Search results for: AIAD model

Authors: Mojtaba Sadeghi, Farshid Baniassadi, Hamed Kashani

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One of the challenging issues faced by seismic retrofitting consultants and employers is quick decision-making on the demolition or retrofitting of a structure at the current time or in the future. For this reason, the existing models proposed by researchers have only covered one of the aspects of cost, execution method, and structural vulnerability. Given the effect of each factor on the final decision, it is crucial to devise a new comprehensive model capable of simultaneously covering all the factors. This study attempted to provide an integrated framework that can be utilized to select the most appropriate earthquake risk mitigation solution for buildings. This framework can overcome the limitations of current models by taking into account several factors such as cost, execution method, risk-taking and structural failure. In the newly proposed model, the database and essential information about retrofitting projects are developed based on the historical data on a retrofit project. In the next phase, an analysis is conducted in order to assess the vulnerability of the building under study. Then, artificial neural networks technique is employed to calculate the cost of retrofitting. While calculating the current price of the structure, an economic analysis is conducted to compare demolition versus retrofitting costs. At the next stage, the optimal method is identified. Finally, the implementation of the framework was demonstrated by collecting data concerning 155 previous projects.

Keywords: decision making, demolition, construction management, seismic retrofit

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Authors: Harshada Vaidya-Kannur, Dattatraya Naik

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Propolis, one of the beehive products also referred as bee-glue is sticky dark coloured complex mixture of compounds. The volatile oil can be isolated from the propolis by hydrodistillation. The mark that is left behind after the removal of volatile oil is referred as the de-oiled propolis. Antioxidant as well as anti-inflammatory properties of total ethanolic extract of de-oiled propolis (TEEDP) was investigated. Another lot of deoiled propolis was successively exacted with hexane, ethyl acetate and ethanol. Activities of these fractions were also determined. Antioxidant activity was determined by studying ABTS, DPPH and NO radical scavenging. Determination of anti-inflammatory activity was carried out by topical TPA induced mouse ear oedema model. It is noteworthy that ethyl acetate fraction of deoiled propolis (EAFDP) exhibited 49.45 % TEAC activity at the concentration 0.2 mg/ml which is equivalent to the activity of trolox at the concentration 0.2 mg/ml. Its DPPH scavenging activity (72.56%) was closely comparable to that of trolox (75%). However its NO scavenging activity was comparatively low. From IC50 values it could be concluded that the efficiency of scavenging ABTS radicals by the de-oiled propolis was more pronounced as compared to scavenging of other radicals. Studies by TPA induced mouse ear inflammation model indicated that the de-oiled propolis of Indian origin had significant topical anti-inflammatory activity. The EAFDP was found to be the most active fraction for this activity also. The purification of EAFP yielded six pure crystalline compounds. These compounds were identified by their physical data and spectral data.

Keywords: anti-inflammatory activity, anti-oxidant activity, column chromatography, de-oiled propolis

Procedia PDF Downloads 288

Authors: Mclee Kerolle

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For more than 50 years, the state of Hawaii has had the beginnings of a burgeoning commercial aerospace presence statewide. While Hawaii provides the aerospace industry with unique assets concerning geographic location, lack of range safety issues and other factors critical to aerospace development, Hawaii’s strategy and commitment for aerospace have been unclear. For this reason, this paper presents a comparative analysis of Hawaii’s space sector with two of the world’s leading space sectors, Colorado and the Netherlands, in order to provide a strategic plan that establishes a firm position going forward to support Hawaii’s aerospace development statewide. This plan will include financial and other economic incentives legislatively supported by the State to help grow and diversify Hawaii’s aerospace sector. The first part of this paper will examine the business model adopted by the Colorado Space Coalition (CSC), a group of industry stakeholders working to make Colorado a center of excellence for aerospace, as blueprint for growth in Hawaii’s space sector. The second section of this paper will examine the business model adopted by the Netherlands Space Business Incubation Centre (NSBIC), a European Space Agency (ESA) affiliated program that offers business support for entrepreneurs to turn space-connected business ideas into commercial companies. This will serve as blueprint to incentivize space businesses to launch and develop in Hawaii. The third section of this paper will analyze the current policies both CSC, and NSBIC implores to promote industry expansion and legislative advocacy. The final section takes the findings from both space sectors and applies their most adaptable features to a Hawaii specific space business model that takes into consideration the unique advantage and disadvantages found in developing Hawaii’s space sector. The findings of this analysis will show that the development of a strategic plan based on a comparative analysis that creates high technology jobs and new pathways for a trained workforce in the space sector, as well as elicit state support and direction, will achieve the goal of establishing Hawaii as a center of space excellence. This analysis will also serve as a signal to the federal, private sector and international community that Hawaii is indeed serious about developing its’ aerospace industry. Ultimately this analysis and subsequent aerospace development plan will serve as a blueprint for the benefit of all space-faring nations seeking to develop their space sectors.

Keywords: Colorado, Hawaii, Netherlands, space policy

Procedia PDF Downloads 170

Authors: V. Pizarro-Carmona, S. Castano-Solis, M. Cortés-Carmona, J. Fraile-Ardanuy, D. Jimenez-Bermejo

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The purpose of this article is to optimize the Equivalent Electric Circuit Model (EECM) of different orders to obtain greater precision in the modeling of Li-ion battery packs. Optimization includes considering circuits based on 1RC, 2RC and 3RC networks, with a dependent voltage source and a series resistor. The parameters are obtained experimentally using tests in the time domain and in the frequency domain. Due to the high non-linearity of the behavior of the battery pack, Genetic Algorithm (GA) was used to solve and optimize the parameters of each EECM considered (1RC, 2RC and 3RC). The objective of the estimation is to minimize the mean square error between the measured impedance in the real battery pack and those generated by the simulation of different proposed circuit models. The results have been verified by comparing the Nyquist graphs of the estimation of the complex impedance of the pack. As a result of the optimization, the 2RC and 3RC circuit alternatives are considered as viable to represent the battery behavior. These battery pack models are experimentally validated using a hardware-in-the-loop (HIL) simulation platform that reproduces the well-known New York City cycle (NYCC) and Federal Test Procedure (FTP) driving cycles for electric vehicles. The results show that using GA optimization allows obtaining EECs with 2RC or 3RC networks, with high precision to represent the dynamic behavior of a battery pack in vehicular applications.

Keywords: Li-ion battery packs modeling optimized, EECM, GA, electric vehicle applications

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Authors: Binoy Chandra Sarma, S. K. Deb

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Over 85% of industrial dryers are of the convective type with hot air or direct flue gases as the drying medium. Over 99% of the applications involve removal of water. In this study, the performance of a solar air heater with the recovery of the absorbed heat by the metallic concentrator sheet itself besides the normal heat accumulated by the receiver at the focus of the concentrator for generating drying air by convection at a low to medium temperature range is discussed. The system performance through thermal analysis & the performance of a model achieving the required temperature range is also investigate in this study. Over 85% of industrial dryers are of the convective type with hot air or direct flue gases as the drying medium. Over 99% of the applications involve removal of water. In this study, the performance of a solar air heater with the recovery of the absorbed heat by the metallic concentrator sheet itself besides the normal heat accumulated by the receiver at the focus of the concentrator for generating drying air by convection at a low to medium temperature range is discussed. The system performance through thermal analysis & the performance of a model achieving the required temperature range is also investigate in this study.

Keywords: dryer, polygeneration, moisture, equilibrium, humidity

Procedia PDF Downloads 396

Authors: Krzysztof J. Czarnocki, E. Czarnocka, K. Szaniawska

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Main goal of the research project is Scaffold Use Risk Assessment Model (SURAM) formulation, developed for the assessment of risk levels as a various construction process stages with various work trades. Finally, in 2016, the project received financing by the National Center for Research and development according to PBS3/A2/19/2015–Research Grant. The presented data, calculations and analyzes discussed in this paper were created as a result of the completion on the first and second phase of the PBS3/A2/19/2015 project. Method: One of the arms of the research project is the assessment of worker visual concentration on the sight zones as well as risky visual point inadequate observation. In this part of research, the mobile eye-tracker was used to monitor the worker observation zones. SMI Eye Tracking Glasses is a tool, which allows us to analyze in real time and place where our eyesight is concentrated on and consequently build the map of worker's eyesight concentration during a shift. While the project is still running, currently 64 construction sites have been examined, and more than 600 workers took part in the experiment including monitoring of typical parameters of the work regimen, workload, microclimate, sound vibration, etc. Full equipment can also be useful in more advanced analyses. Because of that technology we have verified not only main focus of workers eyes during work on or next to scaffolding, but we have also examined which changes in the surrounding environment during their shift influenced their concentration. In the result of this study it has been proven that only up to 45.75% of the shift time, workers’ eye concentration was on one of three work-related areas. Workers seem to be distracted by noisy vehicles or people nearby. In opposite to our initial assumptions and other authors’ findings, we observed that the reflective parts of the scaffoldings were not more recognized by workers in their direct workplaces. We have noticed that the red curbs were the only well recognized part on a very few scaffoldings. Surprisingly on numbers of samples, we have not recognized any significant number of concentrations on those curbs. Conclusion: We have found the eye-tracking method useful for the construction of the SURAM model in the risk perception and worker’s behavior sub-modules. We also have found that the initial worker's stress and work visual conditions seem to be more predictive for assessment of the risky developing situation or an accident than other parameters relating to a work environment.

Keywords: accident assessment model, eye tracking, occupational safety, scaffolding

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Authors: Elisa Coraggio, Dawei Han, Weiru Liu, Theo Tryfonas

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Water is one of the most important resources for human society. The world is currently undergoing a wave of urban growth, and pollution problems are of a great impact. Monitoring water quality is a key task for the future of the environment and human species. In recent times, researchers, using Smart Cities technologies are trying to mitigate the problems generated by the population growth in urban areas. The availability of huge amounts of data collected by a pervasive urban IoT can increase the transparency of decision making. Several services have already been implemented in Smart Cities, but more and more services will be involved in the future. Water quality monitoring can successfully be implemented in the urban IoT. The combination of water quality sensors, cloud computing, smart city infrastructure, and IoT technology can lead to a bright future for environmental monitoring. In the past decades, lots of effort has been put on monitoring and predicting water quality using traditional approaches based on manual collection and laboratory-based analysis, which are slow and laborious. The present study proposes a methodology for implementing a water quality prediction model using artificial intelligence techniques and comparing the results obtained with different algorithms. Furthermore, a 3D numerical model will be created using the software D-Water Quality, and simulation results will be used as a training dataset for the artificial intelligence algorithm. This study derives the methodology and demonstrates its implementation based on information and data collected at the floating harbour in the city of Bristol (UK). The city of Bristol is blessed with the Bristol-Is-Open infrastructure that includes Wi-Fi network and virtual machines. It was also named the UK ’s smartest city in 2017.In recent times, researchers, using Smart Cities technologies are trying to mitigate the problems generated by the population growth in urban areas. The availability of huge amounts of data collected by a pervasive urban IoT can increase the transparency of decision making. Several services have already been implemented in Smart Cities, but more and more services will be involved in the future. Water quality monitoring can successfully be implemented in the urban IoT. The combination of water quality sensors, cloud computing, smart city infrastructure, and IoT technology can lead to a bright future for the environment monitoring. In the past decades, lots of effort has been put on monitoring and predicting water quality using traditional approaches based on manual collection and laboratory-based analysis, which are slow and laborious. The present study proposes a new methodology for implementing a water quality prediction model using artificial intelligence techniques and comparing the results obtained with different algorithms. Furthermore, a 3D numerical model will be created using the software D-Water Quality, and simulation results will be used as a training dataset for the Artificial Intelligence algorithm. This study derives the methodology and demonstrate its implementation based on information and data collected at the floating harbour in the city of Bristol (UK). The city of Bristol is blessed with the Bristol-Is-Open infrastructure that includes Wi-Fi network and virtual machines. It was also named the UK ’s smartest city in 2017.

Keywords: artificial intelligence, hydroinformatics, numerical modelling, smart cities, water quality

Procedia PDF Downloads 188

Authors: Maryam Hajibaba, Mohsen Soltanpour, Mehrnoosh Abbasian, S. Abbas Haghshenas

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This paper aims to evaluate the main role of mangroves forests on the unique hydrodynamic characteristics of the Khuran Strait (KS) in the Persian Gulf. Investigation of hydrodynamic conditions of KS is vital to predict and estimate sedimentation and erosion all over the protected areas north of Qeshm Island. KS (or Tang-e-Khuran) is located between Qeshm Island and the Iranian mother land and has a minimum width of approximately two kilometers. Hydrodynamics of the strait is dominated by strong tidal currents of up to 2 m/s. The bathymetry of the area is dynamic and complicated as 1) strong currents do exist in the area which lead to seemingly sand dune movements in the middle and southern parts of the strait, and 2) existence a vast area with mangrove coverage next to the narrowest part of the strait. This is why ordinary modeling schemes with normal mesh resolutions are not capable for high accuracy estimations of current fields in the KS. A comprehensive set of measurements were carried out with several components, to investigate the hydrodynamics and morpho-dynamics of the study area, including 1) vertical current profiling at six stations, 2) directional wave measurements at four stations, 3) water level measurements at six stations, 4) wind measurements at one station, and 5) sediment grab sampling at 100 locations. Additionally, a set of periodic hydrographic surveys was included in the program. The numerical simulation was carried out by using Delft3D – Flow Module. Model calibration was done by comparing water levels and depth averaged velocity of currents against available observational data. The results clearly indicate that observed data and simulations only fit together if a realistic perspective of the mangrove area is well captured by the model bathymetry data. Generating unstructured grid by using RGFGRID and QUICKIN, the flow model was driven with water level time-series at open boundaries. Adopting the available field data, the key role of mangrove area on the hydrodynamics of the study area can be studied. The results show that including the accurate geometry of the mangrove area and consideration of its sponge-like behavior are the key aspects through which a realistic current field can be simulated in the KS.

Keywords: Khuran Strait, Persian Gulf, tide, current, Delft3D

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Authors: Alireza Ansariyar, Safieh Laaly

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Over the last decades, the vehicle industry has shown increased interest in integrating autonomous, connected, and electrical technologies in vehicle design with the primary hope of improving mobility and road safety while reducing transportation’s environmental impact. Using the State of Maryland (M.D.) in the United States as a pilot study, this research investigates CAVs’ fuel consumption and air pollutants (C.O., PM, and NOx) and utilizes meaningful linear regression models to predict CAV’s environmental effects. Maryland transportation network was simulated in VISUM software, and data on a set of variables were collected through a comprehensive survey. The number of pollutants and fuel consumption were obtained for the time interval 2010 to 2021 from the macro simulation. Eventually, four linear regression models were proposed to predict the amount of C.O., NOx, PM pollutants, and fuel consumption in the future. The results highlighted that CAVs’ pollutants and fuel consumption have a significant correlation with the income, age, and race of the CAV customers. Furthermore, the reliability of four statistical models was compared with the reliability of macro simulation model outputs in the year 2030. The error of three pollutants and fuel consumption was obtained at less than 9% by statistical models in SPSS. This study is expected to assist researchers and policymakers with planning decisions to reduce CAV environmental impacts in M.D.

Keywords: connected and autonomous vehicles, statistical model, environmental effects, pollutants and fuel consumption, VISUM, linear regression models

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Authors: Mohamed Bendoukha, Mustapha Mosbah

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The Radiographic apparent assumed that the asymptomatic adjacent segment disease ASD is common after lumbar fusion, but this does not correlate with the functional outcomes while compensatory increased motion and stresses at the adjacent level of fusion is well-known to be associated to ASD. Newly developed, the hybrid stabilization are allocated to substituted for mostly the superior level of the fusion in an attempt to reduce the number of fusion levels and likelihood of degeneration process at the adjacent levels during the fusion with pedicle screws. Nevertheless, its biomechanical efficiencies still remain unknown and complications associated with failure of constructs such screw loosening and toggling should be elucidated In the current study, a finite element (FE) study was performed using a validated L2/S1 model subjected to a moment of 7.5 Nm and follower load of 400 N to assess the biomedical behavior of hybrid constructs based on dynamic topping off, semi rigid fusion. The residual range of motion (ROM), stress distribution at the fused and adjacent levels, stress distribution at the disc and the cage-endplate interface with respect to changes of bone quality were investigated. The hybrid instrumentation was associated with a reduction in compressive stresses compared to the fusion construct in the adjacent-level disc and showed high substantial axial force in the implant while fusion instrumentation increased the motion for both flexion and extension.

Keywords: intervertebral disc, lumbar spine, degenerative nuclesion, L4-L5, range of motion finite element model, hyperelasticy

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Authors: Onur Kaya, Ilknur Tukenmez

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In this study, we consider vehicle routing problems on networks with alternative direct links between nodes, and we analyze a multi-objective problem considering the financial, environmental and social objectives in this context. In real life, there might exist several alternative direct roads between two nodes, and these roads might have differences in terms of their lengths and durations. For example, a road might be shorter than another but might require longer time due to traffic and speed limits. Similarly, some toll roads might be shorter or faster but require additional payment, leading to higher costs. We consider such alternative links in our problem and develop a mixed integer linear programming model that determines which alternative link to use between two nodes, in addition to determining the optimal routes for different vehicles, depending on the model objectives and constraints. We consider the minimum cost routing as the financial objective for the company, minimizing the CO2 emissions and gas usage as the environmental objectives, and optimizing the driver working conditions/working hours, and minimizing the risks of accidents as the social objectives. With these objective functions, we aim to determine which routes, and which alternative links should be used in addition to the speed choices on each link. We discuss the results of the developed vehicle routing models and compare their results depending on the system parameters.

Keywords: vehicle routing, alternative links between nodes, mixed integer linear programming, triple bottom line accounting

Procedia PDF Downloads 407

Authors: Mojtaba Zabihi, Stephen Munro, Jonathan Little, Ri Li, Joshua Brinkerhoff, Sina Kheirkhah

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Occupational Safety and Health Administration (OSHA) identified dental workers at the highest risk of contracting COVID-19. This is because aerosol-generating procedures (AGP) during dental practices generate aerosols ( < 5µm) and droplets. These particles travel at varying speeds, in varying directions, and for varying durations. If these particles bear infectious viruses, their spreading causes airborne transmission of the virus in the dental room, exposing dentists, hygienists, dental assistants, and even other dental clinic clients to the infection risk. Computational fluid dynamics (CFD) simulation of two-phase flows based on a discrete phase model (DPM) is carried out to study the spreading of aerosol and droplets in a dental room. The simulation includes momentum, heat, and mass transfers between the particles and the airflow. Two simulations are conducted and compared. One simulation focuses on the effects of room ventilation in winter and summer on the particles' travel. The other simulation focuses on the control of aerosol and droplets' spreading. A suction collector is added near the source of aerosol and droplets, creating a flow sink in order to remove the particles. The effects of the suction flow on the aerosol and droplet travel are studied. The suction flow can remove aerosols and also reduce the spreading of droplets.

Keywords: aerosols, computational fluid dynamics, COVID-19, dental, discrete phase model, droplets, two-phase flow

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Authors: Fazlul Hoque, Tahmina Akter Joya, Asma Akter, Supawat Rungsuriyawiboon

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Rice is the staple food in Bangladesh, and therefore, self-sufficiency in rice production remains a major concern. However, Bangladesh is experiencing insufficiency in rice production due to high production cost and low national average productivity of 2.848 ton/ha in comparison to other rice-growing countries in the world. This study aims to find out the profit efficiency and determinants of profit efficiency in Boro rice cultivation in Manikganj and Dhaka districts of Bangladesh. It also focuses on technology adoption and effect of technology adoption on profit efficiency of Boro rice cultivation in Bangladesh. The data were collected from 300 households growing Boro rice through face to face interviews by one set structured questionnaire; Frontier Version 4.1 and STATA 15 software were employed to analyze the data according to the purpose of the study. Maximum likelihood estimates of the specified profit model showed that profit efficiency of the farmer varied between 23% and 97% with a mean of 76% which implied as 24% of the profit is lost due to a combination of technical and allocative inefficiencies in Boro rice cultivation in the study area. The inefficiency model revealed that the education level of the farmer, farm size, variety of seed, and training and extension service influence the profit inefficiency significantly. The study also explained that the level of technology adoption index affects profit efficiency. The technology adoption in Boro rice cultivation is influenced by the education level of the farmer, farm size and farm capital.

Keywords: farmer, maximum likelihood estimation, profit efficiency, rice

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Authors: Mulugeta Fola, Mengistu Ketema, Kumilachew Alamerie

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Watershed provides vast economic benefits within and beyond the management area of interest. But most watersheds in Ethiopia are increasingly facing the threats of degradation due to both natural and man-made causes. To reverse these problems, communities’ participation in sustainable management programs is among the necessary measures. Hence, this study assessed the households’ willingness to pay for watershed management practices through a contingent valuation study approach. Double bounded dichotomous choice with open-ended follow-up format was used to elicit the households’ willingness to pay. Based on data collected from 275 randomly selected households, descriptive statistics results indicated that most households (79.64%) were willing to pay for watershed management practices. A bivariate Probit model was employed to identify determinants of households’ willingness to pay and estimate mean willingness to pay. Its result shows that age, gender, income, livestock size, perception of watershed degradation, social position, and offered bids were important variables affecting willingness to pay for watershed management practices. The study also revealed that the mean willingness to pay for watershed management practices was calculated to be 58.41 Birr and 47.27 Birr per year from the double bounded and open-ended format, respectively. The study revealed that the aggregate welfare gains from watershed management practices were calculated to be 931581.09 Birr and 753909.23 Birr per year from double bounded dichotomous choice and open-ended format, respectively. Therefore, the policymakers should make households to pay for the services of watershed management practices in the study area.

Keywords: bivariate probit model, contingent valuation, watershed management practices, willingness to pay

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Authors: Yousef Farhaoui

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An IDS is a tool which is used to improve the level of security.In this paper we present different architectures of IDS. We will also discuss measures that define the effectiveness of IDS and the very recent works of standardization and homogenization of IDS. At the end, we propose a new model of IDS called BiIDS (IDS Based on the two principles of detection).

Keywords: intrusion detection, architectures, characteristic, tools, security

Procedia PDF Downloads 462

Authors: Ting Lu, Ya-Ru Diao, Fei Fan, Ye Xue, Lei Shi, Xian-e Tang, Meng-jun Zhan, Zhen-hua Deng

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Accurate adult age estimation (AAE) is a significant and challenging task in forensic and archeology fields. Attempts have been made to explore optimal adult age metrics, and the rib is considered a potential age marker. The traditional way is to extract age-related features designed by experts from macroscopic or radiological images followed by classification or regression analysis. Those results still have not met the high-level requirements for practice, and the limitation of using feature design and manual extraction methods is loss of information since the features are likely not designed explicitly for extracting information relevant to age. Deep learning (DL) has recently garnered much interest in imaging learning and computer vision. It enables learning features that are important without a prior bias or hypothesis and could be supportive of AAE. This study aimed to develop DL models for AAE based on CT images and compare their performance to the manual visual scoring method. Chest CT data were reconstructed using volume rendering (VR). Retrospective data of 2500 patients aged 20.00-69.99 years were obtained between December 2019 and September 2021. Five-fold cross-validation was performed, and datasets were randomly split into training and validation sets in a 4:1 ratio for each fold. Before feeding the inputs into networks, all images were augmented with random rotation and vertical flip, normalized, and resized to 224×224 pixels. ResNeXt was chosen as the DL baseline due to its advantages of higher efficiency and accuracy in image classification. Mean absolute error (MAE) was the primary parameter. Independent data from 100 patients acquired between March and April 2022 were used as a test set. The manual method completely followed the prior study, which reported the lowest MAEs (5.31 in males and 6.72 in females) among similar studies. CT data and VR images were used. The radiation density of the first costal cartilage was recorded using CT data on the workstation. The osseous and calcified projections of the 1 to 7 costal cartilages were scored based on VR images using an eight-stage staging technique. According to the results of the prior study, the optimal models were the decision tree regression model in males and the stepwise multiple linear regression equation in females. Predicted ages of the test set were calculated separately using different models by sex. A total of 2600 patients (training and validation sets, mean age=45.19 years±14.20 [SD]; test set, mean age=46.57±9.66) were evaluated in this study. Of ResNeXt model training, MAEs were obtained with 3.95 in males and 3.65 in females. Based on the test set, DL achieved MAEs of 4.05 in males and 4.54 in females, which were far better than the MAEs of 8.90 and 6.42 respectively, for the manual method. Those results showed that the DL of the ResNeXt model outperformed the manual method in AAE based on CT reconstruction of the costal cartilage and the developed system may be a supportive tool for AAE.

Keywords: forensic anthropology, age determination by the skeleton, costal cartilage, CT, deep learning

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Authors: Aaron Zhang, Alimire Kahaer, Gerald Weber, Nalin Arachchilage

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Access control is an essential safeguard for the security of enterprise data, which controls users’ access to information resources and ensures the confidentiality and integrity of information resources [1]. Research shows that the more common types of access control now have shortcomings [2]. In this direction, to improve the existing access control, we have studied the current technologies in the field of data security, deeply investigated the previous data access control policies and their problems, identified the existing deficiencies, and proposed a new extension structure of SPBAC. SPBAC extension proposed in this paper aims to combine Policy-Based Access Control (PBAC) with semantics to provide logically connected, real-time data access functionality by establishing associations between enterprise data through semantics. Our design combines policies with linked data through semantics to create a "Semantic link" so that access control is no longer per-database and determines that users in each role should be granted access based on the instance policy, and improves the SPBAC implementation by constructing policies and defined attributes through the XACML specification, which is designed to extend on the original XACML model. While providing relevant design solutions, this paper hopes to continue to study the feasibility and subsequent implementation of related work at a later stage.

Keywords: access control, semantic policy-based access control, semantic link, access control model, instance policy, XACML

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Authors: Assel Thami Lahlou, Soufiane Stouti, Ismail Lagrat, Hamid Mounir, Oussama Bouazaoui

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The purpose of this research work is to predict the helicopter from stalling by finding the minimum and maximum values that the pitch angle can take in order to fly in a hover state condition. The stall of a helicopter in hover occurs when the pitch angle is too small to generate the thrust required to support its weight or when the critical angle of attack that gives maximum lift is reached or exceeded. In order to find the minimum pitch angle, a 3D CFD simulation was done in this work using ANSYS FLUENT as the CFD solver. We started with a small value of the pitch angle θ, and we kept increasing its value until we found the thrust coefficient required to fly in a hover state and support the weight of the helicopter. For the CFD analysis, the Multiple Reference Frame (MRF) method with k-ε turbulent model was used to study the 3D flow around the rotor for θmin. On the other hand, a 2D simulation of the airfoil NACA 0012 was executed with a velocity inlet Vin=ΩR/2 to visualize the flow at the location span R/2 of the disk rotor using the Spallart-Allmaras turbulent model. Finding the critical angle of attack at this position will give us the ability to predict the stall in hover flight. The results obtained will be exposed later in the article. This study was so useful in analyzing the limitations of the helicopter’s main rotor and thus, in predicting accidents that can lead to a lot of damage.

Keywords: aerodynamic, CFD, helicopter, stall, blades, main rotor, minimum pitch angle, maximum pitch angle

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Authors: Abderrhamane Jarou, Dominique Sauter, Christophe Aubrun

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Over the past decade, the growing demand for energy efficiency in buildings has attracted the attention of the control community. Failures in HVAC (heating, ventilation and air conditioning) systems in buildings can have a significant impact on the desired and expected energy performance of buildings and on the user's comfort as well. FTC is a recent technology area that studies the adaptation of control algorithms to faulty operating conditions of a system. The application of Fault-Tolerant Control (FTC) in HVAC systems has gained attention in the last two decades. The objective is to maintain the variations in system performance due to faults within an acceptable range with respect to the desired nominal behavior. This paper considers the so-called active approach, which is based on fault and identification scheme combined with a control reconfiguration algorithm that consists in determining a new set of control parameters so that the reconfigured performance is "as close as possible, "in some sense, to the nominal performance. Thermal models of buildings and their HVAC systems are described by non-linear (usually bi-linear) equations. Most of the works carried out so far in FDI (fault diagnosis and isolation) or FTC consider a linearized model of the studied system. However, this model is only valid in a reduced range of variation. This study presents a new fault diagnosis (FD) algorithm based on a bilinear observer for the detection and accurate estimation of the magnitude of the HVAC system failure. The main contribution of the proposed FD algorithm is that instead of using specific linearized models, the algorithm inherits the structure of the actual bilinear model of the building thermal dynamics. As an immediate consequence, the algorithm is applicable to a wide range of unpredictable operating conditions, i.e., weather dynamics, outdoor air temperature, zone occupancy profile. A bilinear fault detection observer is proposed for a bilinear system with unknown inputs. The residual vector in the observer design is decoupled from the unknown inputs and, under certain conditions, is made sensitive to all faults. Sufficient conditions are given for the existence of the observer and results are given for the explicit computation of observer design matrices. Dedicated observer schemes (DOS) are considered for sensor FDI while unknown input bilinear observers are considered for actuator or system components FDI. The proposed strategy for FTC works as follows: At a first level, FDI algorithms are implemented, making it also possible to estimate the magnitude of the fault. Once the fault is detected, the fault estimation is then used to feed the second level and reconfigure the control low so that that expected performances are recovered. This paper is organized as follows. A general structure for fault-tolerant control of buildings is first presented and the building model under consideration is introduced. Then, the observer-based design for Fault Diagnosis of bilinear systems is studied. The FTC approach is developed in Section IV. Finally, a simulation example is given in Section V to illustrate the proposed method.

Keywords: bilinear systems, fault diagnosis, fault-tolerant control, multi-zones building

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Authors: Jiaying Zhang, Xin Mu, Chang Ni, Jeff L. Zhang

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Magnetic resonance elastography (MRE) non-invasively assesses tissue elastic properties, such as shear modulus, by measuring tissue’s displacement in response to mechanical waves. The estimated metrics on tissue elasticity or stiffness have been shown to be valuable for monitoring physiologic or pathophysiologic status of tissue, such as a tumor or fatty liver. To quantify tissue shear modulus from MRE-acquired displacements (essentially an inverse problem), multiple approaches have been proposed, including Local Frequency Estimation (LFE) and Direct Inversion (DI). However, one common problem with these methods is that the estimates are severely noise-sensitive due to either the inverse-problem nature or noise propagation in the pixel-by-pixel process. With the advent of deep learning (DL) and its promise in solving inverse problems, a few groups in the field of MRE have explored the feasibility of using DL methods for quantifying shear modulus from MRE data. Most of the groups chose to use real MRE data for DL model training and to cut training images into smaller patches, which enriches feature characteristics of training data but inevitably increases computation time and results in outcomes with patched patterns. In this study, simulated wave images generated by Finite Differential Time Domain (FDTD) simulation are used for network training, and U-Net is used to extract features from each training image without cutting it into patches. The use of simulated data for model training has the flexibility of customizing training datasets to match specific applications. The proposed method aimed to estimate tissue shear modulus from MRE data with high robustness to noise and high model-training efficiency. Specifically, a set of 3000 maps of shear modulus (with a range of 1 kPa to 15 kPa) containing randomly positioned objects were simulated, and their corresponding wave images were generated. The two types of data were fed into the training of a U-Net model as its output and input, respectively. For an independently simulated set of 1000 images, the performance of the proposed method against DI and LFE was compared by the relative errors (root mean square error or RMSE divided by averaged shear modulus) between the true shear modulus map and the estimated ones. The results showed that the estimated shear modulus by the proposed method achieved a relative error of 4.91%±0.66%, substantially lower than 78.20%±1.11% by LFE. Using simulated data, the proposed method significantly outperformed LFE and DI in resilience to increasing noise levels and in resolving fine changes of shear modulus. The feasibility of the proposed method was also tested on MRE data acquired from phantoms and from human calf muscles, resulting in maps of shear modulus with low noise. In future work, the method’s performance on phantom and its repeatability on human data will be tested in a more quantitative manner. In conclusion, the proposed method showed much promise in quantifying tissue shear modulus from MRE with high robustness and efficiency.

Keywords: deep learning, magnetic resonance elastography, magnetic resonance imaging, shear modulus estimation

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Authors: Calister Wingang Makebe, Wilson Ambindei Agwanande, Emmanuel Jong Nso, P. Nisha

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Traditional liquid-state fermentation processes of Annona muricata L. juice can result in fluctuating product quality and quantity due to difficulties in control and scale up. This work describes a laboratory-scale batch fermentation process to produce a probiotic Annona muricata L. enzymatically extracted juice, which was modeled using the Doehlert design with independent extraction factors being incubation time, temperature, and enzyme concentration. It aimed at a better understanding of the traditional process as an initial step for future optimization. Annona muricata L. juice was fermented with L. acidophilus (NCDC 291) (LA), L. casei (NCDC 17) (LC), and a blend of LA and LC (LCA) for 72 h at 37 °C. Experimental data were fitted into mathematical models (Monod, Logistic and Luedeking and Piret models) using MATLAB software, to describe biomass growth, sugar utilization, and organic acid production. The optimal fermentation time was obtained based on cell viability, which was 24 h for LC and 36 h for LA and LCA. The model was particularly effective in estimating biomass growth, reducing sugar consumption, and lactic acid production. The values of the determination coefficient, R2, were 0.9946, 0.9913 and 0.9946, while the residual sum of square error, SSE, was 0.2876, 0.1738 and 0.1589 for LC, LA and LCA, respectively. The growth kinetic parameters included the maximum specific growth rate, µm, which was 0.2876 h-1, 0.1738 h-1 and 0.1589 h-1 as well as the substrate saturation, Ks, with 9.0680 g/L, 9.9337 g/L and 9.0709 g/L respectively for LC, LA and LCA. For the stoichiometric parameters, the yield of biomass based on utilized substrate (YXS) was 50.7932, 3.3940 and 61.0202, and the yield of product based on utilized substrate (YPS) was 2.4524, 0.2307 and 0.7415 for LC, LA, and LCA, respectively. In addition, the maintenance energy parameter (ms) was 0.0128, 0.0001 and 0.0004 with respect to LC, LA and LCA. With the kinetic model proposed by Luedeking and Piret for lactic acid production rate, the growth associated, and non-growth associated coefficients were determined as 1.0028 and 0.0109, respectively. The model was demonstrated for batch growth of LA, LC, and LCA in Annona muricata L. juice. The present investigation validates the potential of Annona muricata L. based medium for heightened economical production of a probiotic medium.

Keywords: L. acidophilus, L. casei, fermentation, modelling, kinetics

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Authors: Torsten Hermanns, Thoufik Al Khawli, Wolfgang Schulz

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In laser cutting as well as in long pulsed laser drilling of metals, it can be demonstrated that the ablation shape (the shape of cut faces respectively the hole shape) that is formed approaches a so-called asymptotic shape such that it changes only slightly or not at all with further irradiation. These findings are already known from the ultrashort pulse (USP) ablation of dielectric and semiconducting materials. The explanation for the occurrence of an asymptotic shape in laser cutting and long pulse drilling of metals is identified, its underlying mechanism numerically implemented, tested and clearly confirmed by comparison with experimental data. In detail, there now is a model that allows the simulation of the temporal (pulse-resolved) evolution of the hole shape in laser drilling as well as the final (asymptotic) shape of the cut faces in laser cutting. This simulation especially requires much less in the way of resources, such that it can even run on common desktop PCs or laptops. Individual parameters can be adjusted using sliders – the simulation result appears in an adjacent window and changes in real time. This is made possible by an application-specific reduction of the underlying ablation model. Because this reduction dramatically decreases the complexity of calculation, it produces a result much more quickly. This means that the simulation can be carried out directly at the laser machine. Time-intensive experiments can be reduced and set-up processes can be completed much faster. The high speed of simulation also opens up a range of entirely different options, such as metamodeling. Suitable for complex applications with many parameters, metamodeling involves generating high-dimensional data sets with the parameters and several evaluation criteria for process and product quality. These sets can then be used to create individual process maps that show the dependency of individual parameter pairs. This advanced simulation makes it possible to find global and local extreme values through mathematical manipulation. Such simultaneous optimization of multiple parameters is scarcely possible by experimental means. This means that new methods in manufacturing such as self-optimization can be executed much faster. However, the software’s potential does not stop there; time-intensive calculations exist in many areas of industry. In laser welding or laser additive manufacturing, for example, the simulation of thermal induced residual stresses still uses up considerable computing capacity or is even not possible. Transferring the principle of reduced models promises substantial savings there, too.

Keywords: asymptotic ablation shape, interactive process simulation, laser drilling, laser cutting, metamodeling, reduced modeling

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Authors: Udayakumar Vee, Franck Quero

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Zwitterionic polymers generally have been viewed as a new class of antimicrobial and non-fouling materials. They offer a broad versatility for chemical modification and hence great freedom for accurate molecular design, which bear an equimolar number of homogenously distributed anionic and cationic groups along their polymer chains. This study explores the effectiveness of the auxetic zwitterion carboxylate/sulfonate hydrogel in the diabetic-induced mouse model. A series of silver metal-doped auxetic zwitterion carboxylate/sulfonate/vinylaniline copolymer hydrogels is designed via a 3D printer. Zwitterion monomers have been characterized by FT-IR and NMR techniques. The effect of changing the monomers and different loading ratios of Ag over zwitterion on the final hydrogel materials' antimicrobial properties and biocompatibility will be investigated in detail. The synthesized auxetic hydrogel has been characterized using a wide range of techniques to help establish the relationship between molecular level and macroscopic properties of these materials, including mechanical and antibacterial and biocompatibility and wound healing ability. This work's comparative studies and results provide new insights and guide us in choosing a better auxetic structured material for a broad spectrum of wound healing applications in the animal model. We expect this approach to provide a versatile and robust platform for biomaterial design that could lead to promising treatments for wound healing applications.

Keywords: auxetic, zwitterion, carboxylate, sulfonate, polymer, wound healing

Procedia PDF Downloads 140

Authors: Udayakumar Veerabagu, Franck Quero

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Zwitterion carboxylate and sulfonate polymers generally have been viewed as a new class of antimicrobial and non-fouling materials. They offer a broad versatility for chemical modification and hence great freedom for accurate molecular design, which bear an equimolar number of homogenously distributed anionic and cationic groups along their polymer chains. This study explores the effectiveness of the auxetic zwitterion carboxylate/sulfonate hydrogel in the diabetic-induced mouse model. A series of silver metal-doped auxetic zwitterion carboxylate/sulfonate/vinylaniline copolymer hydrogels is designed via a 3D printer. Zwitterion monomers have been characterized by FT-IR and NMR techniques. The effect of changing the monomers and different loading ratios of Ag over zwitterion on the final hydrogel materials' antimicrobial properties and biocompatibility will be investigated in detail. The synthesized auxetic hydrogel has been characterized using a wide range of techniques to help establish the relationship between molecular level and macroscopic properties of these materials, including mechanical and antibacterial and biocompatibility and wound healing ability. This work's comparative studies and results provide new insights and guide us in choosing a better auxetic structured material for a broad spectrum of wound healing applications in the animal model. We expect this approach to provide a versatile and robust platform for biomaterial design that could lead to promising treatments for wound healing applications.

Keywords: auxetic, zwitterion, carboxylate, sulfonate, polymer, wound healing

Procedia PDF Downloads 156

Authors: Tatiana Stanchuliak

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It is common knowledge that intonation is not laid over a ready text. On the contrary, intonation forms and accompanies the text on the level of its birth in the speaker’s mind. As a result, intonation plays one of the fundamental roles in the process of transferring a thought into external speech. Intonation structure can highlight the semantic significance of textual elements and become a ranging mark in understanding the information structure of the text. Intonation functions by means of prosodic characteristics, one of which is intonation salience, whose function in texts results in making some textual elements more prominent than others. This function of intonation, therefore, performs as organizing. It helps to form the frame of key elements of the text. The study under consideration made an attempt to look into the inner nature of salience and create a sort of a text intonation model. This general goal brought to some more specific intermediate results. First, there were established degrees of salience on the level of the smallest semantic element - intonation group, as well as prosodic means of creating salience, were examined. Second, the most frequent combinations of prosodic means made it possible to distinguish patterns of salience, which then became constituent elements of a text intonation model. Third, the analysis of the predicate structure allowed to divide the whole text into smaller parts, or units, which performed a specific function in the developing of the general communicative intention. It appeared that such units can be found in any text and they have common characteristics of their intonation arrangement. These findings are certainly very important both for the theory of intonation and their practical application.

Keywords: accentuation , inner speech, intention, intonation, intonation functions, models, patterns, predicate, salience, semantics, sentence stress, text

Procedia PDF Downloads 266

Authors: Musarrat Jabeen

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Thoughtful intelligence offers a sustainable position to enhance the influence of decision-makers. Thoughtful Intelligence implies the understanding to realize the impact of one’s thoughts, words and actions on the survival, dignity and development of the individuals, groups and nations. Thoughtful intelligence has received minimal consideration in the area of Decision Support Systems, with an end goal to evaluate the quantity of knowledge and its viability. This pattern degraded the imbibed contribution of thoughtful intelligence required for sustainable decision making. Given the concern, this paper concentrates on the question: How to present a model of Thoughtful Decision Support System (TDSS)? The aim of this paper is to appreciate the concepts of thoughtful intelligence and insinuate a Decision Support System based on thoughtful intelligence. Thoughtful intelligence includes three dynamic competencies: i) Realization about long term impacts of decisions that are made in a specific time and space, ii) A great sense of taking actions, iii) Intense interconnectivity with people and nature and; seven associate competencies, of Righteousness, Purposefulness, Understanding, Contemplation, Sincerity, Mindfulness, and Nurturing. The study utilizes two methods: Focused group discussion to count prevailing Decision Support Systems; 70% results of focus group discussions found six decision support systems and the positive inexistence of thoughtful intelligence among decision support systems regarding sustainable decision making. Delphi focused on defining thoughtful intelligence to model (TDSS). 65% results helped to conceptualize (definition and description) of thoughtful intelligence. TDSS is offered here as an addition in the decision making literature. The clients are top leaders.

Keywords: thoughtful intelligence, sustainable decision making, thoughtful decision support system

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Authors: A. A. Dare, E. U. Iniegbedion

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Industrial furnaces generally involve enclosures of fire typically initiated by the combustion of gases. The fire leads to temperature distribution inside the enclosure. A proper understanding of the temperature and velocity distribution within the enclosure is often required for optimal design and use of the furnace. This study was therefore directed at numerical modeling of temperature distribution inside an enclosure as typical in a furnace. A mathematical model was developed from the conservation of mass, momentum and energy. The stream function-vorticity formulation of the governing equations was solved by an alternating direction implicit (ADI) finite difference technique. The finite difference formulation obtained were then developed into a computer code. This was used to determine the temperature, velocities, stream function and vorticity. The effect of the wall heat conduction was also considered, by assuming a one-dimensional heat flow through the wall. The computer code (MATLAB program) developed was used for the determination of the aforementioned variables. The results obtained showed that the transient temperature distribution assumed a uniform profile which becomes more chaotic with increasing time. The vertical velocity showed increasing turbulent behavior with time, while the horizontal velocity assumed decreasing laminar behavior with time. All of these behaviours were equally reported in the literature. The developed model has provided understanding of heat transfer process in an industrial furnace.

Keywords: heat source, modelling, enclosure, furnace

Procedia PDF Downloads 255

Authors: Matthew B. Davis, Amit Kumar

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With potentially dangerous impacts of climate change on the horizon, Canada has an opportunity to take a lead role on the international stage to demonstrate how energy use intensity and greenhouse gas emission intensity may be effectively reduced. Through bottom-up modelling of Canada’s energy sector using Long-range Energy Alternative Planning (LEAP) software, it can be determined where efforts should to be concentrated to produce the most positive energy management results. By analyzing a provincially integrated Canada, one can develop strategies to minimize the country’s economic downfall while transitioning to lower-emission energy technologies. Canada’s electricity sector plays an important role in accommodating these transitionary technologies as fossil-fuel based power production is prevalent in many parts of the country and is responsible for a large portion (17%) of Canada’s greenhouse gas emissions. Current findings incorporate an in-depth model of Canada’s current energy supply and demand sectors, as well as a business-as-usual scenario up to the year 2035. This allows for in-depth analysis of energy flow from resource potential, to extraction, to fuel and electricity production, to energy end use and emissions in Canada’s residential, transportation, commercial, institutional, industrial, and agricultural sectors. Bottom-up modelling techniques such as these are useful to critically analyze and compare the various possible scenarios of implementing sustainable energy measures. This work can aid government in creating effective energy and environmental policies, as well as guide industry to what technology or process changes would be most worthwhile to pursue.

Keywords: energy management, LEAP, energy end-use, GHG emissions

Procedia PDF Downloads 301

Authors: Han-Mei Chen, Rongxin Zhou, Taige Wang

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Glass is widely used in everyday life, from glass bottles for beverages to architectural glass for various forms of glazing. Although the mainstream of used glass is recycled in the UK, the single-use and then recycling procedure results in a lot of waste as it incorporates intact glass with smashing, re-melting, and remanufacturing. These processes bring massive energy consumption with a huge loss of high embodied energy and economic value, compared to re-use, which’s towards a ‘zero carbon’ target. As a tourism city, Liverpool has more glass bottle consumption than most less leisure-focused cities. It’s therefore vital for Liverpool to find an upgrading approach for the single-use glass bottles with low carbon output. This project aims to assess the feasibility of industrial symbiosis and upgrading the framework of glass and to investigate the ways of achieving them. It is significant to Liverpool’s future industrial strategy since it provides an opportunity to target economic recovery for post-COVID by industry symbiosis and up-grading waste management in Liverpool to respond to the climate emergency. In addition, it will influence the local government policy for glass bottle reuse and recycling in North West England and as a good practice to be further recommended to other areas of the UK. First, a critical literature review of glass waste strategies has been conducted in the UK and worldwide industrial symbiosis practices. Second, mapping, data collection, and analysis have shown the current life cycle chain and the strong links of glass reuse and upgrading potentials via site visits to 16 local waste recycling centres. The results of this research have demonstrated the understanding of the influence of key factors on the development of a circular industrial symbiosis business model for beverage glass bottles. The current waste management procedures of the glass bottle industry, its business model, supply chain, and material flow have been reviewed. The various potential opportunities for glass bottle up-valuing have been investigated towards an industrial symbiosis in Liverpool. Finally, an up-valuing business model has been developed for an industrial symbiosis framework of glass in Liverpool. For glass bottles, there are two possibilities 1) focus on upgrading processes towards re-use rather than single-use and recycling and 2) focus on ‘smart’ re-use and recycling, leading to optimised values in other sectors to create a wider industry symbiosis for a multi-level and circular economy.

Keywords: glass bottles, industry symbiosis, smart re-use, waste upgrading

Procedia PDF Downloads 107

Authors: Fatema Akram, Mohammad G. Rasul, M. Masud K. Khan, M. Sharif I. I. Amir

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Australia is a country of some 7,700 million square kilometres with a population of about 22.6 million. At present water security is a major challenge for Australia. In some areas the use of water resources is approaching and in some parts it is exceeding the limits of sustainability. A focal point of proposed national water conservation programs is the recycling of both urban storm-water and treated wastewater. But till now it is not widely practiced in Australia, and particularly storm-water is neglected. In Australia, only 4% of storm-water and rainwater is recycled, whereas less than 1% of reclaimed wastewater is reused within urban areas. Therefore, accurately monitoring, assessing and predicting the availability, quality and use of this precious resource are required for better management. As storm-water is usually of better quality than untreated sewage or industrial discharge, it has better public acceptance for recycling and reuse, particularly for non-potable use such as irrigation, watering lawns, gardens, etc. Existing storm-water recycling practice is far behind of research and no robust technologies developed for this purpose. Therefore, there is a clear need for using modern technologies for assessing feasibility of storm-water harvesting and reuse. Numerical modelling has, in recent times, become a popular tool for doing this job. It includes complex hydrological and hydraulic processes of the study area. The hydrologic model computes storm-water quantity to design the system components, and the hydraulic model helps to route the flow through storm-water infrastructures. Nowadays water quality module is incorporated with these models. Integration of Geographic Information System (GIS) with these models provides extra advantage of managing spatial information. However for the overall management of a storm-water harvesting project, Decision Support System (DSS) plays an important role incorporating database with model and GIS for the proper management of temporal information. Additionally DSS includes evaluation tools and Graphical user interface. This research aims to critically review and discuss all the aspects of storm-water harvesting and reuse such as available guidelines of storm-water harvesting and reuse, public acceptance of water reuse, the scopes and recommendation for future studies. In addition to these, this paper identifies, understand and address the importance of modern technologies capable of proper management of storm-water harvesting and reuse.

Keywords: storm-water management, storm-water harvesting and reuse, numerical modelling, geographic information system, decision support system, database

Procedia PDF Downloads 372