Search results for: carbon estimation algorithm

Authors: Dalia El Hadi, Alaa Bou Ghannam, Hala Mostafa, Hana Mansour, Ibrahim Hashim, Soubhi Tahhan, Tharwat El Zahran

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Introduction: Neuro-ophthalmological emergencies require prompt assessment and management to avoid vision or life-threatening sequelae. Some would require neuroimaging. Most commonly used are the CT and MRI of the Brain. They can be over-used when not indicated. Their yield remains dependent on multiple factors relating to the clinical scenario. Methods: A retrospective cross-sectional study was conducted by reviewing the electronic medical records of patients presenting to the Emergency Department (ED) with isolated neuro-ophthalmologic complaints. For each patient, data were collected on the clinical presentation, whether neuroimaging was performed (and which type), and the result of neuroimaging. Analysis of the performed neuroimaging was made, and its yield was determined. Results: A total of 211 patients were reviewed. The complaints or symptoms at presentation were: blurry vision, change in the visual field, transient vision loss, floaters, double vision, eye pain, eyelid droop, headache, dizziness and others such as nausea or vomiting. In the ED, a total of 126 neuroimaging procedures were performed. Ninety-four imagings (74.6%) were normal, while 32 (25.4%) had relevant abnormal findings. Only 2 symptoms were significant for abnormal imaging: blurry vision (p-value= 0.038) and visual field change (p-value= 0.014). While 4 physical exam findings had significant abnormal imaging: visual field defect (p-value= 0.016), abnormal pupil reactivity (p-value= 0.028), afferent pupillary defect (p-value= 0.018), and abnormal optic disc exam (p-value= 0.009). Conclusion: Risk indicators for abnormal neuroimaging in the setting of neuro-ophthalmological emergencies are blurred vision or changes in the visual field on history taking. While visual field irregularities, abnormal pupil reactivity with or without afferent pupillary defect, or abnormal optic discs, are risk factors related to physical testing. These findings, when present, should sway the ED physician towards neuroimaging but still individualizing each case is of utmost importance to prevent time-consuming, resource-draining, and sometimes unnecessary workup. In the end, it suggests a well-structured patient-centered algorithm to be followed by ED physicians.

Keywords: emergency department, neuro-ophthalmology, neuroimaging, risk indicators

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Authors: Siba Soren, Purnendu Parhi

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Today, the world is facing a severe challenge due to depletion of traditional fossil fuels. Scientists across the globe are working for a solution that involves a dramatic shift to practical and environmentally sustainable energy sources. High-capacity energy systems, such as metal-air batteries, fuel cells, are highly desirable to meet the urgent requirement of sustainable energies. Among the fuel cells, Direct methanol fuel cells (DMFCs) are recognized as an ideal power source for mobile applications and have received considerable attention in recent past. In this advanced electrochemical energy conversion technologies, Oxygen Reduction Reaction (ORR) is of utmost importance. However, the poor kinetics of cathodic ORR in DMFCs significantly hampers their possibilities of commercialization. The oxygen is reduced in alkaline medium either through a 4-electron (equation i) or a 2-electron (equation ii) reduction pathway at the cathode ((i) O₂ + 2H₂O + 4e⁻ → 4OH⁻, (ii) O₂ + H₂O + 2e⁻ → OH⁻ + HO₂⁻ ). Due to sluggish ORR kinetics the ability to control the reduction of molecular oxygen electrocatalytically is still limited. The electrocatalytic ORR starts with adsorption of O₂ on the electrode surface followed by O–O bond activation/cleavage and oxide removal. The reaction further involves transfer of 4 electrons and 4 protons. The sluggish kinetics of ORR, on the one hand, demands high loading of precious metal-containing catalysts (e.g., Pt), which unfavorably increases the cost of these electrochemical energy conversion devices. Therefore, synthesis of active electrocatalyst with an increase in ORR performance is need of the hour. In the recent literature, there are many reports on transition metal oxide (TMO) based ORR catalysts for their high activity TMOs are also having drawbacks like low electrical conductivity, which seriously affects the electron transfer process during ORR. It was found that 2D graphene layer is having high electrical conductivity, large surface area, and excellent chemical stability, appeared to be an ultimate choice as support material to enhance the catalytic performance of bare metal oxide. g-C₃N₄ is also another candidate that has been used by the researcher for improving the ORR performance of metal oxides. This material provides more active reaction sites than other N containing carbon materials. Rare earth oxide like CeO₂ is also a good candidate for studying the ORR activity as the metal oxide not only possess unique electronic properties but also possess catalytically active sites. Here we will discuss the ORR performance (in alkaline medium) of N-rGO/C₃N₄ supported nano Cerium Oxides hybrid synthesized by microwave assisted Solvothermal method. These materials exhibit superior electrochemical stability and methanol tolerance capability to that of commercial Pt/C.

Keywords: oxygen reduction reaction, electrocatalyst, cerium oxide, graphene

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Authors: Branimir Jurun, Elza Jurun

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The focus of this paper is the description of an instrument called 'Quattuor 45' and defining of wave pressure measurement. Special attention is given to measurement of wave pressure created by the wind speed increasing obtained with the instrument 'Quattuor 45' in the investigated area. The study begins with respect to theoretical attitudes and numerous up to date investigations related to the waves approaching the coast. The detailed schematic view of the instrument is enriched with pictures from ground plan and side view. Horizontal stability of the instrument is achieved by mooring which relies on two concrete blocks. Vertical wave peak monitoring is ensured by one float above the instrument. The synthesis of horizontal stability and vertical wave peak monitoring allows to create a representative database for wave pressure measuring. Instrument ‘Quattuor 45' is named according to the way the database is received. Namely, the electronic part of the instrument consists of the main chip ‘Arduino', its memory, four load cells with the appropriate modules and the wind speed sensor 'Anemometers'. The 'Arduino' chip is programmed to store two data from each load cell and two data from the anemometer on SD card each second. The next part of the research is dedicated to data processing. All measured results are stored automatically in the database and after that detailed processing is carried out in the MS Excel. The result of the wave pressure measurement is synthesized by the unit of measurement kN/m². This paper also suggests a graphical presentation of the results by multi-line graph. The wave pressure is presented on the left vertical axis, while the wind speed is shown on the right vertical axis. The time of measurement is displayed on the horizontal axis. The paper proposes an algorithm for wind speed measurements showing the results for two characteristic winds in the Adriatic Sea, called 'Bura' and 'Jugo'. The first of them is the northern wind that reaches high speeds, causing low and extremely steep waves, where the pressure of the wave is relatively weak. On the other hand, the southern wind 'Jugo' has a lower speed than the northern wind, but due to its constant duration and constant speed maintenance, it causes extremely long and high waves that cause extremely high wave pressure.

Keywords: instrument, measuring unit, waves pressure metering, wind seed measurement

Procedia PDF Downloads 174

Authors: Shubham Kumar, Chaitanya Goswami, Sudipto Sarkar

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Pseudoplastic (n < 1, n being the power index) fluid flow can be found in food, pharmaceutical and process industries and has very complex flow nature. To our knowledge, inadequate research work has been done in this kind of flow even at very low Reynolds numbers. Here, in the present computation, we have considered unsteady laminar flow over a square cylinder in pseudoplastic flow environment. For Newtonian fluid flow, this laminar vortex shedding range lies between Re = 47-180. In this problem, we consider Re = 100 (Re = U∞ a/ ν, U∞ is the free stream velocity of the flow, a is the side of the cylinder and ν is the kinematic viscosity of the fluid). The pseudoplastic fluid range has been chosen from close to the Newtonian fluid (n = 0.8) to very high pseudoplasticity (n = 0.1). The flow domain is constituted using Gambit 2.2.30 and this software is also used to generate mesh and to impose the boundary conditions. For all places, the domain size is considered as 36a × 16a with 280 ×192 grid point in the streamwise and flow normal directions respectively. The domain and the grid points are selected after a thorough grid independent study at n = 1.0. Fine and equal grid spacing is used close to the square cylinder to capture the upper and lower shear layers shed from the cylinder. Away from the cylinder the grid is unequal in size and stretched out in all direction. Velocity inlet (u = U∞), pressure outlet (Neumann condition), symmetry (free-slip boundary condition du/dy = 0, v = 0) at upper and lower domain boundary conditions are used for this simulation. Wall boundary (u = v = 0) is considered on the square cylinder surface. Fully conservative 2-D unsteady Navier-Stokes equations are discretized and then solved by Ansys Fluent 14.5 to understand the flow nature. SIMPLE algorithm written in finite volume method is selected for this purpose which is the default solver in scripted in Fluent. The result obtained for Newtonian fluid flow agrees well with previous work supporting Fluent’s usefulness in academic research. A minute analysis of instantaneous and time averaged flow field is obtained both for Newtonian and pseudoplastic fluid flow. It has been observed that drag coefficient increases continuously with the reduced value of n. Also, the vortex shedding phenomenon changes at n = 0.4 due to flow instability. These are some of the remarkable findings for laminar periodic vortex shedding regime in pseudoplastic flow environment.

Keywords: Ansys Fluent, CFD, periodic vortex shedding, pseudoplastic fluid flow

Procedia PDF Downloads 158

Authors: Kostas Kouvaris, Anastasia Eleftheriou, Georgios A. Sarantitis, Apostolos Chondronasios

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To achieve the objective of almost zero carbon energy solutions by 2050, the EU needs to accelerate the development of integrated, highly efficient and environmentally friendly solutions. In this direction, district heating and cooling (DHC) emerges as a viable and more efficient alternative to conventional, decentralized heating and cooling systems, enabling a combination of more efficient renewable and competitive energy supplies. In this paper, we develop a forecasting tool for near real-time local weather and thermal energy demand predictions for an entire DHC network. In this fashion, we are able to extend the functionality and to improve the energy efficiency of the DHC network by predicting and adjusting the heat load that is distributed from the heat generation plant to the connected buildings by the heat pipe network. Two case-studies are considered; one for Vransko, Slovenia and one for Montpellier, France. The data consists of i) local weather data, such as humidity, temperature, and precipitation, ii) weather forecast data, such as the outdoor temperature and iii) DHC operational parameters, such as the mass flow rate, supply and return temperature. The external temperature is found to be the most important energy-related variable for space conditioning, and thus it is used as an external parameter for the energy demand models. For the development of the forecasting tool, we use state-of-the-art deep neural networks and more specifically, recurrent networks with long-short-term memory cells, which are able to capture complex non-linear relations among temporal variables. Firstly, we develop models to forecast outdoor temperatures for the next 24 hours using local weather data for each case-study. Subsequently, we develop models to forecast thermal demand for the same period, taking under consideration past energy demand values as well as the predicted temperature values from the weather forecasting models. The contributions to the scientific and industrial community are three-fold, and the empirical results are highly encouraging. First, we are able to predict future thermal demand levels for the two locations under consideration with minimal errors. Second, we examine the impact of the outdoor temperature on the predictive ability of the models and how the accuracy of the energy demand forecasts decreases with the forecast horizon. Third, we extend the relevant literature with a new dataset of thermal demand and examine the performance and applicability of machine learning techniques to solve real-world problems. Overall, the solution proposed in this paper is in accordance with EU targets, providing an automated smart energy management system, decreasing human errors and reducing excessive energy production.

Keywords: machine learning, LSTMs, district heating and cooling system, thermal demand

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Authors: May Fadheel Estephan, Richard Perks

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Context: Cancer is a serious health concern that affects millions of people worldwide. Early detection and treatment are essential for improving patient outcomes. However, current methods for cancer detection have limitations, such as low sensitivity and specificity. Research Aim: The aim of this study was to develop an optical sensor for cancer detection using elastic light scattering spectroscopy (ELSS). ELSS is a noninvasive optical technique that can be used to characterize the size and concentration of particles in a solution. Methodology: An optical probe was fabricated with a 100-μm-diameter core and a 132-μm centre-to-centre separation. The probe was used to measure the ELSS spectra of polystyrene spheres with diameters of 2, 0.8, and 0.413 μm. The spectra were then analysed to determine the size and concentration of the spheres. Findings: The results showed that the optical probe was able to differentiate between the three different sizes of polystyrene spheres. The probe was also able to detect the presence of polystyrene spheres in suspension concentrations as low as 0.01%. Theoretical Importance: The results of this study demonstrate the potential of ELSS for cancer detection. ELSS is a noninvasive technique that can be used to characterize the size and concentration of cells in a tissue sample. This information can be used to identify cancer cells and assess the stage of the disease. Data Collection: The data for this study were collected by measuring the ELSS spectra of polystyrene spheres with different diameters. The spectra were collected using a spectrometer and a computer. Analysis Procedures: The ELSS spectra were analysed using a software program to determine the size and concentration of the spheres. The software program used a mathematical algorithm to fit the spectra to a theoretical model. Question Addressed: The question addressed by this study was whether ELSS could be used to detect cancer cells. The results of the study showed that ELSS could be used to differentiate between different sizes of cells, suggesting that it could be used to detect cancer cells. Conclusion: The findings of this research show the utility of ELSS in the early identification of cancer. ELSS is a noninvasive method for characterizing the number and size of cells in a tissue sample. To determine cancer cells and determine the disease's stage, this information can be employed. Further research is needed to evaluate the clinical performance of ELSS for cancer detection.

Keywords: elastic light scattering spectroscopy, polystyrene spheres in suspension, optical probe, fibre optics

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Authors: Guenther Schuh, Michael Riesener, Frederic Diels

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Nowadays, manufacturing companies are faced with the challenge of meeting heterogeneous customer requirements in short product life cycles with a variety of product functions. So far, some of the functional requirements remain unknown until late stages of the product development. A way to handle these uncertainties is the highly iterative product development (HIP) approach. By structuring the development project as a highly iterative process, this method provides customer oriented and marketable products. There are first approaches for combined, hybrid models comprising deterministic-normative methods like the Stage-Gate process and empirical-adaptive development methods like SCRUM on a project management level. However, almost unconsidered is the question, which development scopes can preferably be realized with either empirical-adaptive or deterministic-normative approaches. In this context, a development scope constitutes a self-contained section of the overall development objective. Therefore, this paper focuses on a methodology that deals with the uncertainty of requirements within the early development stages and the corresponding selection of the most appropriate development approach. For this purpose, internal influencing factors like a company’s technology ability, the prototype manufacturability and the potential solution space as well as external factors like the market accuracy, relevance and volatility will be analyzed and combined into an Agile-Indicator. The Agile-Indicator is derived in three steps. First of all, it is necessary to rate each internal and external factor in terms of the importance for the overall development task. Secondly, each requirement has to be evaluated for every single internal and external factor appropriate to their suitability for empirical-adaptive development. Finally, the total sums of internal and external side are composed in the Agile-Indicator. Thus, the Agile-Indicator constitutes a company-specific and application-related criterion, on which the allocation of empirical-adaptive and deterministic-normative development scopes can be made. In a last step, this indicator will be used for a specific clustering of development scopes by application of the fuzzy c-means (FCM) clustering algorithm. The FCM-method determines sub-clusters within functional clusters based on the empirical-adaptive environmental impact of the Agile-Indicator. By means of the methodology presented in this paper, it is possible to classify requirements, which are uncertainly carried out by the market, into empirical-adaptive or deterministic-normative development scopes.

Keywords: agile, highly iterative development, agile-indicator, product development

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Authors: Marco Frieslaar, Bing Chu, Eric Rogers

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Stroke is a devastating illness that is the second biggest cause of death in the world (after heart disease). Where it does not kill, it leaves survivors with debilitating sensory and physical impairments that not only seriously harm their quality of life, but also cause a high incidence of severe depression. It is widely accepted that early intervention is essential for recovery, but current rehabilitation techniques largely favor hospital-based therapies which have restricted access, expensive and specialist equipment and tend to side-step the emotional challenges. In addition, there is insufficient funding available to provide the long-term assistance that is required. As a consequence, recovery rates are poor. The relatively unexplored solution is to develop therapies that can be harnessed in the home and are formulated from technologies that already exist in everyday life. This would empower individuals to take control of their own improvement and provide choice in terms of when and where they feel best able to undertake their own healing. This research seeks to identify how effective post-stroke, rehabilitation therapy can be applied to upper limb mobility, within the physical context of a home rather than a hospital. This is being achieved through the design and construction of an automation scheme, based on iterative learning control and the Riener muscle model, that has the ability to adapt to the user and react to their level of fatigue and provide tangible physical recovery. It utilizes a SMART Phone and laptop to construct an iterative learning control (ILC) system, that monitors upper arm movement in three dimensions, as a series of exercises are undertaken. The equipment generates functional electrical stimulation to assist in muscle activation and thus improve directional accuracy. In addition, it monitors speed, accuracy, areas of motion weakness and similar parameters to create a performance index that can be compared over time and extrapolated to establish an independent and objective assessment scheme, plus an approximate estimation of predicted final outcome. To further extend its assessment capabilities, nerve conduction velocity readings are taken by the software, between the shoulder and hand muscles. This is utilized to measure the speed of response of neuron signal transfer along the arm and over time, an online indication of regeneration levels can be obtained. This will prove whether or not sufficient training intensity is being achieved even before perceivable movement dexterity is observed. The device also provides the option to connect to other users, via the internet, so that the patient can avoid feelings of isolation and can undertake movement exercises together with others in a similar position. This should create benefits not only for the encouragement of rehabilitation participation, but also an emotional support network potential. It is intended that this approach will extend the availability of stroke recovery options, enable ease of access at a low cost, reduce susceptibility to depression and through these endeavors, enhance the overall recovery success rate.

Keywords: home-based therapy, iterative learning control, Riener muscle model, SMART phone, stroke rehabilitation

Procedia PDF Downloads 243

Authors: Patrizia Frontera, Anastasia Macario, Sebastiano Candamano, Fortunato Crea, Pierluigi Antonucci

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The increasing of the world energy demand makes today biomass an attractive energy source, based on the minimizing of CO2 emission and on the global warming reduction purposes. Recently, COP-21, the international meeting on global climate change, defined the roadmap for sustainable worldwide development, based on low-carbon containing fuel. Hydrogen is an energy vector able to substitute the conventional fuels from petroleum. Ethanol for hydrogen production represents a valid alternative to the fossil sources due to its low toxicity, low production costs, high biodegradability, high H2 content and renewability. Ethanol conversion to generate hydrogen by a combination of partial oxidation and steam reforming reactions is generally called auto-thermal reforming (ATR). The ATR process is advantageous due to the low energy requirements and to the reduced carbonaceous deposits formation. Catalyst plays a pivotal role in the ATR process, especially towards the process selectivity and the carbonaceous deposits formation. Bimetallic or trimetallic catalysts, as well as catalysts with doped-promoters supports, may exhibit high activity, selectivity and deactivation resistance with respect to the corresponding monometallic ones. In this work, NiMoCo/GDC, NiMoCu/GDC and NiMoRe/GDC (where GDC is Gadolinia Doped Ceria support and the metal composition is 60:30:10 for all catalyst) have been prepared by impregnation method. The support, Gadolinia 0.2 Doped Ceria 0.8, was impregnated by metal precursors solubilized in aqueous ethanol solution (50%) at room temperature for 6 hours. After this, the catalysts were dried at 100°C for 8 hours and, subsequently, calcined at 600°C in order to have the metal oxides. Finally, active catalysts were obtained by reduction procedure (H2 atmosphere at 500°C for 6 hours). All sample were characterized by different analytical techniques (XRD, SEM-EDX, XPS, CHNS, H2-TPR and Raman Spectorscopy). Catalytic experiments (auto-thermal reforming of ethanol) were carried out in the temperature range 500-800°C under atmospheric pressure, using a continuous fixed-bed microreactor. Effluent gases from the reactor were analyzed by two Varian CP4900 chromarographs with a TCD detector. The analytical investigation focused on the preventing of the coke deposition, the metals sintering effect and the sulfur poisoning. Hydrogen productivity, ethanol conversion and products distribution were measured and analyzed. At 600°C, all tri-metallic catalysts show the best performance: H2 + CO reaching almost the 77 vol.% in the final gases. While NiMoCo/GDC catalyst shows the best selectivity to hydrogen whit respect to the other tri-metallic catalysts (41 vol.% at 600°C). On the other hand, NiMoCu/GDC and NiMoRe/GDC demonstrated high sulfur poisoning resistance (up to 200 cc/min) with respect to the NiMoCo/GDC catalyst. The correlation among catalytic results and surface properties of the catalysts will be discussed.

Keywords: catalysts, ceria, ethanol, gadolinia, hydrogen, Nickel

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Authors: Ana Bermudez de Castro Muela, Xiomara Santos Salas, Silvia Cayon Somacarrera

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The aim of this review is to explain what is the intracranial hypotension and its main causes, and also to approach to the diagnostic management in the different clinical situations, understanding radiological findings, and physiopathological substrate. An approach to the diagnostic management is presented: what are the guidelines to follow, the different tests available, and the typical findings. We review the myelo-CT and myelo-RM studies in patients with suspected CSF fistula or hypotension of unknown cause during the last 10 years in three centers. Signs of intracranial hypotension (subdural hygromas/hematomas, pachymeningeal enhancement, venous sinus engorgement, pituitary hyperemia, and lowering of the brain) that are evident in baseline CT and MRI are also sought. The intracranial hypotension is defined as a lower opening pressure of 6 cmH₂O. It is a relatively rare disorder with an annual incidence of 5 per 100.000, with a female to male ratio 2:1. The clinical features it’s an orthostatic headache, which is defined as development or aggravation of headache when patients move from a supine to an upright position and disappear or typically relieve after lay down. The etiology is a decrease in the amount of cerebrospinal fluid (CSF), usually by loss of it, either spontaneous or secondary (post-traumatic, post-surgical, systemic disease, post-lumbar puncture etc.) and rhinorrhea and/or otorrhea may exist. The pathophysiological mechanisms of hypotension and CSF hypertension are interrelated, as a situation of hypertension may lead to hypotension secondary to spontaneous CSF leakage. The diagnostic management of intracranial hypotension in our center includes, in the case of being spontaneous and without rhinorrhea and/or otorrhea and according to necessity, a range of available tests, which will be performed from less to more complex: cerebral CT, cerebral MRI and spine without contrast and CT/MRI with intrathecal contrast. If we are in a situation of intracranial hypotension with the presence of rhinorrhea/otorrhea, a sample can be obtained for the detection of b2-transferrin, which is found in the CSF physiologically, as well as sinus CT and cerebral MRI including constructive interference steady state (CISS) sequences. If necessary, cisternography studies are performed to locate the exact point of leakage. It is important to emphasize the significance of myelo-CT / MRI to establish the diagnosis and location of CSF leak, which is indispensable for therapeutic planning (whether surgical or not) in patients with more than one lesion or doubts in the baseline tests.

Keywords: cerebrospinal fluid, neuroradiology brain, magnetic resonance imaging, fistula

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Authors: Ella Sèdé Maforikan

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Accurate land cover mapping is essential for effective environmental monitoring and natural resources management. This study focuses on assessing the classification performance of two satellite datasets and evaluating the impact of different input feature combinations on classification accuracy in the Beterou catchment, situated in the northern part of Benin. Landsat-8 and Sentinel-2 images from June 1, 2020, to March 31, 2021, were utilized. Employing the Random Forest (RF) algorithm on Google Earth Engine (GEE), a supervised classification categorized the land into five classes: forest, savannas, cropland, settlement, and water bodies. GEE was chosen due to its high-performance computing capabilities, mitigating computational burdens associated with traditional land cover classification methods. By eliminating the need for individual satellite image downloads and providing access to an extensive archive of remote sensing data, GEE facilitated efficient model training on remote sensing data. The study achieved commendable overall accuracy (OA), ranging from 84% to 85%, even without incorporating spectral indices and terrain metrics into the model. Notably, the inclusion of additional input sources, specifically terrain features like slope and elevation, enhanced classification accuracy. The highest accuracy was achieved with Sentinel-2 (OA = 91%, Kappa = 0.88), slightly surpassing Landsat-8 (OA = 90%, Kappa = 0.87). This underscores the significance of combining diverse input sources for optimal accuracy in land cover mapping. The methodology presented herein not only enables the creation of precise, expeditious land cover maps but also demonstrates the prowess of cloud computing through GEE for large-scale land cover mapping with remarkable accuracy. The study emphasizes the synergy of different input sources to achieve superior accuracy. As a future recommendation, the application of Light Detection and Ranging (LiDAR) technology is proposed to enhance vegetation type differentiation in the Beterou catchment. Additionally, a cross-comparison between Sentinel-2 and Landsat-8 for assessing long-term land cover changes is suggested.

Keywords: land cover mapping, Google Earth Engine, random forest, Beterou catchment

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Authors: Mazarine Roquet, Pierre Dewallef

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The building sector, both residential and tertiary, accounts for a significant share of greenhouse gas emissions. In Belgium, partly due to poor insulation of the building stock, but certainly because of the massive use of fossil fuels for heating buildings, this share reaches almost 30%. To reduce carbon emissions from urban building heating, district heating networks emerge as a promising solution as they offer various assets such as improving the load factor, integrating combined heat and power systems, and enabling energy source diversification, including renewable sources and waste heat recovery. However, mainly for sake of simple operation, most existing district heating networks still operate at high or medium temperatures ranging between 120°C and 60°C (the socalled second and third-generations district heating networks). Although these district heating networks offer energy savings in comparison with individual boilers, such temperature levels generally require the use of fossil fuels (mainly natural gas) with combined heat and power. The fourth-generation district heating networks improve the transport and energy conversion efficiency by decreasing the operating temperature between 50°C and 30°C. Yet, to decarbonise the building heating one must increase the waste heat recovery and use mainly wind, solar or geothermal sources for the remaining heat supply. Fifth-generation networks operating between 35°C and 15°C offer the possibility to decrease even more the transport losses, to increase the share of waste heat recovery and to use electricity from renewable resources through the use of heat pumps to generate low temperature heat. The main objective of this contribution is to exhibit on a real-life test case the benefits of replacing an existing third-generation network by a fifth-generation one and to decarbonise the heat supply of the building stock. The second objective of the study is to highlight the difficulties resulting from the use of a fifth-generation, low-temperature, district heating network. To do so, a simulation model of the district heating network including its regulation is implemented in the modelling language Modelica. This model is applied to the test case of the heating network on the University of Liège's Sart Tilman campus, consisting of around sixty buildings. This model is validated with monitoring data and then adapted for low-temperature networks. A comparison of primary energy consumptions as well as CO2 emissions is done between the two cases to underline the benefits in term of energy independency and GHG emissions. To highlight the complexity of operating a lowtemperature network, the difficulty of adapting the mass flow rate to the heat demand is considered. This shows the difficult balance between the thermal comfort and the electrical consumption of the circulation pumps. Several control strategies are considered and compared to the global energy savings. The developed model can be used to assess the potential for energy and CO2 emissions savings retrofitting an existing network or when designing a new one.

Keywords: building simulation, fifth-generation district heating network, low-temperature district heating network, urban building heating

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Authors: Federico Capra, Emanuele Martelli, Matteo Gazzani, Marco Mazzotti, Maurizio Notaro

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Natural gas is a major energy source in the current global economy, contributing to roughly 21% of the total primary energy consumption. Production of natural gas starting from renewable energy sources is key to limit the related CO2 emissions, especially for those sectors that heavily rely on natural gas use. In this context, biomethane produced via biogas upgrading represents a good candidate for partial substitution of fossil natural gas. The upgrading process of biogas to biomethane consists in (i) the removal of pollutants and impurities (e.g. H2S, siloxanes, ammonia, water), and (ii) the separation of carbon dioxide from methane. Focusing on the CO2 removal process, several technologies can be considered: chemical or physical absorption with solvents (e.g. water, amines), membranes, adsorption-based systems (PSA). However, none emerged as the leading technology, because of (i) the heterogeneity in plant size, ii) the heterogeneity in biogas composition, which is strongly related to the feedstock type (animal manure, sewage treatment, landfill products), (iii) the case-sensitive optimal tradeoff between purity and recovery of biomethane, and iv) the destination of the produced biomethane (grid injection, CHP applications, transportation sector). With this contribution, we explore the use of a technology for biogas upgrading and we compare the resulting performance with benchmark technologies. The proposed technology makes use of a chemical sorbent, which is engineered by RSE and consists of Di-Ethanol-Amine deposited on a solid support made of γ-Alumina, to chemically adsorb the CO2 contained in the gas. The material is packed into fixed beds that cyclically undergo adsorption and regeneration steps. CO2 is adsorbed at low temperature and ambient pressure (or slightly above) while the regeneration is carried out by pulling vacuum and increasing the temperature of the bed (vacuum-temperature swing adsorption - VTSA). Dynamic adsorption tests were performed by RSE and were used to tune the mathematical model of the process, including material and transport parameters (i.e. Langmuir isotherms data and heat and mass transport). Based on this set of data, an optimal VTSA cycle was designed. The results enabled a better understanding of the interplay between material and cycle tuning. As exemplary application, the upgrading of biogas for grid injection, produced by an anaerobic digester (60-70% CO2, 30-40% CH4), for an equivalent size of 1 MWel was selected. A plant configuration is proposed to maximize heat recovery and minimize the energy consumption of the process. The resulting performances are very promising compared to benchmark solutions, which make the VTSA configuration a valuable alternative for biomethane production starting from biogas.

Keywords: biogas upgrading, biogas upgrading energetic cost, CO2 adsorption, VTSA process modelling

Procedia PDF Downloads 247

Authors: Xiaoyu Sun

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In recent years, the rapid development of Artificial Intelligence (AI) has extensively promoted medicine, pharmaceutical, and other related fields. The medical research and development of artificial intelligence by scientific and commercial organizations are on the fast track. The ethics review is one of the critical procedures of registration to get the products approved and launched. However, the SOPs for ethics review is not enough to guide the healthy and rapid development of artificial intelligence in healthcare in China. Ethical Review Measures for Biomedical Research Involving Human Beings was enacted by the National Health Commission of the People's Republic of China (NHC) on December 1st, 2016. However, from a legislative design perspective, it was neither updated timely nor in line with the trends of AI international development. Therefore, it was great that NHC published a consultation paper on the updated version on March 16th, 2021. Based on the most updated laws and regulations in the States and EU, and in-depth-interviewed 11 subject matter experts in China, including lawmakers, regulators, and key members of ethics review committees, heads of Regulatory Affairs in SaMD industry, and data scientists, several suggestions were proposed on top of the updated version. Although the new version indicated that the Ethics Review Committees need to be created by National, Provincial and individual institute levels, the review authorities of different levels were not clarified. The suggestion is that the precise scope of review authorities for each level should be identified based on Risk Analysis and Management Model, such as the complicated leading technology, gene editing, should be reviewed by National Ethics Review Committees, it will be the job of individual institute Ethics Review Committees to review and approve the clinical study with less risk such as an innovative cream to treat acne. Furthermore, to standardize the research and development of artificial intelligence in healthcare in the age of AI, more clear guidance should be given to data security in the layers of data, algorithm, and application in the process of ethics review. In addition, transparency and responsibility, as two of six principles in the Rome Call for AI Ethics, could be further strengthened in the updated version. It is the shared goal among all countries to manage well and develop AI to benefit human beings. Learned from the other countries who have more learning and experience, China could be one of the most advanced countries in artificial intelligence in healthcare.

Keywords: biomedical research involving human beings, data security, ethics committees, ethical review, medical artificial intelligence

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Authors: Igor Povar, Catherine Goyet

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The seawater is subject to multiple external stressors (ES) including rising atmospheric CO2 and ocean acidification, global warming, atmospheric deposition of pollutants and eutrophication, which deeply alter its chemistry, often on a global scale and, in some cases, at the degree significantly exceeding that in the historical and recent geological verification. In ocean systems the micro- and macronutrients, heavy metals, phosphor- and nitrogen-containing components exist in different forms depending on the concentrations of various other species, organic matter, the types of minerals, the pH etc. The major limitation to assessing more strictly the ES to oceans, such as pollutants (atmospheric greenhouse gas, heavy metals, nutrients as nitrates and phosphates) is the lack of theoretical approach which could predict the ocean resistance to multiple external stressors. In order to assess the abovementioned ES, the research has applied and developed the buffer theory approach and theoretical expressions of the formal chemical thermodynamics to ocean systems, as heterogeneous aqueous systems. The thermodynamic expressions of complex chemical equilibria, involving acid-base, complex formation and mineral ones have been deduced. This thermodynamic approach utilizes thermodynamic relationships coupled with original mass balance constraints, where the solid phases are explicitly expressed. The ocean sensitivity to different external stressors and changes in driving factors are considered in terms of derived buffering capacities or buffer factors for heterogeneous systems. Our investigations have proved that the heterogeneous aqueous systems, as ocean and seas are, manifest their buffer properties towards all their components, not only to pH, as it has been known so far, for example in respect to carbon dioxide, carbonates, phosphates, Ca2+, Mg2+, heavy metal ions etc. The derived expressions make possible to attribute changes in chemical ocean composition to different pollutants. These expressions are also useful for improving the current atmosphere-ocean-marine biogeochemistry models. The major research questions, to which the research responds, are: (i.) What kind of contamination is the most harmful for Future Ocean? (ii.) What are chemical heterogeneous processes of the heavy metal release from sediments and minerals and its impact to the ocean buffer action? (iii.) What will be the long-term response of the coastal ocean to the oceanic uptake of anthropogenic pollutants? (iv.) How will change the ocean resistance in terms of future chemical complex processes and buffer capacities and its response to external (anthropogenic) perturbations? The ocean buffer capacities towards its main components are recommended as parameters that should be included in determining the most important ocean factors which define the response of ocean environment at the technogenic loads increasing. The deduced thermodynamic expressions are valid for any combination of chemical composition, or any of the species contributing to the total concentration, as independent state variable.

Keywords: atmospheric greenhouse gas, chemical thermodynamics, external stressors, pollutants, seawater

Procedia PDF Downloads 113

Authors: Shamini Dhana, G. Subrahmanya VRK Rao

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The fashion industry is advancing towards a mindset of zero waste, personalization, creativity, and circularity. The trend of upcycling clothing and materials into personalized fashion is being demanded by the next generation. There is a need for a digital tool to accelerate the process towards mass customization. Dhana’s D/Sphere fashion technology platform uses digital tools to accelerate upcycling. In essence, advanced fashion garments can be designed and developed via reuse, repurposing, recreating activities, and using existing fabric and circulating materials. The D/Sphere platform has the following objectives: to provide (1) An opportunity to develop modern fashion using existing, finished materials and clothing without chemicals or water consumption; (2) The potential for an everyday customer and designer to use the medium of fashion for creative expression; (3) A solution to address the global textile waste generated by pre- and post-consumer fashion; (4) A solution to reduce carbon emissions, water, and energy consumption with the participation of all stakeholders; (5) An opportunity for brands, manufacturers, retailers to work towards zero-waste designs and as an alternative revenue stream. Other benefits of this alternative approach include sustainability metrics, trend prediction, facilitation of disassembly and remanufacture deep learning, and hyperheuristics for high accuracy. A design tool for mass personalization and customization utilizing existing circulating materials and deadstock, targeted to fashion stakeholders will lower environmental costs, increase revenues through up to date upcycled apparel, produce less textile waste during the cut-sew-stitch process, and provide a real design solution for the end customer to be part of circular fashion. The broader impact of this technology will result in a different mindset to circular fashion, increase the value of the product through multiple life cycles, find alternatives towards zero waste, and reduce the textile waste that ends up in landfills. This technology platform will be of interest to brands and companies that have the responsibility to reduce their environmental impact and contribution to climate change as it pertains to the fashion and apparel industry. Today, over 70% of the $3 trillion fashion and apparel industry ends up in landfills. To this extent, the industry needs such alternative techniques to both address global textile waste as well as provide an opportunity to include all stakeholders and drive circular fashion with new personalized products. This type of modern systems thinking is currently being explored around the world by the private sector, organizations, research institutions, and governments. This technological innovation using digital tools has the potential to revolutionize the way we look at communication, capabilities, and collaborative opportunities amongst stakeholders in the development of new personalized and customized products, as well as its positive impacts on society, our environment, and global climate change.

Keywords: circular fashion, deep learning, digital technology platform, personalization

Procedia PDF Downloads 34

Authors: Benjamin Glasner, Carlos Henriquez, Fernando Alfaro, Nicole Trefault, Santiago Andrade, Rodrigo De La Iglesia

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A central question in ecology refers to the relative importance that local-scale variables have over community composition, when compared with regional-scale variables. In coastal environments, strong seasonal abiotic influence dominates these systems, weakening the impact of other parameters like micronutrients. After the industrial revolution, micronutrients like trace metals have increased in ocean as pollutants, with strong effects upon biotic entities and biological processes in coastal regions. Coastal picoplankton communities had been characterized as a cyanobacterial dominated fraction, but in recent years the eukaryotic component of this size fraction has gained relevance due to their high influence in carbon cycle, although, diversity patterns and responses to disturbances are poorly understood. South Pacific upwelling coastal environments represent an excellent model to study seasonal changes due to a strong influence in the availability of macro- and micronutrients between seasons. In addition, some well constrained coastal bays of this region have been subjected to strong disturbances due to trace metal inputs. In this study, we aim to compare the influence of seasonality and trace metals concentrations, on the community structure of planktonic picoeukaryotes. To describe seasonal patterns in the study area, satellite data in a 6 years time series and in-situ measurements with a traditional oceanographic approach such as CTDO equipment were performed. In addition, trace metal concentrations were analyzed trough ICP-MS analysis, for the same region. For biological data collection, field campaigns were performed in 2011-2012 and the picoplankton community was described by flow cytometry and taxonomical characterization with next-generation sequencing of ribosomal genes. The relation between the abiotic and biotic components was finally determined by multivariate statistical analysis. Our data show strong seasonal fluctuations in abiotic parameters such as photosynthetic active radiation and superficial sea temperature, with a clear differentiation of seasons. However, trace metal analysis allows identifying strong differentiation within the study area, dividing it into two zones based on trace metals concentration. Biological data indicate that there are no major changes in diversity but a significant fluctuation in evenness and community structure. These changes are related mainly with regional parameters, like temperature, but by analyzing the metal influence in picoplankton community structure, we identify a differential response of some plankton taxa to metal pollution. We propose that some picoeukaryotic plankton groups respond differentially to metal inputs, by changing their nutritional status and/or requirements under disturbances as a derived outcome of toxic effects and tolerance.

Keywords: Picoeukaryotes, plankton communities, trace metals, seasonal patterns

Procedia PDF Downloads 142

Authors: Jelvin Tom Sebastian, Vinod Yeldho Baby

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In space, electronic devices are constantly attacked with radiation, which causes certain parts to fail or behave in unpredictable ways. To advance the thermal controllability for microsatellites, we need a new approach and thermal control system that is smaller than that on conventional satellites and that demand no electric power. Heat exchange inside the microsatellites is not that easy as conventional satellites due to the smaller size. With slight mass gain and no electric power, accommodating heat using phase change materials (PCMs) is a strong candidate for solving micro satellites' thermal difficulty. In other words, PCMs can absorb or produce heat in the form of latent heat, changing their phase and minimalizing the temperature fluctuation around the phase change point. The main restriction for these systems is thermal conductivity weakness of common PCMs. As PCM is having low thermal conductivity, it increases the melting and solidification time, which is not suitable for specific application like electronic cooling. In order to increase the thermal conductivity nanoparticles are introduced. Adding the nanoparticles in base PCM increases the thermal conductivity. Increase in weight concentration increases the thermal conductivity. This paper numerically investigates the thermal energy storage panel with nanoparticle enhanced phase change material. Silver nanostructure have increased the thermal properties of the base PCM, eicosane. Different weight concentration (1, 2, 3.5, 5, 6.5, 8, 10%) of silver enhanced phase change material was considered. Both steady state and transient analysis was performed to compare the characteristics of nanoparticle enhanced phase material at different heat loads. Results showed that in steady state, the temperature near the front panel reduced and temperature on NePCM panel increased as the weight concentration increased. With the increase in thermal conductivity more heat was absorbed into the NePCM panel. In transient analysis, it was found that the effect of nanoparticle concentration on maximum temperature of the system was reduced as the melting point of the material reduced with increase in weight concentration. But for the heat load of maximum 20W, the model with NePCM did not attain the melting point temperature. Therefore it showed that the model with NePCM is capable of holding more heat load. In order to study the heat load capacity double the load is given, maximum of 40W was given as first half of the cycle and the other is given constant OW. Higher temperature was obtained comparing the other heat load. The panel maintained a constant temperature for a long duration according to the NePCM melting point. In both the analysis, the uniformity of temperature of the TESP was shown. Using Ag-NePCM it allows maintaining a constant peak temperature near the melting point. Therefore, by altering the weight concentration of the Ag-NePCM it is possible to create an optimum operating temperature required for the effective working of the electronics components.

Keywords: carbon-fiber-reinforced polymer, micro/nano-satellite, nanoparticle phase change material, thermal energy storage

Procedia PDF Downloads 187

Authors: L. R. Valencia Pérez, A. Morita Alexander, Peña A. Juan Manuel, A. Lamadrid Álvarez

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This research shows the reflection and identification of explanatory variables and their relationships between different variables that are involved with educational technology, all of them encompassed in macro-concepts which are: cognitive inequality, economy, food and language; These will give the guideline to have a more detailed knowledge of educational systems, the communication and equipment, the physical space and the teachers; All of them interacting with each other give rise to what is called educational technology management. These elements contribute to have a very specific knowledge of the equipment of communications, networks and computer equipment, systems and content repositories. This is intended to establish the importance of knowing a global environment in the transfer of knowledge in poor countries, so that it does not diminish the capacity to be authentic and preserve their cultures, their languages or dialects, their hierarchies and real needs; In short, to respect the customs of different towns, villages or cities that are intended to be reached through the use of internationally agreed professional educational technologies. The methodology used in this research is the analytical - descriptive, which allows to explain each of the variables, which in our opinion must be taken into account, in order to achieve an optimal incorporation of the educational technology in a model that gives results in a medium term. The idea is that in an encompassing way the concepts will be integrated to others with greater coverage until reaching macro concepts that are of national coverage in the countries and that are elements of conciliation in the different federal and international reforms. At the center of the model is the educational technology which is directly related to the concepts that are contained in factors such as the educational system, communication and equipment, spaces and teachers, which are globally immersed in macro concepts Cognitive inequality, economics, food and language. One of the major contributions of this article is to leave this idea under an algorithm that allows to be as unbiased as possible when evaluating this indicator, since other indicators that are to be taken from international preference entities like the OECD in the area of education systems studied, so that they are not influenced by particular political or interest pressures. This work opens the way for a relationship between involved entities, both conceptual, procedural and human activity, to clearly identify the convergence of their impact on the problem of education and how the relationship can contribute to an improvement, but also shows possibilities of being able to reach a comprehensive education reform for all.

Keywords: relationships macro-concepts, cognitive inequality, economics, alimentation and language

Procedia PDF Downloads 177

Authors: Zeradam Yeshiwas, A. Krishnaia

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The aim of this study is to verify the resulting surface roughness of parts formed by the Single-Point Incremental Forming (SPIF) process for an ISO 3574 Drawing Quality Cold Rolled CR2 Steel. The chemical composition of drawing quality Cold Rolled CR2 steel is comprised of 0.12 percent of carbon, 0.5 percent of manganese, 0.035 percent of sulfur, 0.04 percent phosphorous, and the remaining percentage is iron with negligible impurities. The experiments were performed on a 3-axis vertical CNC milling machining center equipped with a tool setup comprising a fixture and forming tools specifically designed and fabricated for the process. The CNC milling machine was used to transfer the tool path code generated in Mastercam 2017 environment into three-dimensional motions by the linear incremental progress of the spindle. The blanks of Drawing Quality Cold Rolled CR2 steel sheets of 1 mm of thickness have been fixed along their periphery by a fixture and hardened high-speed steel (HSS) tools with a hemispherical tip of 8, 10 and 12mm of diameter were employed to fabricate sample parts. To investigate the surface roughness, hyperbolic-cone shape specimens were fabricated based on the chosen experimental design. The effect of process parameters on the surface roughness was studied using three important process parameters, i.e., tool diameter, feed rate, and step depth. In this study, the Taylor-Hobson Surtronic 3+ surface roughness tester profilometer was used to determine the surface roughness of the parts fabricated using the arithmetic mean deviation (Rₐ). In this instrument, a small tip is dragged across a surface while its deflection is recorded. Finally, the optimum process parameters and the main factor affecting surface roughness were found using the Taguchi design of the experiment and ANOVA. A Taguchi experiment design with three factors and three levels for each factor, the standard orthogonal array L9 (3³) was selected for the study using the array selection table. The lowest value of surface roughness is significant for surface roughness improvement. For this objective, the ‘‘smaller-the-better’’ equation was used for the calculation of the S/N ratio. The finishing roughness parameter Ra has been measured for the different process combinations. The arithmetic means deviation (Rₐ) was measured via the experimental design for each combination of the control factors by using Taguchi experimental design. Four roughness measurements were taken for a single component and the average roughness was taken to optimize the surface roughness. The lowest value of Rₐ is very important for surface roughness improvement. For this reason, the ‘‘smaller-the-better’’ Equation was used for the calculation of the S/N ratio. Analysis of the effect of each control factor on the surface roughness was performed with a ‘‘S/N response table’’. Optimum surface roughness was obtained at a feed rate of 1500 mm/min, with a tool radius of 12 mm, and with a step depth of 0.5 mm. The ANOVA result shows that step depth is an essential factor affecting surface roughness (91.1 %).

Keywords: incremental forming, SPIF, drawing quality steel, surface roughness, roughness behavior

Procedia PDF Downloads 40

Authors: Ali Pourkazemi

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The transient radar method (TRM) is one of the non-destructive methods that was introduced by authors a few years ago. The transient radar method can be classified as a wave-based non destructive testing (NDT) method that can be used in a wide frequency range. Nevertheless, it requires a narrow band, ranging from a few GHz to a few THz, depending on the application. As a time-of-flight and real-time method, TRM can measure the electromagnetic properties of the sample under test not only quickly and accurately, but also blindly. This means that it requires no prior knowledge of the sample under test. For multi-layer structures, TRM is not only able to detect changes related to any parameter within the multi-layer structure but can also measure the electromagnetic properties of each layer and its thickness individually. Although the temperature, humidity, and general environmental conditions may affect the sample under test, they do not affect the accuracy of the Blind TRM algorithm. In this paper, the electromagnetic properties as well as the thickness of the individual building insulation materials - as a single-layer structure - are measured experimentally. Finally, the correlation between the reflection coefficients and some other technical parameters such as sound insulation, thermal resistance, thermal conductivity, compressive strength, and density is investigated. The sample to be studied is 30 cm x 50 cm and the thickness of the samples varies from a few millimeters to 6 centimeters. This experiment is performed with both biostatic and differential hardware at 10 GHz. Since it is a narrow-band system, high-speed computation for analysis, free-space application, and real-time sensor, it has a wide range of potential applications, e.g., in the construction industry, rubber industry, piping industry, wind energy industry, automotive industry, biotechnology, food industry, pharmaceuticals, etc. Detection of metallic, plastic pipes wires, etc. through or behind the walls are specific applications for the construction industry.

Keywords: transient radar method, blind electromagnetic geometrical parameter extraction technique, ultrafast nondestructive multilayer dielectric structure characterization, electronic measurement systems, illumination, data acquisition performance, submillimeter depth resolution, time-dependent reflected electromagnetic signal blind analysis method, EM signal blind analysis method, time domain reflectometer, microwave, milimeter wave frequencies

Procedia PDF Downloads 45

Authors: C. Román, M. Guevara, P. Salas, D. Duclap, J. Houenou, C. Poupon, J. F. Mangin, P. Guevara

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Diffusion Magnetic Resonance Imaging (dMRI) allows the non-invasive study of human brain white matter. From diffusion data, it is possible to reconstruct fiber trajectories using tractography algorithms. Our previous work consists in an automatic method for the identification of short association bundles of the superficial white matter (SWM), based on a whole brain inter-subject hierarchical clustering applied to a HARDI database. The method finds representative clusters of similar fibers, belonging to a group of subjects, according to a distance measure between fibers, using a non-linear registration (DTI-TK). The algorithm performs an automatic labeling based on the anatomy, defined by a cortex mesh parcelated with FreeSurfer software. The clustering was applied to two independent groups of 37 subjects. The clusters resulting from both groups were compared using a restrictive threshold of mean distance between each pair of bundles from different groups, in order to keep reproducible connections. In the left hemisphere, 48 reproducible bundles were found, while 43 bundles where found in the right hemisphere. An inter-hemispheric bundle correspondence was then applied. The symmetric horizontal reflection of the right bundles was calculated, in order to obtain the position of them in the left hemisphere. Next, the intersection between similar bundles was calculated. The pairs of bundles with a fiber intersection percentage higher than 50% were considered similar. The similar bundles between both hemispheres were fused and symmetrized. We obtained 30 common bundles between hemispheres. An atlas was created with the resulting bundles and used to segment 78 new subjects from another HARDI database, using a distance threshold between 6-8 mm according to the bundle length. Finally, a laterality index was calculated based on the bundle volume. Seven bundles of the atlas presented right laterality (IP_SP_1i, LO_LO_1i, Op_Tr_0i, PoC_PoC_0i, PoC_PreC_2i, PreC_SM_0i, y RoMF_RoMF_0i) and one presented left laterality (IP_SP_2i), there is no tendency of lateralization according to the brain region. Many factors can affect the results, like tractography artifacts, subject registration, and bundle segmentation. Further studies are necessary in order to establish the influence of these factors and evaluate SWM laterality.

Keywords: dMRI, hierarchical clustering, lateralization index, tractography

Procedia PDF Downloads 303

Authors: Hosein I. Hosein, Ragab Azzam, Ahmed M. S. Menshawy, Sherin Rouby, Khaled Hendy, Ayman Mahrous, Hany Hussien

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Brucellosis is a highly contagious bacterial zoonotic disease of a worldwide spread and has different names; Infectious or enzootic abortion and Bang's disease in animals; and Mediterranean or Malta fever, Undulant Fever and Rock fever in humans. It is caused by the different species of genus Brucella which is a Gram-negative, aerobic, non-spore forming, facultative intracellular bacterium. Brucella affects a wide range of mammals including bovines, small ruminants, pigs, equines, rodents, marine mammals as well as human resulting in serious economic losses in animal populations. In human, Brucella causes a severe illness representing a great public health problem. The disease was reported in Egypt for the first time in 1939; since then the disease remained endemic at high levels among cattle, buffalo, sheep and goat and is still representing a public health hazard. The annual economic losses due to brucellosis were estimated to be about 60 million Egyptian pounds yearly, but actual estimates are still missing despite almost 30 years of implementation of the Egyptian control programme. Despite being the gold standard, bacterial isolation has been reported to show poor sensitivity for samples with low-level of Brucella and is impractical for regular screening of large populations. Thus, serological tests still remain the corner stone for routine diagnosis of brucellosis, especially in developing countries. In the present study, a total of 1533 cows (256 from Beni-Suef Governorate, 445 from Al-Fayoum Governorate and 832 from Damietta Governorate), were employed for estimation of relative sensitivity, relative specificity, positive predictive value and negative predictive value of buffered acidified plate antigen test (BPAT), rose bengal test (RBT) and complement fixation test (CFT). The overall seroprevalence of brucellosis revealed (19.63%). Relative sensitivity, relative specificity, positive predictive value and negative predictive value of BPAT,RBT and CFT were estimated as, (96.27 %, 96.76 %, 87.65 % and 99.10 %), (93.42 %, 96.27 %, 90.16 % and 98.35%) and (89.30 %, 98.60 %, 94.35 %and 97.24 %) respectively. BPAT showed the highest sensitivity among the three employed serological tests. RBT was less specific than BPAT. CFT showed the least sensitivity 89.30 % among the three employed serological tests but showed the highest specificity. Different tissues specimens of 22 seropositive cows (spleen, retropharyngeal udder, and supra-mammary lymph nodes) were subjected for bacteriological studies for isolation and identification of Brucella organisms. Brucella melitensis biovar 3 could be recovered from 12 (54.55%) cows. Bacteriological examinations failed to classify 10 cases (45.45%) and were culture negative. Bruce-ladder PCR was carried out for molecular identification of the 12 Brucella isolates at the species level. Three fragments of 587 bp, 1071 bp and 1682 bp sizes were amplified indicating Brucella melitensis. The results indicated the importance of using several procedures to overcome the problem of escaping of some infected animals from diagnosis.Bruce-ladder PCR is an important tool for diagnosis and epidemiologic studies, providing relevant information for identification of Brucella spp.

Keywords: brucellosis, relative sensitivity, relative specificity, Bruce-ladder, Egypt

Procedia PDF Downloads 320

Authors: Oksana G. Cherednichenko, Anastasia L. Pilyugina, Sergey N.Lukashenko, Elena G. Gubitskaya

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The estimation of accumulated radiation doses in people professionally exposed to ionizing radiation was performed using methods of biological (chromosomal aberrations frequency in lymphocytes) and physical (radionuclides analysis in urine, whole-body radiation meter, individual thermoluminescent dosimeters) dosimetry. A group of 84 "A" category employees after their work in the territory of former Semipalatinsk test site (Kazakhstan) was investigated. The dose rate in some funnels exceeds 40 μSv/h. After radionuclides determination in urine using radiochemical and WBC methods, it was shown that the total effective dose of personnel internal exposure did not exceed 0.2 mSv/year, while an acceptable dose limit for staff is 20 mSv/year. The range of external radiation doses measured with individual thermo-luminescent dosimeters was 0.3-1.406 µSv. The cytogenetic examination showed that chromosomal aberrations frequency in staff was 4.27±0.22%, which is significantly higher than at the people from non-polluting settlement Tausugur (0.87±0.1%) (р ≤ 0.01) and citizens of Almaty (1.6±0.12%) (р≤ 0.01). Chromosomal type aberrations accounted for 2.32±0.16%, 0.27±0.06% of which were dicentrics and centric rings. The cytogenetic analysis of different types group radiosensitivity among «professionals» (age, sex, ethnic group, epidemiological data) revealed no significant differences between the compared values. Using various techniques by frequency of dicentrics and centric rings, the average cumulative radiation dose for group was calculated, and that was 0.084-0.143 Gy. To perform comparative individual dosimetry using physical and biological methods of dose assessment, calibration curves (including own ones) and regression equations based on general frequency of chromosomal aberrations obtained after irradiation of blood samples by gamma-radiation with the dose rate of 0,1 Gy/min were used. Herewith, on the assumption of individual variation of chromosomal aberrations frequency (1–10%), the accumulated dose of radiation varied 0-0.3 Gy. The main problem in the interpretation of individual dosimetry results is reduced to different reaction of the objects to irradiation - radiosensitivity, which dictates the need of quantitative definition of this individual reaction and its consideration in the calculation of the received radiation dose. The entire examined contingent was assigned to a group based on the received dose and detected cytogenetic aberrations. Radiosensitive individuals, at the lowest received dose in a year, showed the highest frequency of chromosomal aberrations (5.72%). In opposite, radioresistant individuals showed the lowest frequency of chromosomal aberrations (2.8%). The cohort correlation according to the criterion of radio-sensitivity in our research was distributed as follows: radio-sensitive (26.2%) — medium radio-sensitivity (57.1%), radioresistant (16.7%). Herewith, the dispersion for radioresistant individuals is 2.3; for the group with medium radio-sensitivity — 3.3; and for radio-sensitive group — 9. These data indicate the highest variation of characteristic (reactions to radiation effect) in the group of radio-sensitive individuals. People with medium radio-sensitivity show significant long-term correlation (0.66; n=48, β ≥ 0.999) between the values of doses defined according to the results of cytogenetic analysis and dose of external radiation obtained with the help of thermoluminescent dosimeters. Mathematical models based on the type of violation of the radiation dose according to the professionals radiosensitivity level were offered.

Keywords: biodosimetry, chromosomal aberrations, ionizing radiation, radiosensitivity

Procedia PDF Downloads 155

Authors: Omer Burak Iskender, Keck Voon Ling, Vincent Dubanchet, Luca Simonini

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This paper presents Guidance and Control (G&C) strategy to approach and synchronize with potentially rotating targets. The proposed strategy generates and tracks a safe trajectory for space servicing missions, including tasks like approaching, inspecting, and capturing. The main objective of this paper is to validate the G&C laws using a Hardware-In-the-Loop (HIL) setup with realistic rendezvous and docking equipment. Throughout this work, the assumption of full relative state feedback is relaxed by onboard sensors that bring realistic errors and delays and, while the proposed closed loop approach demonstrates the robustness to the above mentioned challenge. Moreover, G&C blocks are unified via the Model Predictive Control (MPC) paradigm, and the coupling between translational motion and rotational motion is addressed via dual quaternion based kinematic description. In this work, G&C is formulated as a convex optimization problem where constraints such as thruster limits and the output constraints are explicitly handled. Furthermore, the Monte-Carlo method is used to evaluate the robustness of the proposed method to the initial condition errors, the uncertainty of the target's motion and attitude, and actuator errors. A capture scenario is tested with the robotic test bench that has onboard sensors which estimate the position and orientation of a drifting satellite through camera imagery. Finally, the approach is compared with currently used robust H-infinity controllers and guidance profile provided by the industrial partner. The HIL experiments demonstrate that the proposed strategy is a potential candidate for future space servicing missions because 1) the algorithm is real-time implementable as convex programming offers deterministic convergence properties and guarantee finite time solution, 2) critical physical and output constraints are respected, 3) robustness to sensor errors and uncertainties in the system is proven, 4) couples translational motion with rotational motion.

Keywords: dual quaternion, model predictive control, real-time experimental test, rendezvous and docking, spacecraft autonomy, space servicing

Procedia PDF Downloads 120

Authors: Nicolò Vaiana, Filip C. Filippou, Giorgio Serino

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In order to reduce numerical computations in the nonlinear dynamic analysis of seismically base-isolated structures, a Mixed Explicit-Implicit time integration Method (MEIM) has been proposed. Adopting the explicit conditionally stable central difference method to compute the nonlinear response of the base isolation system, and the implicit unconditionally stable Newmark’s constant average acceleration method to determine the superstructure linear response, the proposed MEIM, which is conditionally stable due to the use of the central difference method, allows to avoid the iterative procedure generally required by conventional monolithic solution approaches within each time step of the analysis. The main aim of this paper is to investigate the stability and computational efficiency of the MEIM when employed to perform the nonlinear time history analysis of base-isolated structures with sliding bearings. Indeed, in this case, the critical time step could become smaller than the one used to define accurately the earthquake excitation due to the very high initial stiffness values of such devices. The numerical results obtained from nonlinear dynamic analyses of a base-isolated structure with a friction pendulum bearing system, performed by using the proposed MEIM, are compared to those obtained adopting a conventional monolithic solution approach, i.e. the implicit unconditionally stable Newmark’s constant acceleration method employed in conjunction with the iterative pseudo-force procedure. According to the numerical results, in the presented numerical application, the MEIM does not have stability problems being the critical time step larger than the ground acceleration one despite of the high initial stiffness of the friction pendulum bearings. In addition, compared to the conventional monolithic solution approach, the proposed algorithm preserves its computational efficiency even when it is adopted to perform the nonlinear dynamic analysis using a smaller time step.

Keywords: base isolation, computational efficiency, mixed explicit-implicit method, partitioned solution approach, stability

Procedia PDF Downloads 255

Authors: Sagir M. Yusuf, Chris Baber

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In this paper, we describe how to achieve knowledge understanding and prediction (Situation Awareness (SA)) for multiple-agents conducting searching activity using Bayesian inferential reasoning and learning. Bayesian Belief Network was used to monitor agents' knowledge about their environment, and cases are recorded for the network training using expectation-maximisation or gradient descent algorithm. The well trained network will be used for decision making and environmental situation prediction. Forest fire searching by multiple UAVs was the use case. UAVs are tasked to explore a forest and find a fire for urgent actions by the fire wardens. The paper focused on two problems: (i) effective agents’ path planning strategy and (ii) knowledge understanding and prediction (SA). The path planning problem by inspiring animal mode of foraging using Lévy distribution augmented with Bayesian reasoning was fully described in this paper. Results proof that the Lévy flight strategy performs better than the previous fixed-pattern (e.g., parallel sweeps) approaches in terms of energy and time utilisation. We also introduced a waypoint assessment strategy called k-previous waypoints assessment. It improves the performance of the ordinary levy flight by saving agent’s resources and mission time through redundant search avoidance. The agents (UAVs) are to report their mission knowledge at the central server for interpretation and prediction purposes. Bayesian reasoning and learning were used for the SA and results proof effectiveness in different environments scenario in terms of prediction and effective knowledge representation. The prediction accuracy was measured using learning error rate, logarithm loss, and Brier score and the result proves that little agents mission that can be used for prediction within the same or different environment. Finally, we described a situation-based knowledge visualization and prediction technique for heterogeneous multi-UAV mission. While this paper proves linkage of Bayesian reasoning and learning with SA and effective searching strategy, future works is focusing on simplifying the architecture.

Keywords: Levy flight, distributed constraint optimization problem, multi-agent system, multi-robot coordination, autonomous system, swarm intelligence

Procedia PDF Downloads 117

Authors: Pranee Suecharoen, Ratchadaporn Soontornpas, Jaturat Kanpittaya

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Background: Contrast media has an important role for disease diagnosis through detection of pathologies. Contrast media can, however, cause adverse reactions after administration of its agents. Although non-ionic contrast media are commonly used, the incidence of adverse events is relatively low. The most common reactions found (10.5%) were mild and manageable and/or preventable. Pharmacists can play an important role in evaluating adverse reactions, including awareness of the specific preparation and the type of adverse reaction. As most common types of adverse reactions are idiosyncratic or pseudo-allergic reactions, common standards need to be established to prevent and control adverse reactions promptly and effectively. Objective: To measure the effect of using tools for symptom evaluation in order to reduce the severity, or prevent the occurrence, of adverse reactions from contrast media. Methods: Retrospective review descriptive research with data collected on adverse reactions assessment and Naranjo’s algorithm between June 2015 and May 2016. Results: 158 patients (10.53%) had adverse reactions. Of the 1,500 participants with an adverse event evaluation, 137 (9.13%) had a mild adverse reaction, including hives, nausea, vomiting, dizziness, and headache. These types of symptoms can be treated (i.e., with antihistamines, anti-emetics) and the patient recovers completely within one day. The group with moderate adverse reactions, numbering 18 cases (1.2%), had hypertension or hypotension, and shortness of breath. Severe adverse reactions numbered 3 cases (0.2%) and included swelling of the larynx, cardiac arrest, and loss of consciousness, requiring immediate treatment. No other complications under close medical supervision were recorded (i.e., corticosteroids use, epinephrine, dopamine, atropine, or life-saving devices). Using the guideline, therapies are divided into general and specific and are performed according to the severity, risk factors and ingestion of contrast media agents. Patients who have high-risk factors were screened and treated (i.e., prophylactic premedication) for prevention of severe adverse reactions, especially those with renal failure. Thus, awareness for the need for prescreening of different risk factors is necessary for early recognition and prompt treatment. Conclusion: Studying adverse reactions can be used to develop a model for reducing the level of severity and setting a guideline for a standardized, multidisciplinary approach to adverse reactions.

Keywords: role of pharmacist, management of adverse reactions, guideline for contrast media, non-ionic contrast media

Procedia PDF Downloads 280

Authors: Frea Van Steenweghen, Lander Hollevoet, Johan A. Martens

Abstract:

Compared to other hydrogen (H₂) carriers, ammonia (NH₃) is one of the most promising carriers as it contains 17.6 wt% hydrogen. It is easily liquefied at ≈ 9–10 bar pressure at ambient temperature. More importantly, NH₃ is a carbon-free hydrogen carrier with no CO₂ emission at final decomposition. Ammonia has a well-defined regulatory framework and a good track record regarding safety concerns. Furthermore, the industry already has an existing transport infrastructure consisting of pipelines, tank trucks and shipping technology, as ammonia has been manufactured and distributed around the world for over a century. While NH₃ synthesis and transportation technological solutions are at hand, a missing link in the hydrogen delivery scheme from ammonia is an energy-lean and efficient technology for cracking ammonia into H₂ and N₂. The most explored option for ammonia decomposition is thermo-catalytic cracking which is, by itself, the most energy-efficient approach compared to other technologies, such as plasma and electrolysis, as it is the most energy-lean and robust option. The decomposition reaction is favoured only at high temperatures (> 300°C) and low pressures (1 bar) as the thermocatalytic ammonia cracking process is faced with thermodynamic limitations. At 350°C, the thermodynamic equilibrium at 1 bar pressure limits the conversion to 99%. Gaining additional conversion up to e.g. 99.9% necessitates heating to ca. 530°C. However, reaching thermodynamic equilibrium is infeasible as a sufficient driving force is needed, requiring even higher temperatures. Limiting the conversion below the equilibrium composition is a more economical option. Thermocatalytic ammonia cracking is documented in scientific literature. Among the investigated metal catalysts (Ru, Co, Ni, Fe, …), ruthenium is known to be most active for ammonia decomposition with an onset of cracking activity around 350°C. For establishing > 99% conversion reaction, temperatures close to 600°C are required. Such high temperatures are likely to reduce the round-trip efficiency but also the catalyst lifetime because of the sintering of the supported metal phase. In this research, the first focus was on catalyst bed design, avoiding diffusion limitation. Experiments in our packed bed tubular reactor set-up showed that extragranular diffusion limitations occur at low concentrations of NH₃ when reaching high conversion, a phenomenon often overlooked in experimental work. A second focus was thermocatalyst development for ammonia cracking, avoiding the use of noble metals. To this aim, candidate metals and mixtures were deposited on a range of supports. Sintering resistance at high temperatures and the basicity of the support were found to be crucial catalyst properties. The catalytic activity was promoted by adding alkaline and alkaline earth metals. A third focus was studying the optimum process configuration by process simulations. A trade-off between conversion and favorable operational conditions (i.e. low pressure and high temperature) may lead to different process configurations, each with its own pros and cons. For example, high-pressure cracking would eliminate the need for post-compression but is detrimental for the thermodynamic equilibrium, leading to an optimum in cracking pressure in terms of energy cost.

Keywords: ammonia cracking, catalyst research, kinetics, process simulation, thermodynamic equilibrium

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Authors: Kavitha Madhu, Karthik K. Srinivasan, R. Sivanandan

Abstract:

Indian traffic can be considered as mixed and heterogeneous due to the presence of various types of vehicles that operate with weak lane discipline. Consequently, vehicles can position themselves anywhere in the traffic stream depending on availability of gaps. The choice of lateral positioning is an important component in representing and characterizing mixed traffic. The field data provides evidence that the trajectory of vehicles in Indian urban roads have significantly varying longitudinal and lateral components. Further, the notion of headway which is widely used for homogeneous traffic simulation is not well defined in conditions lacking lane discipline. From field data it is clear that following is not strict as in homogeneous and lane disciplined conditions and neighbouring vehicles ahead of a given vehicle and those adjacent to it could also influence the subject vehicles choice of position, speed and acceleration. Given these empirical features, the suitability of using headway distributions to characterize mixed traffic in Indian cities is questionable, and needs to be modified appropriately. To address these issues, this paper attempts to analyze the time gap distribution between consecutive vehicles (in a time-sense) crossing a section of roadway. More specifically, to characterize the complex interactions noted above, the influence of composition, manoeuvre types, and lateral placement characteristics on time gap distribution is quantified in this paper. The developed model is used for evaluating various performance measures such as link speed, midblock delay and intersection delay which further helps to characterise the vehicular fuel consumption and emission on urban roads of India. Identifying and analyzing exact interactions between various classes of vehicles in the traffic stream is essential for increasing the accuracy and realism of microscopic traffic flow modelling. In this regard, this study aims to develop and analyze time gap distribution models and quantify it by lead lag pair, manoeuvre type and lateral position characteristics in heterogeneous non-lane based traffic. Once the modelling scheme is developed, this can be used for estimating the vehicle kilometres travelled for the entire traffic system which helps to determine the vehicular fuel consumption and emission. The approach to this objective involves: data collection, statistical modelling and parameter estimation, simulation using calibrated time-gap distribution and its validation, empirical analysis of simulation result and associated traffic flow parameters, and application to analyze illustrative traffic policies. In particular, video graphic methods are used for data extraction from urban mid-block sections in Chennai, where the data comprises of vehicle type, vehicle position (both longitudinal and lateral), speed and time gap. Statistical tests are carried out to compare the simulated data with the actual data and the model performance is evaluated. The effect of integration of above mentioned factors in vehicle generation is studied by comparing the performance measures like density, speed, flow, capacity, area occupancy etc under various traffic conditions and policies. The implications of the quantified distributions and simulation model for estimating the PCU (Passenger Car Units), capacity and level of service of the system are also discussed.

Keywords: lateral movement, mixed traffic condition, simulation modeling, vehicle following models

Procedia PDF Downloads 320