Search results for: dual phase lag model
Commenced in January 2007
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Edition: International
Paper Count: 20930

Search results for: dual phase lag model

17210 Service Interactions Coordination Using a Declarative Approach: Focuses on Deontic Rule from Semantics of Business Vocabulary and Rules Models

Authors: Nurulhuda A. Manaf, Nor Najihah Zainal Abidin, Nur Amalina Jamaludin

Abstract:

Coordinating service interactions are a vital part of developing distributed applications that are built up as networks of autonomous participants, e.g., software components, web services, online resources, involve a collaboration between a diverse number of participant services on different providers. The complexity in coordinating service interactions reflects how important the techniques and approaches require for designing and coordinating the interaction between participant services to ensure the overall goal of a collaboration between participant services is achieved. The objective of this research is to develop capability of steering a complex service interaction towards a desired outcome. Therefore, an efficient technique for modelling, generating, and verifying the coordination of service interactions is developed. The developed model describes service interactions using service choreographies approach and focusing on a declarative approach, advocating an Object Management Group (OMG) standard, Semantics of Business Vocabulary and Rules (SBVR). This model, namely, SBVR model for service choreographies focuses on a declarative deontic rule expressing both obligation and prohibition, which can be more useful in working with coordinating service interactions. The generated SBVR model is then be formulated and be transformed into Alloy model using Alloy Analyzer for verifying the generated SBVR model. The transformation of SBVR into Alloy allows to automatically generate the corresponding coordination of service interactions (service choreography), hence producing an immediate instance of execution that satisfies the constraints of the specification and verifies whether a specific request can be realised in the given choreography in the generated choreography.

Keywords: service choreography, service coordination, behavioural modelling, complex interactions, declarative specification, verification, model transformation, semantics of business vocabulary and rules, SBVR

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17209 Application of Seasonal Autoregressive Integrated Moving Average Model for Forecasting Monthly Flows in Waterval River, South Africa

Authors: Kassahun Birhanu Tadesse, Megersa Olumana Dinka

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Reliable future river flow information is basic for planning and management of any river systems. For data scarce river system having only a river flow records like the Waterval River, a univariate time series models are appropriate for river flow forecasting. In this study, a univariate Seasonal Autoregressive Integrated Moving Average (SARIMA) model was applied for forecasting Waterval River flow using GRETL statistical software. Mean monthly river flows from 1960 to 2016 were used for modeling. Different unit root tests and Mann-Kendall trend analysis were performed to test the stationarity of the observed flow time series. The time series was differenced to remove the seasonality. Using the correlogram of seasonally differenced time series, different SARIMA models were identified, their parameters were estimated, and diagnostic check-up of model forecasts was performed using white noise and heteroscedasticity tests. Finally, based on minimum Akaike Information (AIc) and Hannan-Quinn (HQc) criteria, SARIMA (3, 0, 2) x (3, 1, 3)12 was selected as the best model for Waterval River flow forecasting. Therefore, this model can be used to generate future river information for water resources development and management in Waterval River system. SARIMA model can also be used for forecasting other similar univariate time series with seasonality characteristics.

Keywords: heteroscedasticity, stationarity test, trend analysis, validation, white noise

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17208 Exploring the Effect of Using Lesh Model in Enhancing Prospective Mathematics Teachers’ Number Sense

Authors: Areej Isam Barham

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Developing students’ number sense is an essential element in the learning of mathematics. Number sense is one of the foundational ideas in mathematics where students need to understand numbers, representing them in different ways, and realize the relationships among numbers. Number sense also reflects students’ understanding of the meaning of operations, how they related to one another, how to compute fluently and make reasonable estimates. Developing students’ number sense in the mathematics classroom requires good preparation for mathematics teachers, those who will direct their students towards the real understanding of numbers and its implementation in the learning of mathematics. This study describes the development of elementary prospective mathematics teachers’ number sense through a mathematics teaching methods course at Qatar University. The study examined the effect of using the Lesh model in enhancing mathematics prospective teachers’ number sense. Thirty-nine elementary prospective mathematics teachers involved in the current study. The study followed an experimental research approach, and quantitative research methods were used to answer the research questions. Pre-post number sense test was constructed and implemented before and after teaching by using the Lesh model. Data were analyzed using Statistical Packages for Social Sciences (SPSS). Descriptive data analysis and t-test were used to examine the impact of using the Lesh model in enhancing prospective teachers’ number sense. Finding of the study indicated poor number sense and limited numeracy skills before implementing the use of the Lesh model, which highly demonstrate the importance of the study. The results of the study also revealed a positive impact on the use of the Lesh model in enhancing prospective teachers’ number sense with statistically significant differences. The discussion of the study addresses different features and issues related to the participants’ number sense. In light of the study, the research presents recommendations and suggestions for the future development of mathematics prospective teachers’ number sense.

Keywords: number sense, Lesh model, prospective mathematics teachers, development of number sense

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17207 Machine Learning Model to Predict TB Bacteria-Resistant Drugs from TB Isolates

Authors: Rosa Tsegaye Aga, Xuan Jiang, Pavel Vazquez Faci, Siqing Liu, Simon Rayner, Endalkachew Alemu, Markos Abebe

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Tuberculosis (TB) is a major cause of disease globally. In most cases, TB is treatable and curable, but only with the proper treatment. There is a time when drug-resistant TB occurs when bacteria become resistant to the drugs that are used to treat TB. Current strategies to identify drug-resistant TB bacteria are laboratory-based, and it takes a longer time to identify the drug-resistant bacteria and treat the patient accordingly. But machine learning (ML) and data science approaches can offer new approaches to the problem. In this study, we propose to develop an ML-based model to predict the antibiotic resistance phenotypes of TB isolates in minutes and give the right treatment to the patient immediately. The study has been using the whole genome sequence (WGS) of TB isolates as training data that have been extracted from the NCBI repository and contain different countries’ samples to build the ML models. The reason that different countries’ samples have been included is to generalize the large group of TB isolates from different regions in the world. This supports the model to train different behaviors of the TB bacteria and makes the model robust. The model training has been considering three pieces of information that have been extracted from the WGS data to train the model. These are all variants that have been found within the candidate genes (F1), predetermined resistance-associated variants (F2), and only resistance-associated gene information for the particular drug. Two major datasets have been constructed using these three information. F1 and F2 information have been considered as two independent datasets, and the third information is used as a class to label the two datasets. Five machine learning algorithms have been considered to train the model. These are Support Vector Machine (SVM), Random forest (RF), Logistic regression (LR), Gradient Boosting, and Ada boost algorithms. The models have been trained on the datasets F1, F2, and F1F2 that is the F1 and the F2 dataset merged. Additionally, an ensemble approach has been used to train the model. The ensemble approach has been considered to run F1 and F2 datasets on gradient boosting algorithm and use the output as one dataset that is called F1F2 ensemble dataset and train a model using this dataset on the five algorithms. As the experiment shows, the ensemble approach model that has been trained on the Gradient Boosting algorithm outperformed the rest of the models. In conclusion, this study suggests the ensemble approach, that is, the RF + Gradient boosting model, to predict the antibiotic resistance phenotypes of TB isolates by outperforming the rest of the models.

Keywords: machine learning, MTB, WGS, drug resistant TB

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17206 Increasing Solubility and Bioavailability of Fluvastatin through Transdermal Nanoemulsion Gel Delivery System for the Treatment of Osteoporosis

Authors: Ramandeep Kaur, Makula Ajitha

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Fluvastatin has been reported for increasing bone mineral density in osteoporosis since last decade. Systemically administered drug undergoes extensive hepatic first-pass metabolism, thus very small amount of drug reaches the bone tissue which is highly insignificant. The present study aims to deliver fluvastatin in the form of nanoemulsion (NE) gel directly to the bone tissue through transdermal route thereby bypassing hepatic first pass metabolism. The NE formulation consisted of isopropyl myristate as oil, tween 80 as surfactant, transcutol as co-surfactant and water as the aqueous phase. Pseudoternary phase diagrams were constructed using aqueous titration method and NE’s obtained were subjected to thermodynamic-kinetic stability studies. The stable NE formulations were evaluated for their droplet size, zeta potential, and transmission electron microscopy (TEM). The nano-sized formulations were incorporated into 0.5% carbopol 934 gel matrix. Ex-vivo permeation behaviour of selected formulations through rat skin was investigated and compared with the conventional formulations (suspension and emulsion). Further, in-vivo pharmacokinetic study was carried using male Wistar rats. The optimized NE formulations mean droplet size was 11.66±3.2 nm with polydispersity index of 0.117. Permeation flux of NE gel formulations was found significantly higher than the conventional formulations i.e. suspension and emulsion. In vivo pharmacokinetic study showed significant increase in bioavailability (1.25 fold) of fluvastatin than oral formulation. Thus, it can be concluded that NE gel was successfully developed for transdermal delivery of fluvastatin for the treatment of osteoporosis.

Keywords: fluvastatin, nanoemulsion gel, osteoporosis, transdermal

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17205 The Influence of Hydrolyzed Cartilage Collagen on General Mobility and Wellbeing of an Active Population

Authors: Sara De Pelsmaeker, Catarina Ferreira da Silva, Janne Prawit

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Recent studies show that enzymatically hydrolysed collagen is absorbed and distributed to joint tissues, where it has analgesic and active anti-inflammatory properties. Reviews of the associated relevant literature also support this theory. However, these studies are all using hydrolyzed collagen from animal hide or skin. This study looks into the effect of daily supplementation of hydrolyzed cartilage collagen (HCC), which has a different composition. A consumer study was set up using a double-blind placebo-controlled design with a control group using twice a day 0.5gr of maltodextrin and an experimental group using twice 0.5g of HCC, over a trial period of 12 weeks. A follow-up phase of 4 weeks without supplementation was taken into the experiment to investigate the ‘wash-out’ phase. As this consumer study was conducted during the lockdown periods, a specific app was designed to follow up with the participants. The app had the advantage that in this way, the motivation of the participants was enhanced and the drop-out range of participants was lower than normally seen in consumer studies. Participants were recruited via various sports and health clubs across the UK as we targeted a general population of people that considered themselves in good health. Exclusion criteria were ‘not experiencing any medical conditions’ and ‘not taking any prescribed medication’. A minimum requirement was that they regularly engaged in some level of physical activity. The participants had to log the type of activity that they conducted and the duration of the activity. Weekly, participants were providing feedback on their joint health and subjective pain using the validated pain measuring instrument Visual Analogue Scale (VAS). The weekly repoAbstract Public Health and Wellbeing Conferencerting section in the app was designed with simplicity and based on the accuracy demonstrated in previous similar studies to track subjective pain measures of participants. At the beginning of the trial, each participant indicated their baseline on joint pain. The results of this consumer study indicated that HCC significantly improved joint health and subjective pain scores compared to the placebo group. No significant differences were found between different demographic groups (age or gender). The level of activity, going from high intensive training to regular walking, did not significantly influence the effect of the HCC. The results of the wash-out phase indicated that when the participants stopped the HCC supplementation, their subjective pain scores increased again to the baseline. In conclusion, the results gave a positive indication that the daily supplementation of HCC can contribute to the overall mobility and wellbeing of a general active population

Keywords: VAS-score, food supplement, mobility, joint health

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17204 Epidemiology of Gestational Choriocarcinoma: A Systematic Review

Authors: Farah Amalina Mohamed Affandi, Redhwan Ahmad Al-Naggar, Seok Mui Wang, Thanikasalam Kathiresan

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Gestational choriocarcinoma is a condition in which there is an abnormal growth or a tumor inside the women’s uterus after conception. It is a type of gestational trophoblastic disease which is relatively rare and malignant. The current epidemiological data of this disease are inadequate. The purposes of this study are to examine the epidemiology of choriocarcinoma and their risk factors based on all available population-based and hospital-based data of the disease. In this study, we searched The MEDLINE and Cumulative Index to Nursing and Allied Health Literature (CINAHL) databases using the keywords ‘choriocarcinoma’, ‘gestational’, ‘gestational choriocarcinoma’ and ‘epidemiology’. We included only human studies published in English between 1995 and 2015 to ensure up to date evidence. Case studies, case reports, animal studies, letters to the editor, news, and review articles were excluded. Retrieved articles were screened in three phases. In the first phase, any articles that did not match the inclusion criteria based solely on titles were excluded. In the second phase, the abstracts of remaining articles were screened thoroughly; any articles that did not meet our inclusion criteria were excluded. In the final phase, full texts of the remaining articles were read and assessed to exclude articles that did not meet the inclusion criteria or any articles that fulfilled the exclusion criteria. Duplicates articles were also removed. Systematic reviews and meta-analysis were excluded. Extracted data were summarized in table and figures descriptively. The reference lists of included studies were thoroughly reviewed in search for other relevant studies. A total of ten studies met all the selection criteria. Nine were retrospective studies and one was cohort study. Total numbers of 4563 cases of choriocarcinoma were reviewed from several countries which are Korea, Japan, South Africa, USA, New Mexico, Finland, Turkey, China, Brazil and The Netherlands. Different studies included different range of age with their mean age of 28.5 to 30.0 years. All studies investigated on the disease’s incidence rate, only two studies examined on the risk factors or associations of the disease. Approximately 20% of the studies showed a reduction in the incidence of choriocarcinoma while the other 80% showed inconsistencies in rate. Associations of age, fertility age, occupations and socio-demographic with the status remains unclear. There is limited information on the epidemiological aspects of gestational choriocarcinoma. The observed results indicated there was a decrease in the incidence rate of gestational choriocarcinoma globally. These could be due to the reduction in the incidence of molar pregnancy and the efficacy of the treatment, mainly by chemotherapy.

Keywords: epidemiology, gestational choriocarcinoma, incidence, prevalence, risk factor

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17203 Design of Smart Urban Lighting by Using Social Sustainability Approach

Authors: Mohsen Noroozi, Maryam Khalili

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Creating cities, objects and spaces that are economically, environmentally and socially sustainable and which meet the challenge of social interaction and generation change will be one of the biggest tasks of designers. Social sustainability is about how individuals, communities and societies live with each other and set out to achieve the objectives of development model which they have chosen for themselves. Urban lightning as one of the most important elements of urban furniture that people constantly interact with it in public spaces; can be a significant object for designers. Using intelligence by internet of things for urban lighting makes it more interactive in public environments. It can encourage individuals to carry out appropriate behaviors and provides them the social awareness through new interactions. The greatest strength of this technology is its strong impact on many aspects of everyday life and users' behaviors. The analytical phase of the research is based on a multiple method survey strategy. Smart lighting proposed in this paper is an urban lighting designed on results obtained from a collective point of view about the social sustainability. In this paper, referring to behavioral design methods, the social behaviors of the people has been studied. Data show that people demands for a deeper experience of social participation, safety perception and energy saving with the meaningful use of interactive and colourful lighting effects. By using intelligent technology, some suggestions are provided in the field of future lighting to consider the new forms of social sustainability.

Keywords: behavior pattern, internet of things, social sustainability, urban lighting

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17202 Generalized Synchronization in Systems with a Complex Topology of Attractor

Authors: Olga I. Moskalenko, Vladislav A. Khanadeev, Anastasya D. Koloskova, Alexey A. Koronovskii, Anatoly A. Pivovarov

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Generalized synchronization is one of the most intricate phenomena in nonlinear science. It can be observed both in systems with a unidirectional and mutual type of coupling including the complex networks. Such a phenomenon has a number of practical applications, for example, for the secure information transmission through the communication channel with a high level of noise. Known methods for the secure information transmission needs in the increase of the privacy of data transmission that arises a question about the observation of such phenomenon in systems with a complex topology of chaotic attractor possessing two or more positive Lyapunov exponents. The present report is devoted to the study of such phenomenon in two unidirectionally and mutually coupled dynamical systems being in chaotic (with one positive Lyapunov exponent) and hyperchaotic (with two or more positive Lyapunov exponents) regimes, respectively. As the systems under study, we have used two mutually coupled modified Lorenz oscillators and two unidirectionally coupled time-delayed generators. We have shown that in both cases the generalized synchronization regime can be detected by means of the calculation of Lyapunov exponents and phase tube approach whereas due to the complex topology of attractor the nearest neighbor method is misleading. Moreover, the auxiliary system approaches being the standard method for the synchronous regime observation, for the mutual type of coupling results in incorrect results. To calculate the Lyapunov exponents in time-delayed systems we have proposed an approach based on the modification of Gram-Schmidt orthogonalization procedure in the context of the time-delayed system. We have studied in detail the mechanisms resulting in the generalized synchronization regime onset paying a great attention to the field where one positive Lyapunov exponent has already been become negative whereas the second one is a positive yet. We have found the intermittency here and studied its characteristics. To detect the laminar phase lengths the method based on a calculation of local Lyapunov exponents has been proposed. The efficiency of the method has been verified using the example of two unidirectionally coupled Rössler systems being in the band chaos regime. We have revealed the main characteristics of intermittency, i.e. the distribution of the laminar phase lengths and dependence of the mean length of the laminar phases on the criticality parameter, for all systems studied in the report. This work has been supported by the Russian President's Council grant for the state support of young Russian scientists (project MK-531.2018.2).

Keywords: complex topology of attractor, generalized synchronization, hyperchaos, Lyapunov exponents

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17201 Strengthening Service Delivery to Improving Cervical Cancer Screening in Southwestern Nigeria: A Pilot Project

Authors: Afolabi K. Esther, Kuye Tolulope, Babafemi, L. Olayemi, Omikunle Yemisi

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Background: Cervical cancer is a potentially preventable disease of public significance. All sexually active women are at risk of cervical cancer; however, the uptake and coverage are low in low-middle resource countries. Hence, the programme explored the feasibility of demonstrating an innovative and low-cost system approach to cervical cancer screening service delivery among reproductive-aged women in low–resource settings in Southwestern Nigeria. This was to promote the uptake and quality improvement of cervical cancer screening services. Methods: This study was an intervention project in three senatorial districts in Osun State that have primary, secondary and tertiary health facilities. The project was in three phases; Pre-intervention, Intervention, and Post-intervention. The study utilised the existing infrastructure, facilities and staff in project settings. The study population was nurse-midwives, community health workers and reproductive-aged women (30-49 years). The intervention phase entailed using innovative, culturally appropriate strategies to create awareness of cervical cancer and preventive health-seeking behaviour among women in the reproductive-aged group (30-49) years. Also, the service providers (community health workers, Nurses, and Midwives) were trained on screening methods and treatment of pre-cancerous lesions, and there was the provision of essential equipment and supplies for cervical cancer screening services at health facilities. Besides, advocacy and engagement were made with relevant stakeholders to integrate the cervical cancer screening services into related reproductive health services and greater allocation of resources. The expected results compared the pre and post-intervention using the baseline and process indicators and the effect of the intervention phase on screening coverage using a plausibility assessment design. The project lasted 12 months; visual Inspection with Acetic acid (VIA) screening for the women for six months and follow-up in 6 months for women receiving treatment. Results: The pre-intervention phase assessed baseline service delivery statistics in the previous 12 months drawn from the retrospective data collected as part of the routine monitoring and reporting systems. The uptake of cervical cancer screening services was low as the number of women screened in the previous 12 months was 156. Service personnel's competency level was fair (54%), and limited availability of essential equipment and supplies for cervical cancer screening services. At the post-intervention phase, the level of uptake had increased as the number of women screened was 1586 within six months in the study settings. This showed about a 100-%increase in the uptake of cervical cancer screening services compared with the baseline assessment. Also, the post-intervention level of competency of service delivery personnel had increased to 86.3%, which indicates quality improvement of the cervical cancer screening service delivery. Conclusion: the findings from the study have shown an effective approach to strengthening and improving cervical cancer screening service delivery in Southwestern Nigeria. Hence, the intervention promoted a positive attitude and health-seeking behaviour among the target population, significantly influencing the uptake of cervical cancer screening services.

Keywords: cervical cancer, screening, nigeria, health system strengthening

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17200 An Application of the Single Equation Regression Model

Authors: S. K. Ashiquer Rahman

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Recently, oil has become more influential in almost every economic sector as a key material. As can be seen from the news, when there are some changes in an oil price or OPEC announces a new strategy, its effect spreads to every part of the economy directly and indirectly. That’s a reason why people always observe the oil price and try to forecast the changes of it. The most important factor affecting the price is its supply which is determined by the number of wildcats drilled. Therefore, a study about the number of wellheads and other economic variables may give us some understanding of the mechanism indicated by the amount of oil supplies. In this paper, we will consider a relationship between the number of wellheads and three key factors: the price of the wellhead, domestic output, and GNP constant dollars. We also add trend variables in the models because the consumption of oil varies from time to time. Moreover, this paper will use an econometrics method to estimate parameters in the model, apply some tests to verify the result we acquire, and then conclude the model.

Keywords: price, domestic output, GNP, trend variable, wildcat activity

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17199 SkyCar Rapid Transit System: An Integrated Approach of Modern Transportation Solutions in the New Queen Elizabeth Quay, Perth, Western Australia

Authors: Arfanara Najnin, Michael W. Roach, Jr., Dr. Jianhong Cecilia Xia

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The SkyCar Rapid Transit System (SRT) is an innovative intelligent transport system for the sustainable urban transport system. This system will increase the urban area network connectivity and decrease urban area traffic congestion. The SRT system is designed as a suspended Personal Rapid Transit (PRT) system that travels under a guideway 5m above the ground. A driver-less passenger is via pod-cars that hang from slender beams supported by columns that replace existing lamp posts. The beams are setup in a series of interconnecting loops providing non-stop travel from beginning to end to assure journey time. The SRT forward movement is effected by magnetic motors built into the guideway. Passenger stops are at either at line level 5m above the ground or ground level via a spur guideway that curves off the main thoroughfare. The main objective of this paper is to propose an integrated Automated Transit Network (ATN) technology for the future intelligent transport system in the urban built environment. To fulfil the objective a 4D simulated model in the urban built environment has been proposed by using the concept of SRT-ATN system. The methodology for the design, construction and testing parameters of a Technology Demonstrator (TD) for proof of concept and a Simulator (S) has been demonstrated. The completed TD and S will provide an excellent proving ground for the next development stage, the SRT Prototype (PT) and Pilot System (PS). This paper covered by a 4D simulated model in the virtual built environment is to effectively show how the SRT-ATN system works. OpenSim software has been used to develop the model in a virtual environment, and the scenario has been simulated to understand and visualize the proposed SkyCar Rapid Transit Network model. The SkyCar system will be fabricated in a modular form which is easily transported. The system would be installed in increasingly congested city centers throughout the world, as well as in airports, tourist resorts, race tracks and other special purpose for the urban community. This paper shares the lessons learnt from the proposed innovation and provides recommendations on how to improve the future transport system in urban built environment. Safety and security of passengers are prime factors to be considered for this transit system. Design requirements to meet the safety needs to be part of the research and development phase of the project. Operational safety aspects would also be developed during this period. The vehicles, the track and beam systems and stations are the main components that need to be examined in detail for safety and security of patrons. Measures will also be required to protect columns adjoining intersections from errant vehicles in vehicular traffic collisions. The SkyCar Rapid Transit takes advantage of all current disruptive technologies; batteries, sensors and 4G/5G communication and solar energy technologies which will continue to reduce the costs and make the systems more profitable. SkyCar's energy consumption is extremely low compared to other transport systems.

Keywords: SkyCar, rapid transit, Intelligent Transport System (ITS), Automated Transit Network (ATN), urban built environment, 4D Visualization, smart city

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17198 Correlation Between Diastolic Function and Lower GLS in Hypertensive Patients

Authors: A. Kherraf, S. Ouarrak, L. Azzouzi, R. Habbal

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Introduction: Preserved LVEF heart failure is an important cause of mortality and morbidity in hypertensive patients. A strong correlation between impaired diastolic function and longitudinal systolic dysfunction. could have several explanations, first, the diastole is an energy dependent process, especially during its first phase, it also includes active systolic components during the phase of iso volumetric relaxation, in addition, the impairment of the intrinsic myocytic function is part of hypertensive pathology as evidenced by recent studies. METHODS AND MATERIALS: This work consists of performing in a series of 333 hypertensive patients (aged 25 to 75 years) a complete echocardiographic study, including LVEF by Simpson biplane method, the calculation of the indexed left ventricular mass, the analysis of the diastolic function, and finally, the study of the longitudinal deformation of the LV by the technique of speckletracking (calculation of the GLS). Patients with secondary hypertension, leaky or stenosing valve disease, arrhythmia, and a history of coronary insufficiency were excluded from this study. RESULTS: Of the 333 hypertensive patients, 225 patients (67.5%) had impaired diastolic function, of which 60 patients (18%) had high filling pressures. 49.39% had echocardigraphic HVG, Almost all of these patients (60 patients) had low GLS. There is a statistically very significant relationship between lower GLS and increased left ventricular filling pressures in hypertensive patients. These results suggest that increased filling pressures are closely associated with atrioventricular interaction in patients with hypertension, with a strong correlation with impairment of longitudinal systolic function and diastolic function CONCLUSION: Overall, a linear relationship is established between increased left ventricular mass, diastolic dysfunction, and longitudinal LV systolic dysfunction

Keywords: hypertension, diastolic function, left ventricle, heart failure

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17197 Building Information Modeling Applied for the Measurement of Water Footprint of Construction Supplies

Authors: Julio Franco

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Water is used, directly and indirectly, in all activities of the construction productive chain, making it a subject of worldwide relevance for sustainable development. The ongoing expansion of urban areas leads to a high demand for natural resources, which in turn cause significant environmental impacts. The present work proposes the application of BIM tools to assist the measurement of the water footprint (WF) of civil construction supplies. Data was inserted into the model as element properties, allowing them to be analyzed by element or in the whole model. The WF calculation was automated using parameterization in Autodesk Revit software. Parameterization was associated to the materials of each element in the model so that any changes in these elements directly alter the results of WF calculations. As a case study, we applied into a building project model to test the parameterized calculus of WF. Results show that the proposed parameterization successfully automated WF calculations according to design changes. We envision this tool to assist the measurement and rationalization of the environmental impact in terms of WF of construction projects.

Keywords: building information modeling, BIM, sustainable development, water footprint

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17196 Operation Cycle Model of ASz62IR Radial Aircraft Engine

Authors: M. Duk, L. Grabowski, P. Magryta

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Today's very important element relating to air transport is the environment impact issues. Nowadays there are no emissions standards for turbine and piston engines used in air transport. However, it should be noticed that the environmental effect in the form of exhaust gases from aircraft engines should be as small as possible. For this purpose, R&D centers often use special software to simulate and to estimate the negative effect of engine working process. For cooperation between the Lublin University of Technology and the Polish aviation company WSK "PZL-KALISZ" S.A., to achieve more effective operation of the ASz62IR engine, one of such tools have been used. The AVL Boost software allows to perform 1D simulations of combustion process of piston engines. ASz62IR is a nine-cylinder aircraft engine in a radial configuration. In order to analyze the impact of its working process on the environment, the mathematical model in the AVL Boost software have been made. This model contains, among others, model of the operation cycle of the cylinders. This model was based on a volume change in combustion chamber according to the reciprocating movement of a piston. The simplifications that all of the pistons move identically was assumed. The changes in cylinder volume during an operating cycle were specified. Those changes were important to determine the energy balance of a cylinder in an internal combustion engine which is fundamental for a model of the operating cycle. The calculations for cylinder thermodynamic state were based on the first law of thermodynamics. The change in the mass in the cylinder was calculated from the sum of inflowing and outflowing masses including: cylinder internal energy, heat from the fuel, heat losses, mass in cylinder, cylinder pressure and volume, blowdown enthalpy, evaporation heat etc. The model assumed that the amount of heat released in combustion process was calculated from the pace of combustion, using Vibe model. For gas exchange, it was also important to consider heat transfer in inlet and outlet channels because of much higher values there than for flow in a straight pipe. This results from high values of heat exchange coefficients and temperature coefficients near valves and valve seats. A Zapf modified model of heat exchange was used. To use the model with the flight scenarios, the impact of flight altitude on engine performance has been analyze. It was assumed that the pressure and temperature at the inlet and outlet correspond to the values resulting from the model for International Standard Atmosphere (ISA). Comparing this model of operation cycle with the others submodels of the ASz62IR engine, it could be noticed, that a full analysis of the performance of the engine, according to the ISA conditions, can be made. This work has been financed by the Polish National Centre for Research and Development, INNOLOT, under

Keywords: aviation propulsion, AVL Boost, engine model, operation cycle, aircraft engine

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17195 Probability-Based Damage Detection of Structures Using Model Updating with Enhanced Ideal Gas Molecular Movement Algorithm

Authors: M. R. Ghasemi, R. Ghiasi, H. Varaee

Abstract:

Model updating method has received increasing attention in damage detection structures based on measured modal parameters. Therefore, a probability-based damage detection (PBDD) procedure based on a model updating procedure is presented in this paper, in which a one-stage model-based damage identification technique based on the dynamic features of a structure is investigated. The presented framework uses a finite element updating method with a Monte Carlo simulation that considers the uncertainty caused by measurement noise. Enhanced ideal gas molecular movement (EIGMM) is used as the main algorithm for model updating. Ideal gas molecular movement (IGMM) is a multiagent algorithm based on the ideal gas molecular movement. Ideal gas molecules disperse rapidly in different directions and cover all the space inside. This is embedded in the high speed of molecules, collisions between them and with the surrounding barriers. In IGMM algorithm to accomplish the optimal solutions, the initial population of gas molecules is randomly generated and the governing equations related to the velocity of gas molecules and collisions between those are utilized. In this paper, an enhanced version of IGMM, which removes unchanged variables after specified iterations, is developed. The proposed method is implemented on two numerical examples in the field of structural damage detection. The results show that the proposed method can perform well and competitive in PBDD of structures.

Keywords: enhanced ideal gas molecular movement (EIGMM), ideal gas molecular movement (IGMM), model updating method, probability-based damage detection (PBDD), uncertainty quantification

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17194 Laser Registration and Supervisory Control of neuroArm Robotic Surgical System

Authors: Hamidreza Hoshyarmanesh, Hosein Madieh, Sanju Lama, Yaser Maddahi, Garnette R. Sutherland, Kourosh Zareinia

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This paper illustrates the concept of an algorithm to register specified markers on the neuroArm surgical manipulators, an image-guided MR-compatible tele-operated robot for microsurgery and stereotaxy. Two range-finding algorithms, namely time-of-flight and phase-shift, are evaluated for registration and supervisory control. The time-of-flight approach is implemented in a semi-field experiment to determine the precise position of a tiny retro-reflective moving object. The moving object simulates a surgical tool tip. The tool is a target that would be connected to the neuroArm end-effector during surgery inside the magnet bore of the MR imaging system. In order to apply flight approach, a 905-nm pulsed laser diode and an avalanche photodiode are utilized as the transmitter and receiver, respectively. For the experiment, a high frequency time to digital converter was designed using a field-programmable gate arrays. In the phase-shift approach, a continuous green laser beam with a wavelength of 530 nm was used as the transmitter. Results showed that a positioning error of 0.1 mm occurred when the scanner-target point distance was set in the range of 2.5 to 3 meters. The effectiveness of this non-contact approach exhibited that the method could be employed as an alternative for conventional mechanical registration arm. Furthermore, the approach is not limited by physical contact and extension of joint angles.

Keywords: 3D laser scanner, intraoperative MR imaging, neuroArm, real time registration, robot-assisted surgery, supervisory control

Procedia PDF Downloads 290
17193 Wear Resistance and Thermal Stability of Tungsten Boride Layers Deposited by Magnetron Sputtering

Authors: Justyna Chrzanowska, Jacek Hoffman, Dariusz Garbiec, Łukasz Kurpaska, Piotr Denis, Tomasz Moscicki, Zygmunt Szymanski

Abstract:

Tungsten and boron compounds belong to the group of superhard materials and its hardness could exceed 40 GPa. In this study, the properties of the tungsten boride (WB) layers deposited in magnetron sputtering process are investigated. The sputtering process occurred from specially prepared targets that were composed of boron and tungsten mixed in molar ratio of 2.5 or 4.5 and sintered in spark plasma sintering process. WB layers were deposited on silicon (100) and stainless steel 304 substrates at room temperature (RT) or in 570 °C. Layers deposited in RT and in elevated temperature varied considerably. Layers deposited in RT are amorphous and have low adhesion. In contrast, the layers deposited in 570 °C are crystalline and have good adhesion. All deposited layers have a hardness about 40 GPa. Moreover, the friction coefficient of crystalline layers is 0.22 and wear rate is about 0.67•10-6 mm3N-1m-1. After material characterization the WB layers were annealed in argon atmosphere in 1000 °C for 1 hour. On the basis of X-Ray Diffraction analysis, it has been noted that the crystalline layers are thermally stable and do not change their phase composition, whereas the amorphous layers change their phase composition. Moreover, after annealing, on the surface of WB layers some cracks were observed. It is probably connected with the differences of the thermal expansion between the layer and the substrate. Despite of the presence of cracks, the wear resistance of annealed layers is still higher than the wear resistance of uncoated substrate. The analysis of the structure and properties of tungsten boride layers lead to the discussion about the application area of this material.

Keywords: hard coatings, hard materials, magnetron sputtering, mechanical properties, tungsten boride

Procedia PDF Downloads 291
17192 Critically Sampled Hybrid Trigonometry Generalized Discrete Fourier Transform for Multistandard Receiver Platform

Authors: Temidayo Otunniyi

Abstract:

This paper presents a low computational channelization algorithm for the multi-standards platform using poly phase implementation of a critically sampled hybrid Trigonometry generalized Discrete Fourier Transform, (HGDFT). An HGDFT channelization algorithm exploits the orthogonality of two trigonometry Fourier functions, together with the properties of Quadrature Mirror Filter Bank (QMFB) and Exponential Modulated filter Bank (EMFB), respectively. HGDFT shows improvement in its implementation in terms of high reconfigurability, lower filter length, parallelism, and medium computational activities. Type 1 and type 111 poly phase structures are derived for real-valued HGDFT modulation. The design specifications are decimated critically and over-sampled for both single and multi standards receiver platforms. Evaluating the performance of oversampled single standard receiver channels, the HGDFT algorithm achieved 40% complexity reduction, compared to 34% and 38% reduction in the Discrete Fourier Transform (DFT) and tree quadrature mirror filter (TQMF) algorithm. The parallel generalized discrete Fourier transform (PGDFT) and recombined generalized discrete Fourier transform (RGDFT) had 41% complexity reduction and HGDFT had a 46% reduction in oversampling multi-standards mode. While in the critically sampled multi-standard receiver channels, HGDFT had complexity reduction of 70% while both PGDFT and RGDFT had a 34% reduction.

Keywords: software defined radio, channelization, critical sample rate, over-sample rate

Procedia PDF Downloads 152
17191 A Comparative Asessment of Some Algorithms for Modeling and Forecasting Horizontal Displacement of Ialy Dam, Vietnam

Authors: Kien-Trinh Thi Bui, Cuong Manh Nguyen

Abstract:

In order to simulate and reproduce the operational characteristics of a dam visually, it is necessary to capture the displacement at different measurement points and analyze the observed movement data promptly to forecast the dam safety. The accuracy of forecasts is further improved by applying machine learning methods to data analysis progress. In this study, the horizontal displacement monitoring data of the Ialy hydroelectric dam was applied to machine learning algorithms: Gaussian processes, multi-layer perceptron neural networks, and the M5-rules algorithm for modelling and forecasting of horizontal displacement of the Ialy hydropower dam (Vietnam), respectively, for analysing. The database which used in this research was built by collecting time series of data from 2006 to 2021 and divided into two parts: training dataset and validating dataset. The final results show all three algorithms have high performance for both training and model validation, but the MLPs is the best model. The usability of them are further investigated by comparison with a benchmark models created by multi-linear regression. The result show the performance which obtained from all the GP model, the MLPs model and the M5-Rules model are much better, therefore these three models should be used to analyze and predict the horizontal displacement of the dam.

Keywords: Gaussian processes, horizontal displacement, hydropower dam, Ialy dam, M5-Rules, multi-layer perception neural networks

Procedia PDF Downloads 219
17190 A Pedagogical Study of Computational Design in a Simulated Building Information Modeling-Cloud Environment

Authors: Jaehwan Jung, Sung-Ah Kim

Abstract:

Building Information Modeling (BIM) provides project stakeholders with various information about property and geometry of entire component as a 3D object-based parametric building model. BIM represents a set of Information and solutions that are expected to improve collaborative work process and quality of the building design. To improve collaboration among project participants, the BIM model should provide the necessary information to remote participants in real time and manage the information in the process. The purpose of this paper is to propose a process model that can apply effective architectural design collaborative work process in architectural design education in BIM-Cloud environment.

Keywords: BIM, cloud computing, collaborative design, digital design education

Procedia PDF Downloads 438
17189 LORA: A Learning Outcome Modelling Approach for Higher Education

Authors: Aqeel Zeid, Hasna Anees, Mohamed Adheeb, Mohamed Rifan, Kalpani Manathunga

Abstract:

To achieve constructive alignment in a higher education program, a clear set of learning outcomes must be defined. Traditional learning outcome definition techniques such as Bloom’s taxonomy are not written to be utilized by the student. This might be disadvantageous for students in student-centric learning settings where the students are expected to formulate their own learning strategies. To solve the problem, we propose the learning outcome relation and aggregation (LORA) model. To achieve alignment, we developed learning outcome, assessment, and resource authoring tools which help teachers to tag learning outcomes during creation. A pilot study was conducted with an expert panel consisting of experienced professionals in the education domain to evaluate whether the LORA model and tools present an improvement over the traditional methods. The panel unanimously agreed that the model and tools are beneficial and effective. Moreover, it helped them model learning outcomes in a more student centric and descriptive way.

Keywords: learning design, constructive alignment, Bloom’s taxonomy, learning outcome modelling

Procedia PDF Downloads 191
17188 Model of Application of Blockchain Technology in Public Finances

Authors: M. Vlahovic

Abstract:

This paper presents a model of public finances, which combines three concepts: participatory budgeting, crowdfunding and blockchain technology. Participatory budgeting is defined as a process in which community members decide how to spend a part of community’s budget. Crowdfunding is a practice of funding a project by collecting small monetary contributions from a large number of people via an Internet platform. Blockchain technology is a distributed ledger that enables efficient and reliable transactions that are secure and transparent. In this hypothetical model, the government or authorities on local/regional level would set up a platform where they would propose public projects to citizens. Citizens would browse through projects and support or vote for those which they consider justified and necessary. In return, they would be entitled to a tax relief in the amount of their monetary contribution. Since the blockchain technology enables tracking of transactions, it can be used to mitigate corruption, money laundering and lack of transparency in public finances. Models of its application have already been created for e-voting, health records or land registries. By presenting a model of application of blockchain technology in public finances, this paper takes into consideration the potential of blockchain technology to disrupt governments and make processes more democratic, secure, transparent and efficient. The framework for this paper consists of multiple streams of research, including key concepts of direct democracy, public finance (especially the voluntary theory of public finance), information and communication technology, especially blockchain technology and crowdfunding. The framework defines rules of the game, basic conditions for the implementation of the model, benefits, potential problems and development perspectives. As an oversimplified map of a new form of public finances, the proposed model identifies primary factors, that influence the possibility of implementation of the model, and that could be tracked, measured and controlled in case of experimentation with the model.

Keywords: blockchain technology, distributed ledger, participatory budgeting, crowdfunding, direct democracy, internet platform, e-government, public finance

Procedia PDF Downloads 155
17187 Assessment Power and Oscillation Damping Using the POD Controller and Proposed FOD Controller

Authors: Tohid Rahimi, Yahya Naderi, Babak Yousefi, Seyed Hossein Hoseini

Abstract:

Today’s modern interconnected power system is highly complex in nature. In this, one of the most important requirements during the operation of the electric power system is the reliability and security. Power and frequency oscillation damping mechanism improve the reliability. Because of power system stabilizer (PSS) low speed response against of major fault such as three phase short circuit, FACTs devise that can control the network condition in very fast time, are becoming popular. However, FACTs capability can be seen in a major fault present when nonlinear models of FACTs devise and power system equipment are applied. To realize this aim, the model of multi-machine power system with FACTs controller is developed in MATLAB/SIMULINK using Sim Power System (SPS) blockiest. Among the FACTs device, Static synchronous series compensator (SSSC) due to high speed changes its reactance characteristic inductive to capacitive, is effective power flow controller. Tuning process of controller parameter can be performed using different method. However, Genetic Algorithm (GA) ability tends to use it in controller parameter tuning process. In this paper, firstly POD controller is used to power oscillation damping. But in this station, frequency oscillation dos not has proper damping situation. Therefore, FOD controller that is tuned using GA is using that cause to damp out frequency oscillation properly and power oscillation damping has suitable situation.

Keywords: power oscillation damping (POD), frequency oscillation damping (FOD), Static synchronous series compensator (SSSC), Genetic Algorithm (GA)

Procedia PDF Downloads 479
17186 Facility Anomaly Detection with Gaussian Mixture Model

Authors: Sunghoon Park, Hank Kim, Jinwon An, Sungzoon Cho

Abstract:

Internet of Things allows one to collect data from facilities which are then used to monitor them and even predict malfunctions in advance. Conventional quality control methods focus on setting a normal range on a sensor value defined between a lower control limit and an upper control limit, and declaring as an anomaly anything falling outside it. However, interactions among sensor values are ignored, thus leading to suboptimal performance. We propose a multivariate approach which takes into account many sensor values at the same time. In particular Gaussian Mixture Model is used which is trained to maximize likelihood value using Expectation-Maximization algorithm. The number of Gaussian component distributions is determined by Bayesian Information Criterion. The negative Log likelihood value is used as an anomaly score. The actual usage scenario goes like a following. For each instance of sensor values from a facility, an anomaly score is computed. If it is larger than a threshold, an alarm will go off and a human expert intervenes and checks the system. A real world data from Building energy system was used to test the model.

Keywords: facility anomaly detection, gaussian mixture model, anomaly score, expectation maximization algorithm

Procedia PDF Downloads 277
17185 Developing an ANN Model to Predict Anthropometric Dimensions Based on Real Anthropometric Database

Authors: Waleed A. Basuliman, Khalid S. AlSaleh, Mohamed Z. Ramadan

Abstract:

Applying the anthropometric dimensions is considered one of the important factors when designing any human-machine system. In this study, the estimation of anthropometric dimensions has been improved by developing artificial neural network that aims to predict the anthropometric measurements of the male in Saudi Arabia. A total of 1427 Saudi males from age 6 to 60 participated in measuring twenty anthropometric dimensions. These anthropometric measurements are important for designing the majority of work and life applications in Saudi Arabia. The data were collected during 8 months from different locations in Riyadh City. Five of these dimensions were used as predictors variables (inputs) of the model, and the remaining fifteen dimensions were set to be the measured variables (outcomes). The hidden layers have been varied during the structuring stage, and the best performance was achieved with the network structure 6-25-15. The results showed that the developed Neural Network model was significantly able to predict the body dimensions for the population of Saudi Arabia. The network mean absolute percentage error (MAPE) and the root mean squared error (RMSE) were found 0.0348 and 3.225 respectively. The accuracy of the developed neural network was evaluated by compare the predicted outcomes with a multiple regression model. The ANN model performed better and resulted excellent correlation coefficients between the predicted and actual dimensions.

Keywords: artificial neural network, anthropometric measurements, backpropagation, real anthropometric database

Procedia PDF Downloads 582
17184 X-Ray Diffraction, Microstructure, and Mössbauer Studies of Nanostructured Materials Obtained by High-Energy Ball Milling

Authors: N. Boudinar, A. Djekoun, A. Otmani, B. Bouzabata, J. M. Greneche

Abstract:

High-energy ball milling is a solid-state powder processing technique that allows synthesizing a variety of equilibrium and non-equilibrium alloy phases starting from elemental powders. The advantage of this process technology is that the powder can be produced in large quantities and the processing parameters can be easily controlled, thus it is a suitable method for commercial applications. It can also be used to produce amorphous and nanocrystalline materials in commercially relevant amounts and is also amenable to the production of a variety of alloy compositions. Mechanical alloying (high-energy ball milling) provides an inter-dispersion of elements through a repeated cold welding and fracture of free powder particles; the grain size decreases to nano metric scale and the element mix together. Progressively, the concentration gradients disappear and eventually the elements are mixed at the atomic scale. The end products depend on many parameters such as the milling conditions and the thermodynamic properties of the milled system. Here, the mechanical alloying technique has been used to prepare nano crystalline Fe_50 and Fe_64 wt.% Ni alloys from powder mixtures. Scanning electron microscopy (SEM) with energy-dispersive, X-ray analyses and Mössbauer spectroscopy were used to study the mixing at nanometric scale. The Mössbauer Spectroscopy confirmed the ferromagnetic ordering and was use to calculate the distribution of hyperfin field. The Mössbauer spectrum for both alloys shows the existence of a ferromagnetic phase attributed to γ-Fe-Ni solid solution.

Keywords: nanocrystalline, mechanical alloying, X-ray diffraction, Mössbauer spectroscopy, phase transformations

Procedia PDF Downloads 438
17183 Gas-Phase Nondestructive and Environmentally Friendly Covalent Functionalization of Graphene Oxide Paper with Amines

Authors: Natalia Alzate-Carvajal, Diego A. Acevedo-Guzman, Victor Meza-Laguna, Mario H. Farias, Luis A. Perez-Rey, Edgar Abarca-Morales, Victor A. Garcia-Ramirez, Vladimir A. Basiuk, Elena V. Basiuk

Abstract:

Direct covalent functionalization of prefabricated free-standing graphene oxide paper (GOP) is considered as the only approach suitable for systematic tuning of thermal, mechanical and electronic characteristics of this important class of carbon nanomaterials. At the same time, the traditional liquid-phase functionalization protocols can compromise physical integrity of the paper-like material up to its total disintegration. To avoid such undesirable effects, we explored the possibility of employing an alternative, solvent-free strategy for facile and nondestructive functionalization of GOP with two representative aliphatic amines, 1-octadecylamine (ODA) and 1,12-diaminododecane (DAD), as well as with two aromatic amines, 1-aminopyrene (AP) and 1,5-diaminonaphthalene (DAN). The functionalization was performed under moderate heating at 150-180 °C in vacuum. Under such conditions, it proceeds through both amidation and epoxy ring opening reactions. Comparative characterization of pristine and amine-functionalized GOP mats was carried out by using Fourier-transform infrared, Raman, and X-ray photoelectron spectroscopy (XPS), thermogravimetric (TGA) and differential thermal analysis, scanning electron and atomic force microscopy (SEM and AFM, respectively). Besides that, we compared the stability in water, wettability, electrical conductivity and elastic (Young's) modulus of GOP mats before and after amine functionalization. The highest content of organic species was obtained in the case of GOP-ODA, followed by GOP-DAD, GOP-AP and GOP-DAN samples. The covalent functionalization increased mechanical and thermal stability of GOP, as well as its electrical conductivity. The magnitude of each effect depends on the particular chemical structure of amine employed, which allows for tuning a given GOP property. Morphological characterization by using SEM showed that, compared to pristine graphene oxide paper, amine-modified GOP mats become relatively ordered layered assemblies, in which individual GO sheets are organized in a near-parallel pattern. Financial support from the National Autonomous University of Mexico (grants DGAPA-IN101118 and IN200516) and from the National Council of Science and Technology of Mexico (CONACYT, grant 250655) is greatly appreciated. The authors also thank David A. Domínguez (CNyN of UNAM) for XPS measurements and Dr. Edgar Alvarez-Zauco (Faculty of Science of UNAM) for the opportunity to use TGA equipment.

Keywords: amines, covalent functionalization, gas-phase, graphene oxide paper

Procedia PDF Downloads 183
17182 Evolved Bat Algorithm Based Adaptive Fuzzy Sliding Mode Control with LMI Criterion

Authors: P.-W. Tsai, C.-Y. Chen, C.-W. Chen

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In this paper, the stability analysis of a GA-Based adaptive fuzzy sliding model controller for a nonlinear system is discussed. First, a nonlinear plant is well-approximated and described with a reference model and a fuzzy model, both involving FLC rules. Then, FLC rules and the consequent parameter are decided on via an Evolved Bat Algorithm (EBA). After this, we guarantee a new tracking performance inequality for the control system. The tracking problem is characterized to solve an eigenvalue problem (EVP). Next, an adaptive fuzzy sliding model controller (AFSMC) is proposed to stabilize the system so as to achieve good control performance. Lyapunov’s direct method can be used to ensure the stability of the nonlinear system. It is shown that the stability analysis can reduce nonlinear systems into a linear matrix inequality (LMI) problem. Finally, a numerical simulation is provided to demonstrate the control methodology.

Keywords: adaptive fuzzy sliding mode control, Lyapunov direct method, swarm intelligence, evolved bat algorithm

Procedia PDF Downloads 447
17181 Modeling the Impacts of Road Construction on Lands Values

Authors: Maha Almumaiz, Harry Evdorides

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Change in land value typically occurs when a new interurban road construction causes an increase in accessibility; this change in the adjacent lands values differs according to land characteristics such as geographic location, land use type, land area and sale time (appraisal time). A multiple regression model is obtained to predict the percent change in land value (CLV) based on four independent variables namely land distance from the constructed road, area of land, nature of land use and time from the works completion of the road. The random values of percent change in land value were generated using Microsoft Excel with a range of up to 35%. The trend of change in land value with the four independent variables was determined from the literature references. The statistical analysis and model building process has been made by using the IBM SPSS V23 software. The Regression model suggests, for lands that are located within 3 miles as the straight distance from the road, the percent CLV is between (0-35%) which is depending on many factors including distance from the constructed road, land use, land area and time from works completion of the new road.

Keywords: interurban road, land use types, new road construction, percent CLV, regression model

Procedia PDF Downloads 268