Search results for: Large Wind Turbine
4950 Airon Project: IoT-Based Agriculture System for the Optimization of Irrigation Water Consumption
Authors: África Vicario, Fernando J. Álvarez, Felipe Parralejo, Fernando Aranda
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The irrigation systems of traditional agriculture, such as gravity-fed irrigation, produce a great waste of water because, generally, there is no control over the amount of water supplied in relation to the water needed. The AIRON Project tries to solve this problem by implementing an IoT-based system to sensor the irrigation plots so that the state of the crops and the amount of water used for irrigation can be known remotely. The IoT system consists of a sensor network that measures the humidity of the soil, the weather conditions (temperature, relative humidity, wind and solar radiation) and the irrigation water flow. The communication between this network and a central gateway is conducted by means of long-range wireless communication that depends on the characteristics of the irrigation plot. The main objective of the AIRON project is to deploy an IoT sensor network in two different plots of the irrigation community of Aranjuez in the Spanish region of Madrid. The first plot is 2 km away from the central gateway, so LoRa has been used as the base communication technology. The problem with this plot is the absence of mains electric power, so devices with energy-saving modes have had to be used to maximize the external batteries' use time. An ESP32 SOC board with a LoRa module is employed in this case to gather data from the sensor network and send them to a gateway consisting of a Raspberry Pi with a LoRa hat. The second plot is located 18 km away from the gateway, a range that hampers the use of LoRa technology. In order to establish reliable communication in this case, the long-term evolution (LTE) standard is used, which makes it possible to reach much greater distances by using the cellular network. As mains electric power is available in this plot, a Raspberry Pi has been used instead of the ESP32 board to collect sensor data. All data received from the two plots are stored on a proprietary server located at the irrigation management company's headquarters. The analysis of these data by means of machine learning algorithms that are currently under development should allow a short-term prediction of the irrigation water demand that would significantly reduce the waste of this increasingly valuable natural resource. The major finding of this work is the real possibility of deploying a remote sensing system for irrigated plots by using Commercial-Off-The-Shelf (COTS) devices, easily scalable and adaptable to design requirements such as the distance to the control center or the availability of mains electrical power at the site.Keywords: internet of things, irrigation water control, LoRa, LTE, smart farming
Procedia PDF Downloads 854949 Inclusion Body Refolding at High Concentration for Large-Scale Applications
Authors: J. Gabrielczyk, J. Kluitmann, T. Dammeyer, H. J. Jördening
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High-level expression of proteins in bacteria often causes production of insoluble protein aggregates, called inclusion bodies (IB). They contain mainly one type of protein and offer an easy and efficient way to get purified protein. On the other hand, proteins in IB are normally devoid of function and therefore need a special treatment to become active. Most refolding techniques aim at diluting the solubilizing chaotropic agents. Unfortunately, optimal refolding conditions have to be found empirically for every protein. For large-scale applications, a simple refolding process with high yields and high final enzyme concentrations is still missing. The constructed plasmid pASK-IBA63b containing the sequence of fructosyltransferase (FTF, EC 2.4.1.162) from Bacillus subtilis NCIMB 11871 was transformed into E. coli BL21 (DE3) Rosetta. The bacterium was cultivated in a fed-batch bioreactor. The produced FTF was obtained mainly as IB. For refolding experiments, five different amounts of IBs were solubilized in urea buffer with protein concentration of 0.2-8.5 g/L. Solubilizates were refolded with batch or continuous dialysis. The refolding yield was determined by measuring the protein concentration of the clear supernatant before and after the dialysis. Particle size was measured by dynamic light scattering. We tested the solubilization properties of fructosyltransferase IBs. The particle size measurements revealed that the solubilization of the aggregates is achieved at urea concentration of 5M or higher and confirmed by absorption spectroscopy. All results confirm previous investigations that refolding yields are dependent upon initial protein concentration. In batch dialysis, the yields dropped from 67% to 12% and 72% to 19% for continuous dialysis, in relation to initial concentrations from 0.2 to 8.5 g/L. Often used additives such as sucrose and glycerol had no effect on refolding yields. Buffer screening indicated a significant increase in activity but also temperature stability of FTF with citrate/phosphate buffer. By adding citrate to the dialysis buffer, we were able to increase the refolding yields to 82-47% in batch and 90-74% in the continuous process. Further experiments showed that in general, higher ionic strength of buffers had major impact on refolding yields; doubling the buffer concentration increased the yields up to threefold. Finally, we achieved corresponding high refolding yields by reducing the chamber volume by 75% and the amount of buffer needed. The refolded enzyme had an optimal activity of 12.5±0.3 x104 units/g. However, detailed experiments with native FTF revealed a reaggregation of the molecules and loss in specific activity depending on the enzyme concentration and particle size. For that reason, we actually focus on developing a process of simultaneous enzyme refolding and immobilization. The results of this study show a new approach in finding optimal refolding conditions for inclusion bodies at high concentrations. Straightforward buffer screening and increase of the ionic strength can optimize the refolding yield of the target protein by 400%. Gentle removal of chaotrope with continuous dialysis increases the yields by an additional 65%, independent of the refolding buffer applied. In general time is the crucial parameter for successful refolding of solubilized proteins.Keywords: dialysis, inclusion body, refolding, solubilization
Procedia PDF Downloads 2944948 The Effect of Awareness-Raising on Household Water Consumption
Authors: R. Morbidelli, C. Saltalippi, A. Flammini, J. Dari
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This work analyses what effect systematic awareness-raising of the population on domestic water consumption produces. In a period where the availability of water is continually decreasing due to reduced rainfall, it is of paramount importance to raise awareness among the population. We conducted an experiment on a large sample of homes in urban areas of Central Italy. In the first phase, lasting three weeks, normal per capita, water consumption was quantified. Subsequently, instructions were given on how to save water during various uses in the household (showers, cleaning hands, use of water in toilets, watering small green areas, use of water in the kitchen, ...), and small visual messages were posted at water dispensers to remind users to behave properly. Finally, household consumption was assessed again for a further three weeks. This experiment made it possible to quantify the effect of the awareness-raising action on the reduction of water consumption without the use of any structural action (replacement of dispensers, improvement of the water system, ...).Keywords: water saving, urban areas, awareness-raising, climate change
Procedia PDF Downloads 1054947 The Investigation of Psychological Motives of Creative Abilities in the Omani Musical Intelligence
Authors: Mohammed Talib Alkiyumi
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The Sultanate of Oman is characterized by a huge musical heritage that remains mostly preserved. 142 different traditional musical genres and styles (funun) have been registered in the Sultanate. This large number is a unique phenomenon that is worthy of attention and study. These genres and styles are different from others in their origins, rhythms, melodies, poetry, dance movements, etc. Certainly, Oman is exposed to other cultures and there is a variety of ethnicities in the Sultanate; however, this musical diversity is mostly an Omani product. This paper investigates the psychological motives behind Omani musical creativity. This qualitative study is based on relevant documents, as well as an analysis of Omani performance in those genres through documentary films and direct observations. Musical genres are performed in social events such as weddings and celebrations; however, research has shown psychological motives that motivated Omani people to create these various genres, such as provocation of enthusiasm, meditation, religious motivations, poetic competition, and emotional motivation. For each motive, musical genres have been presented.Keywords: traditional musical, creativity, musical intelligence, Sultanate of Oman
Procedia PDF Downloads 1034946 Simulation of the Performance of the Reforming of Methane in a Primary Reformer
Authors: A. Alkattib, M. Boumaza
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Steam reforming is industrially important as it is incorporated in several major chemical processes including the production of ammonia, methanol, hydrogen and ox alcohols. Due to the strongly endothermic nature of the process, a large amount of heat is supplied by fuel burning (commonly natural gas) in the furnace chamber. Reaction conversions, tube catalyst life, energy consumption and CO2 emission represent the principal factors affecting the performance of this unit and are directly influenced by the high operating temperatures and pressures. This study presents a simulation of the performance of the reforming of methane in a primary reformer, through a developed empirical relation which enables to investigate the effects of operating parameters such as the pressure, temperature, steam to carbon ratio on the production of hydrogen, as well as the fraction of non-converted methane. It appears from this analysis that the exit temperature Te, the operating pressure as well the steam to carbon ratio has an important effect on the reforming of methane.Keywords: reforming, methane, performance, hydrogen, parameters
Procedia PDF Downloads 2264945 Finite Element Analysis of the Ordinary Reinforced Concrete Bridge Piers
Authors: Nabin Raj Chaulagain
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Most of the concrete bridges in Nepal constructed during 90's and before are made up of low strength ordinary concrete which might be one of the reasons for damage in higher magnitude earthquake. Those bridges were designed by the outdated bridge codes which might not account the large seismic loads. This research investigates the seismic vulnerability of the existing single column ordinary concrete bridge pier by finite element modeling, using the software Seismostruct. The existing bridge pier capacity has been assessed using nonlinear pushover analysis and performance is compared after retrofitting those pier models with CFRP. Furthermore, the seismic evaluation was made by conducting cyclic loading test at different drift percentage. The performance analysis of bridge pier by nonlinear pushover analysis is further validated by energy dissipation phenomenon measured from the hysteric loop for each model of ordinary concrete piers.Keywords: finite element modeling, ordinary concrete bridge pier, performance analysis, retrofitting
Procedia PDF Downloads 3204944 Learning Predictive Models for Efficient Energy Management of Exhibition Hall
Authors: Jeongmin Kim, Eunju Lee, Kwang Ryel Ryu
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This paper addresses the problem of predictive control for energy management of large-scaled exhibition halls, where a lot of energy is consumed to maintain internal atmosphere under certain required conditions. Predictive control achieves better energy efficiency by optimizing the operation of air-conditioning facilities with not only the current but also some future status taken into account. In this paper, we propose to use predictive models learned from past sensor data of hall environment, for use in optimizing the operating plan for the air-conditioning facilities by simulating future environmental change. We have implemented an emulator of an exhibition hall by using EnergyPlus, a widely used building energy emulation tool, to collect data for learning environment-change models. Experimental results show that the learned models predict future change highly accurately on a short-term basis.Keywords: predictive control, energy management, machine learning, optimization
Procedia PDF Downloads 2744943 4D Monitoring of Subsurface Conditions in Concrete Infrastructure Prior to Failure Using Ground Penetrating Radar
Authors: Lee Tasker, Ali Karrech, Jeffrey Shragge, Matthew Josh
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Monitoring for the deterioration of concrete infrastructure is an important assessment tool for an engineer and difficulties can be experienced with monitoring for deterioration within an infrastructure. If a failure crack, or fluid seepage through such a crack, is observed from the surface often the source location of the deterioration is not known. Geophysical methods are used to assist engineers with assessing the subsurface conditions of materials. Techniques such as Ground Penetrating Radar (GPR) provide information on the location of buried infrastructure such as pipes and conduits, positions of reinforcements within concrete blocks, and regions of voids/cavities behind tunnel lining. This experiment underlines the application of GPR as an infrastructure-monitoring tool to highlight and monitor regions of possible deterioration within a concrete test wall due to an increase in the generation of fractures; in particular, during a time period of applied load to a concrete wall up to and including structural failure. A three-point load was applied to a concrete test wall of dimensions 1700 x 600 x 300 mm³ in increments of 10 kN, until the wall structurally failed at 107.6 kN. At each increment of applied load, the load was kept constant and the wall was scanned using GPR along profile lines across the wall surface. The measured radar amplitude responses of the GPR profiles, at each applied load interval, were reconstructed into depth-slice grids and presented at fixed depth-slice intervals. The corresponding depth-slices were subtracted from each data set to compare the radar amplitude response between datasets and monitor for changes in the radar amplitude response. At lower values of applied load (i.e., 0-60 kN), few changes were observed in the difference of radar amplitude responses between data sets. At higher values of applied load (i.e., 100 kN), closer to structural failure, larger differences in radar amplitude response between data sets were highlighted in the GPR data; up to 300% increase in radar amplitude response at some locations between the 0 kN and 100 kN radar datasets. Distinct regions were observed in the 100 kN difference dataset (i.e., 100 kN-0 kN) close to the location of the final failure crack. The key regions observed were a conical feature located between approximately 3.0-12.0 cm depth from surface and a vertical linear feature located approximately 12.1-21.0 cm depth from surface. These key regions have been interpreted as locations exhibiting an increased change in pore-space due to increased mechanical loading, or locations displaying an increase in volume of micro-cracks, or locations showing the development of a larger macro-crack. The experiment showed that GPR is a useful geophysical monitoring tool to assist engineers with highlighting and monitoring regions of large changes of radar amplitude response that may be associated with locations of significant internal structural change (e.g. crack development). GPR is a non-destructive technique that is fast to deploy in a production setting. GPR can assist with reducing risk and costs in future infrastructure maintenance programs by highlighting and monitoring locations within the structure exhibiting large changes in radar amplitude over calendar-time.Keywords: 4D GPR, engineering geophysics, ground penetrating radar, infrastructure monitoring
Procedia PDF Downloads 1794942 Model and Algorithm for Dynamic Wireless Electric Vehicle Charging Network Design
Authors: Trung Hieu Tran, Jesse O'Hanley, Russell Fowler
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When in-wheel wireless charging technology for electric vehicles becomes mature, a need for such integrated charging stations network development is essential. In this paper, we thus investigate the optimisation problem of in-wheel wireless electric vehicle charging network design. A mixed-integer linear programming model is formulated to solve into optimality the problem. In addition, a meta-heuristic algorithm is proposed for efficiently solving large-sized instances within a reasonable computation time. A parallel computing strategy is integrated into the algorithm to speed up its computation time. Experimental results carried out on the benchmark instances show that our model and algorithm can find the optimal solutions and their potential for practical applications.Keywords: electric vehicle, wireless charging station, mathematical programming, meta-heuristic algorithm, parallel computing
Procedia PDF Downloads 794941 Material Characterization and Numerical Simulation of a Rubber Bumper
Authors: Tamás Mankovits, Dávid Huri, Imre Kállai, Imre Kocsis, Tamás Szabó
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Non-linear FEM calculations are indispensable when important technical information like operating performance of a rubber component is desired. Rubber bumpers built into air-spring structures may undergo large deformations under load, which in itself shows non-linear behavior. The changing contact range between the parts and the incompressibility of the rubber increases this non-linear behavior further. The material characterization of an elastomeric component is also a demanding engineering task. In this paper, a comprehensive investigation is introduced including laboratory measurements, mesh density analysis and complex finite element simulations to obtain the load-displacement curve of the chosen rubber bumper. Contact and friction effects are also taken into consideration. The aim of this research is to elaborate an FEM model which is accurate and competitive for a future shape optimization task.Keywords: rubber bumper, finite element analysis, compression test, Mooney-Rivlin material model
Procedia PDF Downloads 5094940 Computational Cell Segmentation in Immunohistochemically Image of Meningioma Tumor Using Fuzzy C-Means and Adaptive Vector Directional Filter
Authors: Vahid Anari, Leila Shahmohammadi
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Diagnosing and interpreting manually from a large cohort dataset of immunohistochemically stained tissue of tumors using an optical microscope involves subjectivity and also is tedious for pathologist specialists. Moreover, digital pathology today represents more of an evolution than a revolution in pathology. In this paper, we develop and test an unsupervised algorithm that can automatically enhance the IHC image of a meningioma tumor and classify cells into positive (proliferative) and negative (normal) cells. A dataset including 150 images is used to test the scheme. In addition, a new adaptive color image enhancement method is proposed based on a vector directional filter (VDF) and statistical properties of filtering the window. Since the cells are distinguishable by the human eye, the accuracy and stability of the algorithm are quantitatively compared through application to a wide variety of real images.Keywords: digital pathology, cell segmentation, immunohistochemically, noise reduction
Procedia PDF Downloads 674939 A Study on the New Weapon Requirements Analytics Using Simulations and Big Data
Authors: Won Il Jung, Gene Lee, Luis Rabelo
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Since many weapon systems are getting more complex and diverse, various problems occur in terms of the acquisition cost, time, and performance limitation. As a matter of fact, the experiment execution in real world is costly, dangerous, and time-consuming to obtain Required Operational Characteristics (ROC) for a new weapon acquisition although enhancing the fidelity of experiment results. Also, until presently most of the research contained a large amount of assumptions so therefore a bias is present in the experiment results. At this moment, the new methodology is proposed to solve these problems without a variety of assumptions. ROC of the new weapon system is developed through the new methodology, which is a way to analyze big data generated by simulating various scenarios based on virtual and constructive models which are involving 6 Degrees of Freedom (6DoF). The new methodology enables us to identify unbiased ROC on new weapons by reducing assumptions and provide support in terms of the optimal weapon systems acquisition.Keywords: big data, required operational characteristics (ROC), virtual and constructive models, weapon acquisition
Procedia PDF Downloads 2894938 Effective Removal of Tetrodotoxin with Fiber Mat Containing Activated Charcoal
Authors: Min Sik Kim, Hwa Sung Shin
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From 2013, small eel farms, which are located in Han River Estuary, South Korea suffer damage because of unknown massive perish. In the middle of discussion that the cause of perish could be environmental changes or waste water, a large amount of unknown nemertean was discovered during that time. Some nemerteans are known releasing neurotoxin substance. In this study, we isolated intestinal bacteria using selective media and conducted 16s rDNA microbial identification by gene alignment. As a result, there was a type of bacteria producing TTX, blocks sodium-channel inducing organism’s death. TTX production from the bacteria was confirmed by ELISA and liquid chromatography coupled with mass spectrometer. Additionally, the activated-charcoal which has an ability to absorb small molecules like toxin was applied to fibrous mesh to prevent ingestion of aquatic organisms and increase applicable area. The viability of zebrafish in the water with TTX and charcoal fiber mat were not decreased meaning it could be used for solving the perishing problem in fish farm.Keywords: nemertean, TTX, fiber mat, activated charcoal, zebrafish
Procedia PDF Downloads 2084937 Culvert Blockage Evaluation Using Australian Rainfall And Runoff 2019
Authors: Rob Leslie, Taher Karimian
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The blockage of cross drainage structures is a risk that needs to be understood and managed or lessened through the design. A blockage is a random event, influenced by site-specific factors, which needs to be quantified for design. Under and overestimation of blockage can have major impacts on flood risk and cost associated with drainage structures. The importance of this matter is heightened for those projects located within sensitive lands. It is a particularly complex problem for large linear infrastructure projects (e.g., rail corridors) located within floodplains where blockage factors can influence flooding upstream and downstream of the infrastructure. The selection of the appropriate blockage factors for hydraulic modeling has been subject to extensive research by hydraulic engineers. This paper has been prepared to review the current Australian Rainfall and Runoff 2019 (ARR 2019) methodology for blockage assessment by applying this method to a transport corridor brownfield upgrade case study in New South Wales. The results of applying the method are also validated against asset data and maintenance records. ARR 2019 – Book 6, Chapter 6 includes advice and an approach for estimating the blockage of bridges and culverts. This paper concentrates specifically on the blockage of cross drainage structures. The method has been developed to estimate the blockage level for culverts affected by sediment or debris due to flooding. The objective of the approach is to evaluate a numerical blockage factor that can be utilized in a hydraulic assessment of cross drainage structures. The project included an assessment of over 200 cross drainage structures. In order to estimate a blockage factor for use in the hydraulic model, a process has been advanced that considers the qualitative factors (e.g., Debris type, debris availability) and site-specific hydraulic factors that influence blockage. A site rating associated with the debris potential (i.e., availability, transportability, mobility) at each crossing was completed using the method outlined in ARR 2019 guidelines. The hydraulic results inputs (i.e., flow velocity, flow depth) and qualitative factors at each crossing were developed into an advanced spreadsheet where the design blockage level for cross drainage structures were determined based on the condition relating Inlet Clear Width and L10 (average length of the longest 10% of the debris reaching the site) and the Adjusted Debris Potential. Asset data, including site photos and maintenance records, were then reviewed and compared with the blockage assessment to check the validity of the results. The results of this assessment demonstrate that the estimated blockage factors at each crossing location using ARR 2019 guidelines are well-validated with the asset data. The primary finding of the study is that the ARR 2019 methodology is a suitable approach for culvert blockage assessment that has been validated against a case study spanning a large geographical area and multiple sub-catchments. The study also found that the methodology can be effectively coded within a spreadsheet or similar analytical tool to automate its application.Keywords: ARR 2019, blockage, culverts, methodology
Procedia PDF Downloads 3614936 X̄ and S Control Charts based on Weighted Standard Deviation Method
Authors: Derya Karagöz
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A Shewhart chart based on normality assumption is not appropriate for skewed distributions since its Type-I error rate is inflated. This study presents X̄ and S control charts for monitoring the process variability for skewed distributions. We propose Weighted Standard Deviation (WSD) X̄ and S control charts. Standard deviation estimator is applied to monitor the process variability for estimating the process standard deviation, in the case of the W SD X̄ and S control charts as this estimator is simple and easy to compute. Unlike the Shewhart control chart, the proposed charts provide asymmetric limits in accordance with the direction and degree of skewness to construct the upper and lower limits. The performances of the proposed charts are compared with other heuristic charts for skewed distributions by using Simulation study. The Simulation studies show that the proposed control charts have good properties for skewed distributions and large sample sizes.Keywords: weighted standard deviation, MAD, skewed distributions, S control charts
Procedia PDF Downloads 3994935 Land Use Change Modeling Using Cellular Automata, Case Study: Karawang City, West Java Province, Indonesia
Authors: Bagus Indrawan Hardi
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Cellular Automata are widely used in land use modeling, it has been proven powerful to simulate land use change for small scale in many large cities in the world. In this paper, we try to implement CA for land use modeling in unique city in Indonesia, Karawang. Instead the complex numerical implementation, CA are simple, and it is accurate and also highly dependable on the on the rules (rule based). The most important to do in CA is how we form and calculate the neighborhood effect. The neighborhood effect represents the environment and relationship situation between the occupied cell and others. We adopted 196 cells of circular neighborhood with 8 cells of radius. For the results, CA works well in this study, we exhibit several analyzed and proceed of zoomed part in Karawang region. The rule set can handle the complexity in land use modeling. However, we cannot strictly believe of the result, many non-technical parameters, such as politics, natural disaster activities, etc. may change the results dramatically.Keywords: cellular automata (CA), land use change, spatial dynamics, urban sprawl
Procedia PDF Downloads 2444934 Detection of COVID-19 Cases From X-Ray Images Using Capsule-Based Network
Authors: Donya Ashtiani Haghighi, Amirali Baniasadi
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Coronavirus (COVID-19) disease has spread abruptly all over the world since the end of 2019. Computed tomography (CT) scans and X-ray images are used to detect this disease. Different Deep Neural Network (DNN)-based diagnosis solutions have been developed, mainly based on Convolutional Neural Networks (CNNs), to accelerate the identification of COVID-19 cases. However, CNNs lose important information in intermediate layers and require large datasets. In this paper, Capsule Network (CapsNet) is used. Capsule Network performs better than CNNs for small datasets. Accuracy of 0.9885, f1-score of 0.9883, precision of 0.9859, recall of 0.9908, and Area Under the Curve (AUC) of 0.9948 are achieved on the Capsule-based framework with hyperparameter tuning. Moreover, different dropout rates are investigated to decrease overfitting. Accordingly, a dropout rate of 0.1 shows the best results. Finally, we remove one convolution layer and decrease the number of trainable parameters to 146,752, which is a promising result.Keywords: capsule network, dropout, hyperparameter tuning, classification
Procedia PDF Downloads 784933 Mechanical Properties of CNT Reinforced Composite Using Berkovich Nanoindentation Analysis
Authors: Khondaker Sakil Ahmed, Ang Kok Keng, Shah Md Muniruzzaman
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Spherical and Berkovich indentation tests are carried out numerically using finite element method for uniformly dispersed Carbon Nanotube (CNT) in the polymer matrix in which perfectly bonded CNT/matrix interface is considered. The Large strain elasto-plastic analysis is performed to investigate the actual scenario of nanoindentation test. This study investigates how the addition of CNT in polymer matrix influences the mechanical properties like hardness, elastic modulus of the nanocomposite. Since the wall thickness to radius ratio (t/r) is significantly small for SWCNT there is a huge possibility of lateral buckling which is a function of the location of indentation tip as well as the mechanical properties of matrix. Separate finite element models are constructed to compare the result with Berkovich indentation. This study also investigates the buckling behavior of different nanotube in a different polymer matrix.Keywords: carbon nanotube, elasto-plastic, finite element model, nano-indentation
Procedia PDF Downloads 3894932 Facile Synthesis of Potassium Vanadium Fluorophosphate: Semiconducting Properties and Its Photocatalytic Performance for Dye Degradation under Visible Light
Authors: S. Tartaya, R. Bagtache, A. M. Djaballah, M. Trari
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Due to the increase in the trade of colored products and their applications in various fields such as cosmetic, food, textile, pharmaceutical industries, etc. Dyes constitute a large part of the contaminants in wastewater and cause serious damage in the environment and the aquatic system. Photocatalytic systems are highly efficient processes for treating wastewater in the presence of semiconductor photocatalysts. In this field, we report our contribution by synthesizing a potassium vanadium fluorophosphate compound KVPO4F (which is abbreviated KVPOF) by a simplified hydrothermal method at 180°C for 5 days. The as synthesized product has been characterized physically and photoelectrochemically. The indirect optical transition of 1.88 eV, determined from the diffuse reflectance, was assigned to the charge transfer. Moreover, the curve (C-2–E) of the KVPOF displayed n-type character of the semiconductor. Even more, interestingly, the photocatalytic performance was evaluated through the photo-degradation of cationic dye Methyl Violet (MV). An abatement of 61% was obtained after 6 h of irradiation under visible light.Keywords: KVPO4F, photocatalysis, semiconductor, wastewater, environment
Procedia PDF Downloads 784931 The Effect of Sumatra Fault Earthquakes on West Malaysia
Authors: Noushin Naraghi Araghi, M. Nawawi, Syed Mustafizur Rahman
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This paper presents the effect of Sumatra fault earthquakes on west Malaysia by calculating the peak horizontal ground acceleration (PGA). PGA is calculated by a probabilistic seismic hazard assessment (PSHA). A uniform catalog of earthquakes for the interest region has been provided. We used empirical relations to convert all magnitudes to Moment Magnitude. After eliminating foreshocks and aftershocks in order to achieve more reliable results, the completeness of the catalog and uncertainty of magnitudes have been estimated and seismicity parameters were calculated. Our seismic source model considers the Sumatran strike slip fault that is known historically to generate large earthquakes. The calculations were done using the logic tree method and four attenuation relationships and slip rates for different part of this fault. Seismic hazard assessment carried out for 48 grid points. Eventually, two seismic hazard maps based PGA for 5% and 10% probability of exceedance in 50 year are presented.Keywords: Sumatra fault, west Malaysia, PGA, seismic parameters
Procedia PDF Downloads 4044930 Preliminary Seismic Hazard Mapping of Papua New Guinea
Authors: Hadi Ghasemi, Mark Leonard, Spiliopoulos Spiro, Phil Cummins, Mathew Moihoi, Felix Taranu, Eric Buri, Chris Mckee
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In this study the level of seismic hazard in terms of Peak Ground Acceleration (PGA) was calculated for return period of 475 years, using modeled seismic sources and assigned ground-motion equations. The calculations were performed for bedrock site conditions (Vs30=760 m/s). From the results it is evident that the seismic hazard reaches its maximum level (i.e. PGA≈1g for 475 yr return period) at the Huon Peninsula and southern New Britain regions. Disaggregation analysis revealed that moderate to large earthquakes occurring along the New Britain Trench mainly control the level of hazard at these locations. The open-source computer program OpenQuake developed by Global Earthquake Model foundation was used for the seismic hazard computations. It should be emphasized that the presented results are still preliminary and should not be interpreted as our final assessment of seismic hazard in PNG.Keywords: probabilistic seismic hazard assessment, Papua New Guinea, building code, OpenQuake
Procedia PDF Downloads 5564929 Mapping New Technologies for Sustainability along the Fashion Supply Chain
Authors: Hilde Heim
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The textile industry is known for its swift adoption of innovations in fashion technology (Fash-Tech). The industry is also known for its harmful effects on the environment. Opportunely, Fash-Tech is expected to facilitate the turn towards more sustainable practice. However, although several technologies have the potential for advancing sustainable practice, many industry players, whether large or small, are confused and misinformed about Fash-Tech adoption, application, and impact. Through a visual poster presentation, this project aims to map global fashion innovations along the supply chain from fibre production to waste management, thus providing a clearer picture of numbers, scale, and adoption. While the project aims to identify Fash-Tech effectiveness in reaching sustainability goals, it also identifies areas of congestion as well as insufficiency in the accessibility of Fash-Tech. This project intends to help inform future decisions in business, investment, and policy for the advancement of sustainable practice.Keywords: fashion technology, sustainability, supply chain, enterprise management
Procedia PDF Downloads 2414928 Performance Analysis of Proprietary and Non-Proprietary Tools for Regression Testing Using Genetic Algorithm
Authors: K. Hema Shankari, R. Thirumalaiselvi, N. V. Balasubramanian
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The present paper addresses to the research in the area of regression testing with emphasis on automated tools as well as prioritization of test cases. The uniqueness of regression testing and its cyclic nature is pointed out. The difference in approach between industry, with business model as basis, and academia, with focus on data mining, is highlighted. Test Metrics are discussed as a prelude to our formula for prioritization; a case study is further discussed to illustrate this methodology. An industrial case study is also described in the paper, where the number of test cases is so large that they have to be grouped as Test Suites. In such situations, a genetic algorithm proposed by us can be used to reconfigure these Test Suites in each cycle of regression testing. The comparison is made between a proprietary tool and an open source tool using the above-mentioned metrics. Our approach is clarified through several tables.Keywords: APFD metric, genetic algorithm, regression testing, RFT tool, test case prioritization, selenium tool
Procedia PDF Downloads 4364927 Centrifuge Modeling of Monopiles Subjected to Lateral Monotonic Loading
Authors: H. R. Khodaei, M. Moradi, A. H. Tajik
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The type of foundation commonly used today for berthing dolphins is a set of tubular steel piles with large diameters, which are known as monopiles. The design of these monopiles is based on the theories related with laterally loaded piles. One of the most common methods to analyze and design the piles subjected to lateral loads is the p-y curves. In the present study, centrifuge tests are conducted in order to obtain the p-y curves. Series of tests were designed in order to investigate the scaling laws in the centrifuge for monotonic loading. Also, two important parameters, the embedded depth L of the pile in the soil and free length e of the pile, as well as their ratios were studied via five experimental tests. Finally, the p-y curves of API are presented to be compared with the curves obtained from the tests so that the differences could be demonstrated. The results show that the p-y curves proposed by API highly overestimate the lateral load bearing capacity. It suggests that these curves need correction and modification for each site as the soil conditions change.Keywords: centrifuge modeling, monopile, lateral loading, p-y curves
Procedia PDF Downloads 2474926 The Spatial Equity Assessment of Community-Based Elderly Care Facilities in Old Neighborhood of Chongqing
Authors: Jiayue Zhao, Hongjuan Wu, Guiwen Liu
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Old neighborhoods with a large elderly population depend on community-based elderly care facilities (community-based ECFs) for aging-in-place. Yet, due to scarce and scattered land, the facilities face inequitable distribution. This research uses spatial equity theory to measure the spatial equity of community-based ECFs in old neighborhoods. Field surveys gather granular data and methods, including coverage rate, Gini coefficient, Lorenz curve, and G2SFCA. The findings showed that coverage is substantial but does not indicate supply is a match to demand, nor does it imply superior accessibility. The key contributions are that structuring spatial equity framework considering elderly residents’ travel behavior. This study is dedicated to the international literature on spatial equity from the perspective of travel behavior and could provide valuable suggestions for the urban planning of old neighborhoods.Keywords: community-based ECFs, elderly residents’ travel behavior, old neighborhoods, spatial equity
Procedia PDF Downloads 594925 Managing the Water Projects and Controlling Its Boundary Disturbances Which Affect the Water Supply
Authors: Sead A. Bakheet, Salah M. Elkoum, Asharaf A. Almaghribi
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Disturbance defined as activity that malfunction, intrusion, or interruption. We have to look around for the source of the disturbance affecting the inputs and outputs of engineering projects, take the necessary actions to control them. In this paper we will present and discuss a production system consisting of three elements, inputs, the production process and outputs. The production process which we chose is the production of large diameter pre-stressed concrete cylinder pipes (out puts), in reality, the outputs are the starting points of the operation (laying the concrete pipes for transporting drinkable water). The main objective also to address the controlling methods of the natural resources and raw materials (basic inputs), study the disturbances affecting them as well as the output quality. The importance of making the right decision, which effect the final product quality will be summarized. Finally, we will address the proposals regarding the managing of secure water supply to the customers.Keywords: disturbances, management, inputs, outputs, decision
Procedia PDF Downloads 624924 Improving Detection of Illegitimate Scores and Assessment in Most Advantageous Tenders
Authors: Hao-Hsi Tseng, Hsin-Yun Lee
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The Most Advantageous Tender (MAT) has been criticized for its susceptibility to dictatorial situations and for its processing of same score, same rank issues. This study applies the four criteria from Arrow's Impossibility Theorem to construct a mechanism for revealing illegitimate scores in scoring methods. While commonly be used to improve on problems resulting from extreme scores, ranking methods hide significant defects, adversely affecting selection fairness. To address these shortcomings, this study relies mainly on the overall evaluated score method, using standardized scores plus normal cumulative distribution function conversion to calculate the evaluation of vender preference. This allows for free score evaluations, which reduces the influence of dictatorial behavior and avoiding same score, same rank issues. Large-scale simulations confirm that this method outperforms currently used methods using the Impossibility Theorem.Keywords: Arrow’s impossibility theorem, cumulative normal distribution function, most advantageous tender, scoring method
Procedia PDF Downloads 4644923 Clinical Validation of an Automated Natural Language Processing Algorithm for Finding COVID-19 Symptoms and Complications in Patient Notes
Authors: Karolina Wieczorek, Sophie Wiliams
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Introduction: Patient data is often collected in Electronic Health Record Systems (EHR) for purposes such as providing care as well as reporting data. This information can be re-used to validate data models in clinical trials or in epidemiological studies. Manual validation of automated tools is vital to pick up errors in processing and to provide confidence in the output. Mentioning a disease in a discharge letter does not necessarily mean that a patient suffers from this disease. Many of them discuss a diagnostic process, different tests, or discuss whether a patient has a certain disease. The COVID-19 dataset in this study used natural language processing (NLP), an automated algorithm which extracts information related to COVID-19 symptoms, complications, and medications prescribed within the hospital. Free-text patient clinical patient notes are rich sources of information which contain patient data not captured in a structured form, hence the use of named entity recognition (NER) to capture additional information. Methods: Patient data (discharge summary letters) were exported and screened by an algorithm to pick up relevant terms related to COVID-19. Manual validation of automated tools is vital to pick up errors in processing and to provide confidence in the output. A list of 124 Systematized Nomenclature of Medicine (SNOMED) Clinical Terms has been provided in Excel with corresponding IDs. Two independent medical student researchers were provided with a dictionary of SNOMED list of terms to refer to when screening the notes. They worked on two separate datasets called "A” and "B”, respectively. Notes were screened to check if the correct term had been picked-up by the algorithm to ensure that negated terms were not picked up. Results: Its implementation in the hospital began on March 31, 2020, and the first EHR-derived extract was generated for use in an audit study on June 04, 2020. The dataset has contributed to large, priority clinical trials (including International Severe Acute Respiratory and Emerging Infection Consortium (ISARIC) by bulk upload to REDcap research databases) and local research and audit studies. Successful sharing of EHR-extracted datasets requires communicating the provenance and quality, including completeness and accuracy of this data. The results of the validation of the algorithm were the following: precision (0.907), recall (0.416), and F-score test (0.570). Percentage enhancement with NLP extracted terms compared to regular data extraction alone was low (0.3%) for relatively well-documented data such as previous medical history but higher (16.6%, 29.53%, 30.3%, 45.1%) for complications, presenting illness, chronic procedures, acute procedures respectively. Conclusions: This automated NLP algorithm is shown to be useful in facilitating patient data analysis and has the potential to be used in more large-scale clinical trials to assess potential study exclusion criteria for participants in the development of vaccines.Keywords: automated, algorithm, NLP, COVID-19
Procedia PDF Downloads 1024922 An Inverse Optimal Control Approach for the Nonlinear System Design Using ANN
Authors: M. P. Nanda Kumar, K. Dheeraj
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The design of a feedback controller, so as to minimize a given performance criterion, for a general non-linear dynamical system is difficult; if not impossible. But for a large class of non-linear dynamical systems, the open loop control that minimizes a performance criterion can be obtained using calculus of variations and Pontryagin’s minimum principle. In this paper, the open loop optimal trajectories, that minimizes a given performance measure, is used to train the neural network whose inputs are state variables of non-linear dynamical systems and the open loop optimal control as the desired output. This trained neural network is used as the feedback controller. In other words, attempts are made here to solve the “inverse optimal control problem” by using the state and control trajectories that are optimal in an open loop sense.Keywords: inverse optimal control, radial basis function, neural network, controller design
Procedia PDF Downloads 5534921 Design and Implementation of Security Middleware for Data Warehouse Signature, Framework
Authors: Mayada Al Meghari
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Recently, grid middlewares have provided large integrated use of network resources as the shared data and the CPU to become a virtual supercomputer. In this work, we present the design and implementation of the middleware for Data Warehouse Signature, DWS Framework. The aim of using the middleware in our DWS framework is to achieve the high performance by the parallel computing. This middleware is developed on Alchemi.Net framework to increase the security among the network nodes through the authentication and group-key distribution model. This model achieves the key security and prevents any intermediate attacks in the middleware. This paper presents the flow process structures of the middleware design. In addition, the paper ensures the implementation of security for DWS middleware enhancement with the authentication and group-key distribution model. Finally, from the analysis of other middleware approaches, the developed middleware of DWS framework is the optimal solution of a complete covering of security issues.Keywords: middleware, parallel computing, data warehouse, security, group-key, high performance
Procedia PDF Downloads 119