consequently, it has become crucial to analyse participant’s engagement levels in online communication videos. Engagement prediction of people in videos can be useful in many domains, like education, client meetings, dating, etc. Video-level or frame-level prediction of engagement for a user involves the development of robust models that can capture facial micro-emotions efficiently. For the development of an engagement prediction model, it is necessary to have a widely-accepted standard dataset for engagement analysis. DAiSEE is one of the datasets which consist of in-the-wild data and has a gold standard annotation for engagement prediction. Earlier research done using the DAiSEE dataset involved training and testing standard models like CNN-based models, but the results were not satisfactory according to industry standards. In this paper, a multi-level classification approach has been introduced to create a more robust model for engagement analysis using the DAiSEE dataset. This approach has recorded testing accuracies of 0.638, 0.7728, 0.8195, and 0.866 for predicting boredom level, engagement level, confusion level, and frustration level, respectively.

Keywords: computer vision, engagement prediction, deep learning, multi-level classification

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Authors: Cristina Galiana Carballo, Ibon Doval Martínez

Abstract:

Urban boundaries often result in a controversial limit between countryside and city in Europe. This territory is normally defined by the very limited land uses and the abundance of open space. The dimension and dynamics of peri-urbanization in the last decades have increased this land stock, which has influenced/impacted in several factors in terms of economic costs (maintenance, transport), ecological disturbances of the territory and changes in inhabitant´s behaviour. In an increasingly urbanised world and a growing urban population, cities also face challenges such as Climate Change. In this context, new near-future corrective trends including circular economies for local food supply or decentralised waste management became key strategies towards more sustainable urban models. Those new solutions need to be planned and implemented considering the potential conflict with current land uses. The city of Vitoria-Gasteiz (Basque Country, Spain) has triplicated land consumption per habitant in 10 years, resulting in a vast extension of low-density urban type confronting rural land and threatening agricultural uses, landscape and urban sustainability. Urban planning allows managing and optimum use allocation based on soil vocation and socio-ecosystem needs, while peri-urban space arises as an opportunity for developing different uses which do not match either within the compact city, not in open agricultural lands, such as medium-size agrocomposting systems or biomass plants. Therefore, a qualitative multi-criteria methodology has been developed for Vitoria-Gasteiz city to assess the spatial definition of peri-urban land. Therefore, a qualitative multi-criteria methodology has been developed for Vitoria-Gasteiz city to assess the spatial definition of peri-urban land. Climate change and circular economy were identified as frameworks where to determine future land, soil vocation and urban planning requirements which eventually become estimations of required local food and renewable energy supply along with alternative waste management system´s implementation. By means of it, it has been developed an urban planning proposal which overcomes urban-non urban dichotomy in Vitoria-Gasteiz. The proposal aims to enhance rural system and improve urban sustainability performance through the normative recognition of an agricultural peri-urban belt.

Keywords: landscape ecology, land-use management, periurban, urban planning

Procedia PDF Downloads 163

Authors: Hassan Al Salman, Ahmed Al Ghafli

Abstract:

In this study we consider a nonlinear in time finite element approximation of a reaction diffusion system of lambda-omega type. We use a fixed point theorem to prove existence of the approximations. Then, we derive some essential stability estimates and discuss the uniqueness of the approximations. Also, we prove an optimal error bound in time for d=1, 2 and 3 space dimensions. Finally, we present some numerical experiments to verify the theoretical results.

Keywords: reaction diffusion system, finite element approximation, fixed point theorem, an optimal error bound

Procedia PDF Downloads 533