Search results for: error estimates
355 Real-Time Hybrid Simulation for a Tuned Liquid Column Damper Implementation
Authors: Carlos Riascos, Peter Thomson
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Real-time hybrid simulation (RTHS) is a modern cyber-physical technique used for the experimental evaluation of complex systems, that treats the system components with predictable behavior as a numerical substructure and the components that are difficult to model as an experimental substructure. Therefore it is an attractive method for evaluation of the response of civil structures under earthquake, wind and anthropic loads. Another practical application of RTHS is the evaluation of control systems, as these devices are often nonlinear and their characterization is an important step in the design of controllers with the desired performance. In this paper, the response of three-story shear frame controlled by a tuned liquid column damper (TLCD) and subject to base excitation is considered. Both passive and semi-active control strategies were implemented and are compared. While the passive TLCD achieved a reduction of 50% in the acceleration response of the main structure in comparison with the structure without control, the semi-active TLCD achieved a reduction of 70%, and was robust to variations in the dynamic properties of the main structure. In addition, a RTHS was implemented with the main structure modeled as a linear, time-invariant (LTI) system through a state space representation and the TLCD, with both control strategies, was evaluated on a shake table that reproduced the displacement of the virtual structure. Current assessment measures for RTHS were used to quantify the performance with parameters such as generalized amplitude, equivalent time delay between the target and measured displacement of the shake table, and energy error using the measured force, and prove that the RTHS described in this paper is an accurate method for the experimental evaluation of structural control systems.Keywords: structural control, hybrid simulation, tuned liquid column damper, semi-active sontrol strategy
Procedia PDF Downloads 289354 Evaluating Robustness of Conceptual Rainfall-runoff Models under Climate Variability in Northern Tunisia
Authors: H. Dakhlaoui, D. Ruelland, Y. Tramblay, Z. Bargaoui
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To evaluate the impact of climate change on water resources at the catchment scale, not only future projections of climate are necessary but also robust rainfall-runoff models that are able to be fairly reliable under changing climate conditions. This study aims at assessing the robustness of three conceptual rainfall-runoff models (GR4j, HBV and IHACRES) on five basins in Northern Tunisia under long-term climate variability. Their robustness was evaluated according to a differential split sample test based on a climate classification of the observation period regarding simultaneously precipitation and temperature conditions. The studied catchments are situated in a region where climate change is likely to have significant impacts on runoff and they already suffer from scarcity of water resources. They cover the main hydrographical basins of Northern Tunisia (High Medjerda, Zouaraâ, Ichkeul and Cap bon), which produce the majority of surface water resources in Tunisia. The streamflow regime of the basins can be considered as natural since these basins are located upstream from storage-dams and in areas where withdrawals are negligible. A 30-year common period (1970‒2000) was considered to capture a large spread of hydro-climatic conditions. The calibration was based on the Kling-Gupta Efficiency (KGE) criterion, while the evaluation of model transferability is performed according to the Nash-Suttfliff efficiency criterion and volume error. The three hydrological models were shown to have similar behaviour under climate variability. Models prove a better ability to simulate the runoff pattern when transferred toward wetter periods compared to the case when transferred to drier periods. The limits of transferability are beyond -20% of precipitation and +1.5 °C of temperature in comparison with the calibration period. The deterioration of model robustness could in part be explained by the climate dependency of some parameters.Keywords: rainfall-runoff modelling, hydro-climate variability, model robustness, uncertainty, Tunisia
Procedia PDF Downloads 286353 Transfer Function Model-Based Predictive Control for Nuclear Core Power Control in PUSPATI TRIGA Reactor
Authors: Mohd Sabri Minhat, Nurul Adilla Mohd Subha
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The 1MWth PUSPATI TRIGA Reactor (RTP) in Malaysia Nuclear Agency has been operating more than 35 years. The existing core power control is using conventional controller known as Feedback Control Algorithm (FCA). It is technically challenging to keep the core power output always stable and operating within acceptable error bands for the safety demand of the RTP. Currently, the system could be considered unsatisfactory with power tracking performance, yet there is still significant room for improvement. Hence, a new design core power control is very important to improve the current performance in tracking and regulating reactor power by controlling the movement of control rods that suit the demand of highly sensitive of nuclear reactor power control. In this paper, the proposed Model Predictive Control (MPC) law was applied to control the core power. The model for core power control was based on mathematical models of the reactor core, MPC, and control rods selection algorithm. The mathematical models of the reactor core were based on point kinetics model, thermal hydraulic models, and reactivity models. The proposed MPC was presented in a transfer function model of the reactor core according to perturbations theory. The transfer function model-based predictive control (TFMPC) was developed to design the core power control with predictions based on a T-filter towards the real-time implementation of MPC on hardware. This paper introduces the sensitivity functions for TFMPC feedback loop to reduce the impact on the input actuation signal and demonstrates the behaviour of TFMPC in term of disturbance and noise rejections. The comparisons of both tracking and regulating performance between the conventional controller and TFMPC were made using MATLAB and analysed. In conclusion, the proposed TFMPC has satisfactory performance in tracking and regulating core power for controlling nuclear reactor with high reliability and safety.Keywords: core power control, model predictive control, PUSPATI TRIGA reactor, TFMPC
Procedia PDF Downloads 231352 Healthcare Utilization and Costs of Specific Obesity Related Health Conditions in Alberta, Canada
Authors: Sonia Butalia, Huong Luu, Alexis Guigue, Karen J. B. Martins, Khanh Vu, Scott W. Klarenbach
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Obesity-related health conditions impose a substantial economic burden on payers due to increased healthcare use. Estimates of healthcare resource use and costs associated with obesity-related comorbidities are needed to inform policies and interventions targeting these conditions. Methods: Adults living with obesity were identified (a procedure-related body mass index code for class 2/3 obesity between 2012 and 2019 in Alberta, Canada; excluding those with bariatric surgery), and outcomes were compared over 1-year (2019/2020) between those who had and did not have specific obesity-related comorbidities. The probability of using a healthcare service (based on the odds ratio of a zero [OR-zero] cost) was compared; 95% confidence intervals (CI) were reported. Logistic regression and a generalized linear model with log link and gamma distribution were used for total healthcare cost comparisons ($CDN); cost ratios and estimated cost differences (95% CI) were reported. Potential socio-demographic and clinical confounders were adjusted for, and incremental cost differences were representative of a referent case. Results: A total of 220,190 adults living with obesity were included; 44% had hypertension, 25% had osteoarthritis, 24% had type-2 diabetes, 17% had cardiovascular disease, 12% had insulin resistance, 9% had chronic back pain, and 4% of females had polycystic ovarian syndrome (PCOS). The probability of hospitalization, ED visit, and ambulatory care was higher in those with a following obesity-related comorbidity versus those without: chronic back pain (hospitalization: 1.8-times [OR-zero: 0.57 [0.55/0.59]] / ED visit: 1.9-times [OR-zero: 0.54 [0.53/0.56]] / ambulatory care visit: 2.4-times [OR-zero: 0.41 [0.40/0.43]]), cardiovascular disease (2.7-times [OR-zero: 0.37 [0.36/0.38]] / 1.9-times [OR-zero: 0.52 [0.51/0.53]] / 2.8-times [OR-zero: 0.36 [0.35/0.36]]), osteoarthritis (2.0-times [OR-zero: 0.51 [0.50/0.53]] / 1.4-times [OR-zero: 0.74 [0.73/0.76]] / 2.5-times [OR-zero: 0.40 [0.40/0.41]]), type-2 diabetes (1.9-times [OR-zero: 0.54 [0.52/0.55]] / 1.4-times [OR-zero: 0.72 [0.70/0.73]] / 2.1-times [OR-zero: 0.47 [0.46/0.47]]), hypertension (1.8-times [OR-zero: 0.56 [0.54/0.57]] / 1.3-times [OR-zero: 0.79 [0.77/0.80]] / 2.2-times [OR-zero: 0.46 [0.45/0.47]]), PCOS (not significant / 1.2-times [OR-zero: 0.83 [0.79/0.88]] / not significant), and insulin resistance (1.1-times [OR-zero: 0.88 [0.84/0.91]] / 1.1-times [OR-zero: 0.92 [0.89/0.94]] / 1.8-times [OR-zero: 0.56 [0.54/0.57]]). After fully adjusting for potential confounders, the total healthcare cost ratio was higher in those with a following obesity-related comorbidity versus those without: chronic back pain (1.54-times [1.51/1.56]), cardiovascular disease (1.45-times [1.43/1.47]), osteoarthritis (1.36-times [1.35/1.38]), type-2 diabetes (1.30-times [1.28/1.31]), hypertension (1.27-times [1.26/1.28]), PCOS (1.08-times [1.05/1.11]), and insulin resistance (1.03-times [1.01/1.04]). Conclusions: Adults with obesity who have specific disease-related health conditions have a higher probability of healthcare use and incur greater costs than those without specific comorbidities; incremental costs are larger when other obesity-related health conditions are not adjusted for. In a specific referent case, hypertension was costliest (44% had this condition with an additional annual cost of $715 [$678/$753]). If these findings hold for the Canadian population, hypertension in persons with obesity represents an estimated additional annual healthcare cost of $2.5 billion among adults living with obesity (based on an adult obesity rate of 26%). Results of this study can inform decision making on investment in interventions that are effective in treating obesity and its complications.Keywords: administrative data, healthcare cost, obesity-related comorbidities, real world evidence
Procedia PDF Downloads 138351 Examining the Missing Feedback Link in Environmental Kuznets Curve Hypothesis
Authors: Apra Sinha
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The inverted U-shaped Environmental Kuznets curve (EKC) demonstrates(pollution-income relationship)that initially the pollution and environmental degradation surpass the level of income per capita; however this trend reverses since at the higher income levels, economic growth initiates environmental upgrading. However, what effect does increased environmental degradation has on growth is the missing feedback link which has not been addressed in the EKC hypothesis. This paper examines the missing feedback link in EKC hypothesis in Indian context by examining the casual association between fossil fuel consumption, carbon dioxide emissions and economic growth for India. Fossil fuel consumption here has been taken as a proxy of driver of economic growth. The casual association between the aforementioned variables has been analyzed using five interventions namely 1) urban development for which urbanization has been taken proxy 2) industrial development for which industrial value added has been taken proxy 3) trade liberalization for which sum of exports and imports as a share of GDP has been taken as proxy 4)financial development for which a)domestic credit to private sector and b)net foreign assets has been taken as proxies. The choice of interventions for this study has been done keeping in view the economic liberalization perspective of India. The main aim of the paper is to investigate the missing feedback link for Environmental Kuznets Curve Hypothesis before and after incorporating the intervening variables. The period of study is from 1971 to 2011 as it covers pre and post liberalization era in India. All the data has been taken from World Bank country level indicators. The Johansen and Juselius cointegration testing methodology and Error Correction based Granger causality have been applied on all the variables. The results clearly show that out of five interventions, only in two interventions the missing feedback link is being addressed. This paper can put forward significant policy implications for environment protection and sustainable development.Keywords: environmental Kuznets curve hypothesis, fossil fuel consumption, industrialization, trade liberalization, urbanization
Procedia PDF Downloads 240350 Determinants of Domestic Violence among Married Women Aged 15-49 Years in Sierra Leone by an Intimate Partner: A Cross-Sectional Study
Authors: Tesfaldet Mekonnen Estifanos, Chen Hui, Afewerki Weldezgi
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Background: Intimate partner violence (hereafter IPV) is a major global public health challenge that tortures and disables women in the place where they are ought to be most secure within their own families. The fact that the family unit is commonly viewed as a private circle, violent acts towards women remains undermined. There are limited research and knowledge about the influencing factors linked to IPV in Sierra Leone. This study, therefore, estimates the prevalence rate and the predicting factors associated with IPV. Methods: Data were taken from Sierra-Leone Demographic and Health Survey (SDHS, 2013): the first in its form to incorporate information on domestic violence. Multistage cluster sampling research design was used, and information was gathered by a standard questionnaire. A total of 5185 respondents selected were interviewed, out of whom 870 were never been in union, thus excluded. To analyze the two dependent variables: experience of IPV, ‘ever’ and 'last 12 months prior to the survey', a total of 4315 (currently or formerly married) and 4029 women (currently in union) were included respectively. These dependent variables were constructed from the three forms of violence namely physical, emotional and sexual. Data analysis was applied using SPSS version 23, comprising three-step process. First, descriptive statistics were used to show the frequency distribution of both the outcome and explanatory variables. Second, bivariate analysis adopting chi-square test was applied to assess the individual relationship between the outcome and explanatory variables. Third, multivariate logistic regression analysis was undertaken using hierarchical modeling strategy to identify the influence of the explanatory variables on the outcome variables. Odds ratio (OR) and 95% confidence interval (CI) were utilized to examine the association of the variables considering p-values less than 0.05 statistically significant. Results: The prevalence of lifetime IPV among ever married women was 48.4%, while 39.8% of those currently married experienced IPV in the previous year preceding the survey. Women having 1 to 4 and more than 5 number of ever born babies were almost certain to encounter lifetime IPV. However, women who own a property, and those who referenced 3-5 reasons for which wife-beating is acceptable were less probably to experience lifetime IPV. Attesting parental violence, partner’s dominant marital behavior, and women afraid of their partner were the variables related to both experience of IPV ‘ever’ and ‘the previous year prior to the survey’. Respondents who concur that wife-beating is sensible in certain situations and occupations under the professional category had diminished chances of revealing IPV in the year prior to the data collection. Conclusion: This study indicated that factors significantly correlated with IPV in Sierra-Leone are mostly linked with husband related factors specifically, marital controlling behaviors. Addressing IPV in Sierra-Leone requires joint efforts that target men raise awareness to address controlling behavior and empower security in affiliations.Keywords: husband behavior, married women, partner violence, Sierra Leone
Procedia PDF Downloads 125349 Radar Track-based Classification of Birds and UAVs
Authors: Altilio Rosa, Chirico Francesco, Foglia Goffredo
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In recent years, the number of Unmanned Aerial Vehicles (UAVs) has significantly increased. The rapid development of commercial and recreational drones makes them an important part of our society. Despite the growing list of their applications, these vehicles pose a huge threat to civil and military installations: detection, classification and neutralization of such flying objects become an urgent need. Radar is an effective remote sensing tool for detecting and tracking flying objects, but scenarios characterized by the presence of a high number of tracks related to flying birds make especially challenging the drone detection task: operator PPI is cluttered with a huge number of potential threats and his reaction time can be severely affected. Flying birds compared to UAVs show similar velocity, RADAR cross-section and, in general, similar characteristics. Building from the absence of a single feature that is able to distinguish UAVs and birds, this paper uses a multiple features approach where an original feature selection technique is developed to feed binary classifiers trained to distinguish birds and UAVs. RADAR tracks acquired on the field and related to different UAVs and birds performing various trajectories were used to extract specifically designed target movement-related features based on velocity, trajectory and signal strength. An optimization strategy based on a genetic algorithm is also introduced to select the optimal subset of features and to estimate the performance of several classification algorithms (Neural network, SVM, Logistic regression…) both in terms of the number of selected features and misclassification error. Results show that the proposed methods are able to reduce the dimension of the data space and to remove almost all non-drone false targets with a suitable classification accuracy (higher than 95%).Keywords: birds, classification, machine learning, UAVs
Procedia PDF Downloads 208348 Ruminal Fermentation of Biologically Active Nitrate- and Nitro-Containing Forages
Authors: Robin Anderson, David Nisbet
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Nitrate, 3-nitro-1-propionic acid (NPA) and 3-nitro-1-propanol (NPOH) are biologically active chemicals that can accumulate naturally in rangeland grasses forages consumed by grazing cattle, sheep and goats. While toxic to livestock if accumulations and amounts consumed are high enough, particularly in animals having no recent exposure to the forages, these chemicals are known to be potent inhibitors of methane-producing bacteria inhabiting the rumen. Consequently, there is interest in examining their potential use as anti-methanogenic compounds to decrease methane emissions by grazing ruminants. Presently, rumen microbes, collected freshly from a cannulated Holstein cow maintained on 50:50 corn based concentrate:alfalfa diet were mixed (10 mL fluid) in 18 x 150 mm crimp top tubes with 0.5 of high nitrate-containing barley (Hordeum vulgare; containing 272 µmol nitrate per g forage dry matter), and NPA- or NPOH- containing milkvetch forages (Astragalus canadensis and Astragalus miser containing 80 and 174 soluble µmol NPA or NPOH/g forage dry matter respectively). Incubations containing 0.5 g alfalfa (Medicago sativa) were used as controls. Tubes (3 per each respective forage) were capped and incubated anaerobically (using oxygen free carbon dioxide) for 24 h at 39oC after which time amounts of total gas produced were measured via volume displacement and headspace samples were analyzed by gas chromatography to determine concentrations of hydrogen and methane. Fluid samples were analyzed by gas chromatography to measure accumulations of fermentation acids. A completely randomized analysis of variance revealed that the nitrate-containing barley and both the NPA- and the NPOH-containing milkvetches significantly decreased methane production, by > 50%, when compared to methane produced by populations incubated similarly with alfalfa (70.4 ± 3.6 µmol/ml incubation fluid). Accumulations of hydrogen, which are typically increased when methane production is inhibited, by incubations with the nitrate-containing barley and the NPA- and NPOH-containing milkvetches did not differ from accumulations observed in the alfalfa controls (0.09 ± 0.04 µmol/mL incubation fluid). Accumulations of fermentation acids produced in the incubations containing the high-nitrate barley and the NPA- and NPOH-containing milkvetches likewise did not differ from accumulations observed in incubations containing alfalfa (123.5 ± 10.8, 36.0 ± 3.0, 17.1 ± 1.5, 3.5 ± 0.3, 2.3 ± 0.2, 2.2 ± 0.2 µmol/mL incubation fluid for acetate, propionate, butyrate, valerate, isobutyrate, and isovalerate, respectively). This finding indicates the microbial populations did not compensate for the decreased methane production via compensatory changes in production of fermentative acids. Stoichiometric estimation of fermentation balance revealed that > 77% of reducing equivalents generated during fermentation of the forages were recovered in fermentation products and the recoveries did not differ between the alfalfa incubations and those with the high-nitrate barley or the NPA- or NPOH-containing milkvetches. Stoichiometric estimates of amounts of hexose fermented similarly did not differ between the nitrate-, NPA and NPOH-containing incubations and those with the alfalfa, averaging 99.6 ± 37.2 µmol hexose consumed/mL of incubation fluid. These results suggest that forages containing nitrate, NPA or NPOH may be useful to reduce methane emissions of grazing ruminants provided risks of toxicity can be effectively managed.Keywords: nitrate, nitropropanol, nitropropionic acid, rumen methane emissions
Procedia PDF Downloads 116347 Mathematical Modelling of Drying Kinetics of Cantaloupe in a Solar Assisted Dryer
Authors: Melike Sultan Karasu Asnaz, Ayse Ozdogan Dolcek
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Crop drying, which aims to reduce the moisture content to a certain level, is a method used to extend the shelf life and prevent it from spoiling. One of the oldest food preservation techniques is open sunor shade drying. Even though this technique is the most affordable of all drying methods, there are some drawbacks such as contamination by insects, environmental pollution, windborne dust, and direct expose to weather conditions such as wind, rain, hail. However, solar dryers that provide a hygienic and controllable environment to preserve food and extend its shelf life have been developed and used to dry agricultural products. Thus, foods can be dried quickly without being affected by weather variables, and quality products can be obtained. This research is mainly devoted to investigating the modelling of drying kinetics of cantaloupe in a forced convection solar dryer. Mathematical models for the drying process should be defined to simulate the drying behavior of the foodstuff, which will greatly contribute to the development of solar dryer designs. Thus, drying experiments were conducted and replicated five times, and various data such as temperature, relative humidity, solar irradiation, drying air speed, and weight were instantly monitored and recorded. Moisture content of sliced and pretreated cantaloupe were converted into moisture ratio and then fitted against drying time for constructing drying curves. Then, 10 quasi-theoretical and empirical drying models were applied to find the best drying curve equation according to the Levenberg-Marquardt nonlinear optimization method. The best fitted mathematical drying model was selected according to the highest coefficient of determination (R²), and the mean square of the deviations (χ^²) and root mean square error (RMSE) criterial. The best fitted model was utilized to simulate a thin layer solar drying of cantaloupe, and the simulation results were compared with the experimental data for validation purposes.Keywords: solar dryer, mathematical modelling, drying kinetics, cantaloupe drying
Procedia PDF Downloads 118346 Molecular Topology and TLC Retention Behaviour of s-Triazines: QSRR Study
Authors: Lidija R. Jevrić, Sanja O. Podunavac-Kuzmanović, Strahinja Z. Kovačević
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Quantitative structure-retention relationship (QSRR) analysis was used to predict the chromatographic behavior of s-triazine derivatives by using theoretical descriptors computed from the chemical structure. Fundamental basis of the reported investigation is to relate molecular topological descriptors with chromatographic behavior of s-triazine derivatives obtained by reversed-phase (RP) thin layer chromatography (TLC) on silica gel impregnated with paraffin oil and applied ethanol-water (φ = 0.5-0.8; v/v). Retention parameter (RM0) of 14 investigated s-triazine derivatives was used as dependent variable while simple connectivity index different orders were used as independent variables. The best QSRR model for predicting RM0 value was obtained with simple third order connectivity index (3χ) in the second-degree polynomial equation. Numerical values of the correlation coefficient (r=0.915), Fisher's value (F=28.34) and root mean square error (RMSE = 0.36) indicate that model is statistically significant. In order to test the predictive power of the QSRR model leave-one-out cross-validation technique has been applied. The parameters of the internal cross-validation analysis (r2CV=0.79, r2adj=0.81, PRESS=1.89) reflect the high predictive ability of the generated model and it confirms that can be used to predict RM0 value. Multivariate classification technique, hierarchical cluster analysis (HCA), has been applied in order to group molecules according to their molecular connectivity indices. HCA is a descriptive statistical method and it is the most frequently used for important area of data processing such is classification. The HCA performed on simple molecular connectivity indices obtained from the 2D structure of investigated s-triazine compounds resulted in two main clusters in which compounds molecules were grouped according to the number of atoms in the molecule. This is in agreement with the fact that these descriptors were calculated on the basis of the number of atoms in the molecule of the investigated s-triazine derivatives.Keywords: s-triazines, QSRR, chemometrics, chromatography, molecular descriptors
Procedia PDF Downloads 386345 Knowledge, Attitude and Beliefs Towards Polypharmacy Amongst Older People Attending Family Medicine Clinic at the Aga Khan University Hospital, Nairobi, Kenya (AKUHN) Sub-Saharan Africa-Qualitative Study
Authors: Maureen Kamau, Gulnaz Mohamoud, Adelaide Lusambili, Njeri Nyanja
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Life expectancy has increased over the last century amongst older individuals, and in particular, those 60 years and over. The World Health Organization estimates that the world's population of persons over 60 years will rise to 22 per cent by the year 2050. Ageing is associated with increasing disability, multiple chronic conditions, and an increase in the use of health services. These multiple chronic conditions are managed with polypharmacy. Polypharmacy has numerous adverse effects including non-adherence, poor compliance to the various medications, reduced appetite, and risk of fall. Studies on polypharmacy and ageing are few and poorly understood especially in low and middle - income countries. The aim of this study was to explore the knowledge, attitudes and beliefs of older people towards polypharmacy. A qualitative study of 15 patients aged 60 years and above, taking more than five medications per day were conducted at the Aga Khan University using Semi-structured in-depth interviews. Three interviews were pilot interviews, and data analysis was performed on 12 interviews. Data were analyzed using NVIVO 12 software. A thematic qualitative analysis was carried out guided by Braun and Clarke (2006) framework. Themes identified; - knowledge of their co-morbidities and of the medication that older persons take, sources of information about medicines, and storage of the medication, experiences and attitudes of older patients towards polypharmacy both positive and negative, older peoples beliefs and their coping mechanisms with polypharmacy. The study participants had good knowledge on their multiple co-morbidities, and on the medication they took. The patients had positive attitudes towards medication as it enhanced their health and well-being, and enabled them to perform their activities of daily living. There was a strong belief among older patients that the medications were necessary for their health. All these factors enhanced compliance to the multiple medication. However, some older patients had negative attitudes due to the pill burden, side effects of the medication, and stigma associated with being ill. Cost of healthcare was a concern, with most of the patients interviewed relying on insurance to cover the cost of their medication. Older patients had accepted that the medication they were prescribed were necessary for their health, as it enabled them to complete their activities of daily living. Some concerns about the side effects of the medication arose, and brought about the need for patient education that would ensure that the patients are aware of the medications they take, and potential side effects. The effect that the COVID 19 pandemic had in the healthcare of the older patients was evident by the number of the older patients avoided coming to the hospital during the period of the pandemic. The relationship with the primary care physician and the older patients is an important one, especially in LMICs such as Kenya, as many of the older patients trusted the doctors wholeheartedly to make the best decision about their health and about their medication. Prescription review is important to avoid the use of potentially inappropriate medication.Keywords: polypharmacy, older patients, multiple chronic conditions, Kenya, Africa, qualitative study, indepth interviews, primary care
Procedia PDF Downloads 88344 Measurement of Ionospheric Plasma Distribution over Myanmar Using Single Frequency Global Positioning System Receiver
Authors: Win Zaw Hein, Khin Sandar Linn, Su Su Yi Mon, Yoshitaka Goto
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The Earth ionosphere is located at the altitude of about 70 km to several 100 km from the ground, and it is composed of ions and electrons called plasma. In the ionosphere, these plasma makes delay in GPS (Global Positioning System) signals and reflect in radio waves. The delay along the signal path from the satellite to the receiver is directly proportional to the total electron content (TEC) of plasma, and this delay is the largest error factor in satellite positioning and navigation. Sounding observation from the top and bottom of the ionosphere was popular to investigate such ionospheric plasma for a long time. Recently, continuous monitoring of the TEC using networks of GNSS (Global Navigation Satellite System) observation stations, which are basically built for land survey, has been conducted in several countries. However, in these stations, multi-frequency support receivers are installed to estimate the effect of plasma delay using their frequency dependence and the cost of multi-frequency support receivers are much higher than single frequency support GPS receiver. In this research, single frequency GPS receiver was used instead of expensive multi-frequency GNSS receivers to measure the ionospheric plasma variation such as vertical TEC distribution. In this measurement, single-frequency support ublox GPS receiver was used to probe ionospheric TEC. The location of observation was assigned at Mandalay Technological University in Myanmar. In the method, the ionospheric TEC distribution is represented by polynomial functions for latitude and longitude, and parameters of the functions are determined by least-squares fitting on pseudorange data obtained at a known location under an assumption of thin layer ionosphere. The validity of the method was evaluated by measurements obtained by the Japanese GNSS observation network called GEONET. The performance of measurement results using single-frequency of GPS receiver was compared with the results by dual-frequency measurement.Keywords: ionosphere, global positioning system, GPS, ionospheric delay, total electron content, TEC
Procedia PDF Downloads 127343 Artificial Neural Network Approach for Modeling and Optimization of Conidiospore Production of Trichoderma harzianum
Authors: Joselito Medina-Marin, Maria G. Serna-Diaz, Alejandro Tellez-Jurado, Juan C. Seck-Tuoh-Mora, Eva S. Hernandez-Gress, Norberto Hernandez-Romero, Iaina P. Medina-Serna
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Trichoderma harzianum is a fungus that has been utilized as a low-cost fungicide for biological control of pests, and it is important to determine the optimal conditions to produce the highest amount of conidiospores of Trichoderma harzianum. In this work, the conidiospore production of Trichoderma harzianum is modeled and optimized by using Artificial Neural Networks (AANs). In order to gather data of this process, 30 experiments were carried out taking into account the number of hours of culture (10 distributed values from 48 to 136 hours) and the culture humidity (70, 75 and 80 percent), obtained as a response the number of conidiospores per gram of dry mass. The experimental results were used to develop an iterative algorithm to create 1,110 ANNs, with different configurations, starting from one to three hidden layers, and every hidden layer with a number of neurons from 1 to 10. Each ANN was trained with the Levenberg-Marquardt backpropagation algorithm, which is used to learn the relationship between input and output values. The ANN with the best performance was chosen in order to simulate the process and be able to maximize the conidiospores production. The obtained ANN with the highest performance has 2 inputs and 1 output, three hidden layers with 3, 10 and 10 neurons in each layer, respectively. The ANN performance shows an R2 value of 0.9900, and the Root Mean Squared Error is 1.2020. This ANN predicted that 644175467 conidiospores per gram of dry mass are the maximum amount obtained in 117 hours of culture and 77% of culture humidity. In summary, the ANN approach is suitable to represent the conidiospores production of Trichoderma harzianum because the R2 value denotes a good fitting of experimental results, and the obtained ANN model was used to find the parameters to produce the biggest amount of conidiospores per gram of dry mass.Keywords: Trichoderma harzianum, modeling, optimization, artificial neural network
Procedia PDF Downloads 148342 Economic Valuation of Emissions from Mobile Sources in the Urban Environment of Bogotá
Authors: Dayron Camilo Bermudez Mendoza
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Road transportation is a significant source of externalities, notably in terms of environmental degradation and the emission of pollutants. These emissions adversely affect public health, attributable to criteria pollutants like particulate matter (PM2.5 and PM10) and carbon monoxide (CO), and also contribute to climate change through the release of greenhouse gases, such as carbon dioxide (CO2). It is, therefore, crucial to quantify the emissions from mobile sources and develop a methodological framework for their economic valuation, aiding in the assessment of associated costs and informing policy decisions. The forthcoming congress will shed light on the externalities of transportation in Bogotá, showcasing methodologies and findings from the construction of emission inventories and their spatial analysis within the city. This research focuses on the economic valuation of emissions from mobile sources in Bogotá, employing methods like hedonic pricing and contingent valuation. Conducted within the urban confines of Bogotá, the study leverages demographic, transportation, and emission data sourced from the Mobility Survey, official emission inventories, and tailored estimates and measurements. The use of hedonic pricing and contingent valuation methodologies facilitates the estimation of the influence of transportation emissions on real estate values and gauges the willingness of Bogotá's residents to invest in reducing these emissions. The findings are anticipated to be instrumental in the formulation and execution of public policies aimed at emission reduction and air quality enhancement. In compiling the emission inventory, innovative data sources were identified to determine activity factors, including information from automotive diagnostic centers and used vehicle sales websites. The COPERT model was utilized to ascertain emission factors, requiring diverse inputs such as data from the national transit registry (RUNT), OpenStreetMap road network details, climatological data from the IDEAM portal, and Google API for speed analysis. Spatial disaggregation employed GIS tools and publicly available official spatial data. The development of the valuation methodology involved an exhaustive systematic review, utilizing platforms like the EVRI (Environmental Valuation Reference Inventory) portal and other relevant sources. The contingent valuation method was implemented via surveys in various public settings across the city, using a referendum-style approach for a sample of 400 residents. For the hedonic price valuation, an extensive database was developed, integrating data from several official sources and basing analyses on the per-square meter property values in each city block. The upcoming conference anticipates the presentation and publication of these results, embodying a multidisciplinary knowledge integration and culminating in a master's thesis.Keywords: economic valuation, transport economics, pollutant emissions, urban transportation, sustainable mobility
Procedia PDF Downloads 48341 A Cooperative Signaling Scheme for Global Navigation Satellite Systems
Authors: Keunhong Chae, Seokho Yoon
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Recently, the global navigation satellite system (GNSS) such as Galileo and GPS is employing more satellites to provide a higher degree of accuracy for the location service, thus calling for a more efficient signaling scheme among the satellites used in the overall GNSS network. In that the network throughput is improved, the spatial diversity can be one of the efficient signaling schemes; however, it requires multiple antenna that could cause a significant increase in the complexity of the GNSS. Thus, a diversity scheme called the cooperative signaling was proposed, where the virtual multiple-input multiple-output (MIMO) signaling is realized with using only a single antenna in the transmit satellite of interest and with modeling the neighboring satellites as relay nodes. The main drawback of the cooperative signaling is that the relay nodes receive the transmitted signal at different time instants, i.e., they operate in an asynchronous way, and thus, the overall performance of the GNSS network could degrade severely. To tackle the problem, several modified cooperative signaling schemes were proposed; however, all of them are difficult to implement due to a signal decoding at the relay nodes. Although the implementation at the relay nodes could be simpler to some degree by employing the time-reversal and conjugation operations instead of the signal decoding, it would be more efficient if we could implement the operations of the relay nodes at the source node having more resources than the relay nodes. So, in this paper, we propose a novel cooperative signaling scheme, where the data signals are combined in a unique way at the source node, thus obviating the need of the complex operations such as signal decoding, time-reversal and conjugation at the relay nodes. The numerical results confirm that the proposed scheme provides the same performance in the cooperative diversity and the bit error rate (BER) as the conventional scheme, while reducing the complexity at the relay nodes significantly. Acknowledgment: This work was supported by the National GNSS Research Center program of Defense Acquisition Program Administration and Agency for Defense Development.Keywords: global navigation satellite network, cooperative signaling, data combining, nodes
Procedia PDF Downloads 273340 Entrepreneurship Education: A Panacea for Entrepreneurial Intention of University Undergraduates in Ogun State, Nigeria
Authors: Adedayo Racheal Agbonna
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The rising level of graduate unemployment in Nigeria has brought about the introduction of entrepreneurship education as a career option for self–reliance and self-employment. Sequel to this, it is important to have an understanding of the determining factors of entrepreneurial intention. Therefore this research empirically investigated the influence of entrepreneurship education on entrepreneurial intention of undergraduate students of selected universities in Ogun State, Nigeria. The study is significant to researchers, university policy makers, and the government. Survey research design was adopted in the study. The population consisted of 17,659 final year undergraduate students universities in Ogun State. The study adopted stratified and random sampling technique. The table of sample size determination was used to determine the sample size for this study at 95% confidence level and 5% margin error to arrive at a sample size of 1877 respondents. The elements of population were 400 level students of the selected universities. A structured questionnaire titled 'Entrepreneurship Education and students’ Entrepreneurial intention' was administered. The result of the reliability test had the following values 0.716, 0.907 and 0.949 for infrastructure, perceived university support, and entrepreneurial intention respectively. In the same vein, from the construct validity test, the following values were obtained 0.711, 0.663 and 0.759 for infrastructure, perceived university support and entrepreneurial intention respectively. Findings of this study revealed that each of the entrepreneurship education variables significantly affected intention University infrastructure B= -1.200, R²=0.679, F (₁,₁₈₇₅) = 3958.345, P < 0.05) Perceived University Support B= -1.027, R²=0.502, F(₁,₁₈₇₅) = 1924.612, P < 0.05). The perception of respondents in public university and private university on entrepreneurship education have a statistically significant difference [F(₁,₁₈₇₅) = 134.614, p < 0.05) α F(₁,₁₈₇₅) = 363.439]. The study concluded that entrepreneurship education positively influenced entrepreneurial intention of undergraduate students in Ogun State, Nigeria. Also, university infrastructure and perceived university support have negative and significant effect on entrepreneurial intention. The study recommended that to promote entrepreneurial intention of university undergraduate students, infrastructures and the university support that can arouse entrepreneurial intention of students should be put in place.Keywords: entrepreneurship education, entrepreneurial intention, perceived university support, university infrastructure
Procedia PDF Downloads 222339 Fully Coupled Porous Media Model
Authors: Nia Mair Fry, Matthew Profit, Chenfeng Li
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This work focuses on the development and implementation of a fully implicit-implicit, coupled mechanical deformation and porous flow, finite element software tool. The fully implicit software accurately predicts classical fundamental analytical solutions such as the Terzaghi consolidation problem. Furthermore, it can capture other analytical solutions less well known in the literature, such as Gibson’s sedimentation rate problem and Coussy’s problems investigating wellbore stability for poroelastic rocks. The mechanical volume strains are transferred to the porous flow governing equation in an implicit framework. This will overcome some of the many current industrial issues, which use explicit solvers for the mechanical governing equations and only implicit solvers on the porous flow side. This can potentially lead to instability and non-convergence issues in the coupled system, plus giving results with an accountable degree of error. The specification of a fully monolithic implicit-implicit coupled porous media code sees the solution of both seepage-mechanical equations in one matrix system, under a unified time-stepping scheme, which makes the problem definition much easier. When using an explicit solver, additional input such as the damping coefficient and mass scaling factor is required, which are circumvented with a fully implicit solution. Further, improved accuracy is achieved as the solution is not dependent on predictor-corrector methods for the pore fluid pressure solution, but at the potential cost of reduced stability. In testing of this fully monolithic porous media code, there is the comparison of the fully implicit coupled scheme against an existing staggered explicit-implicit coupled scheme solution across a range of geotechnical problems. These cases include 1) Biot coefficient calculation, 2) consolidation theory with Terzaghi analytical solution, 3) sedimentation theory with Gibson analytical solution, and 4) Coussy well-bore poroelastic analytical solutions.Keywords: coupled, implicit, monolithic, porous media
Procedia PDF Downloads 130338 Aerial Photogrammetry-Based Techniques to Rebuild the 30-Years Landform Changes of a Landslide-Dominated Watershed in Taiwan
Authors: Yichin Chen
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Taiwan is an island characterized by an active tectonics and high erosion rates. Monitoring the dynamic landscape of Taiwan is an important issue for disaster mitigation, geomorphological research, and watershed management. Long-term and high spatiotemporal landform data is essential for quantifying and simulating the geomorphological processes and developing warning systems. Recently, the advances in unmanned aerial vehicle (UAV) and computational photogrammetry technology have provided an effective way to rebuild and monitor the topography changes in high spatio-temporal resolutions. This study rebuilds the 30-years landform change in the Aiyuzi watershed in 1986-2017 by using the aerial photogrammetry-based techniques. The Aiyuzi watershed, located in central Taiwan and has an area of 3.99 Km², is famous for its frequent landslide and debris flow disasters. This study took the aerial photos by using UAV and collected multi-temporal historical, stereo photographs, taken by the Aerial Survey Office of Taiwan’s Forestry Bureau. To rebuild the orthoimages and digital surface models (DSMs), Pix4DMapper, a photogrammetry software, was used. Furthermore, to control model accuracy, a set of ground control points was surveyed by using eGPS. The results show that the generated DSMs have the ground sampling distance (GSD) of ~10 cm and ~0.3 cm from the UAV’s and historical photographs, respectively, and vertical error of ~1 m. By comparing the DSMs, there are many deep-seated landslides (with depth over 20 m) occurred on the upstream in the Aiyuzi watershed. Even though a large amount of sediment is delivered from the landslides, the steep main channel has sufficient capacity to transport sediment from the channel and to erode the river bed to ~20 m in depth. Most sediments are transported to the outlet of watershed and deposits on the downstream channel. This case study shows that UAV and photogrammetry technology are useful for topography change monitoring effectively.Keywords: aerial photogrammetry, landslide, landform change, Taiwan
Procedia PDF Downloads 149337 Development of an Optimised, Automated Multidimensional Model for Supply Chains
Authors: Safaa H. Sindi, Michael Roe
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This project divides supply chain (SC) models into seven Eras, according to the evolution of the market’s needs throughout time. The five earliest Eras describe the emergence of supply chains, while the last two Eras are to be created. Research objectives: The aim is to generate the two latest Eras with their respective models that focus on the consumable goods. Era Six contains the Optimal Multidimensional Matrix (OMM) that incorporates most characteristics of the SC and allocates them into four quarters (Agile, Lean, Leagile, and Basic SC). This will help companies, especially (SMEs) plan their optimal SC route. Era Seven creates an Automated Multidimensional Model (AMM) which upgrades the matrix of Era six, as it accounts for all the supply chain factors (i.e. Offshoring, sourcing, risk) into an interactive system with Heuristic Learning that helps larger companies and industries to select the best SC model for their market. Methodologies: The data collection is based on a Fuzzy-Delphi study that analyses statements using Fuzzy Logic. The first round of Delphi study will contain statements (fuzzy rules) about the matrix of Era six. The second round of Delphi contains the feedback given from the first round and so on. Preliminary findings: both models are applicable, Matrix of Era six reduces the complexity of choosing the best SC model for SMEs by helping them identify the best strategy of Basic SC, Lean, Agile and Leagile SC; that’s tailored to their needs. The interactive heuristic learning in the AMM of Era seven will help mitigate error and aid large companies to identify and re-strategize the best SC model and distribution system for their market and commodity, hence increasing efficiency. Potential contributions to the literature: The problematic issue facing many companies is to decide which SC model or strategy to incorporate, due to the many models and definitions developed over the years. This research simplifies this by putting most definition in a template and most models in the Matrix of era six. This research is original as the division of SC into Eras, the Matrix of Era six (OMM) with Fuzzy-Delphi and Heuristic Learning in the AMM of Era seven provides a synergy of tools that were not combined before in the area of SC. Additionally the OMM of Era six is unique as it combines most characteristics of the SC, which is an original concept in itself.Keywords: Leagile, automation, heuristic learning, supply chain models
Procedia PDF Downloads 382336 The Effect of Extensive Mosquito Migration on Dengue Control as Revealed by Phylogeny of Dengue Vector Aedes aegypti
Authors: M. D. Nirmani, K. L. N. Perera, G. H. Galhena
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Dengue has become one of the most important arbo-viral disease in all tropical and subtropical regions of the world. Aedes aegypti, is the principal vector of the virus, vary in both epidemiological and behavioral characteristics, which could be finely measured through DNA sequence comparison at their population level. Such knowledge in the population differences can assist in implementation of effective vector control strategies allowing to make estimates of the gene flow and adaptive genomic changes, which are important predictors of the spread of Wolbachia infection or insecticide resistance. As such, this study was undertaken to investigate the phylogenetic relationships of Ae. aegypti from Galle and Colombo, Sri Lanka, based on the ribosomal protein region which spans between two exons, in order to understand the geographical distribution of genetically distinct mosquito clades and its impact on mosquito control measures. A 320bp DNA region spanning from 681-930 bp, corresponding to the ribosomal protein, was sequenced in 62 Ae. aegypti larvae collected from Galle (N=30) and Colombo (N=32), Sri Lanka. The sequences were aligned using ClustalW and the haplotypes were determined with DnaSP 5.10. Phylogenetic relationships among haplotypes were constructed using the maximum likelihood method under Tamura 3 parameter model in MEGA 7.0.14 including three previously reported sequences of Australian (N=2) and Brazilian (N=1) Ae. aegypti. The bootstrap support was calculated using 1000 replicates and the tree was rooted using Aedes notoscriptus (GenBank accession No. KJ194101). Among all sequences, nineteen different haplotypes were found among which five haplotypes were shared between 80% of mosquitoes in the two populations. Seven haplotypes were unique to each of the population. Phylogenetic tree revealed two basal clades and a single derived clade. All observed haplotypes of the two Ae. aegypti populations were distributed in all the three clades, indicating a lack of genetic differentiation between populations. The Brazilian Ae. aegypti haplotype and one of the Australian haplotypes were grouped together with the Sri Lankan basal haplotype in the same basal clade, whereas the other Australian haplotype was found in the derived clade. Phylogram showed that Galle and Colombo Ae. aegypti populations are highly related to each other despite the large geographic distance (129 Km) indicating a substantial genetic similarity between them. This may have probably arisen from passive migration assisted by human travelling and trade through both land and water as the two areas are bordered by the sea. In addition, studied Sri Lankan mosquito populations were closely related to Australian and Brazilian samples. Probably this might have caused by shipping industry between the three countries as all of them are fully or partially enclosed by sea. For example, illegal fishing boats migrating to Australia by sea is perhaps a good mean of transportation of all life stages of mosquitoes from Sri Lanka. These findings indicate that extensive mosquito migrations occur between populations not only within the country, but also among other countries in the world which might be a main barrier to the successful vector control measures.Keywords: Aedes aegypti, dengue control, extensive mosquito migration, haplotypes, phylogeny, ribosomal protein
Procedia PDF Downloads 176335 The Bidirectional Effect between Parental Burnout and the Child’s Internalized and/or Externalized Behaviors
Authors: Aline Woine, Moïra Mikolajczak, Virginie Dardier, Isabelle Roskam
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Background information: Becoming a parent is said to be the happiest event one can ever experience in one’s life. This popular (and almost absolute) truth–which no reasonable and decent human being would ever dare question on pain of being singled out as a bad parent–contrasts with the nuances that reality offers. Indeed, while many parents do thrive in their parenting role, some others falter and become progressively overwhelmed by their parenting role, ineluctably caught in a spiral of exhaustion. Parental burnout (henceforth PB) sets in when parental demands (stressors) exceed parental resources. While it is now generally acknowledged that PB affects the parent’s behavior in terms of neglect and violence toward their offspring, little is known about the impact that the syndrome might have on the children’s internalized (anxious and depressive symptoms, somatic complaints, etc.) and/or externalized (irritability, violence, aggressiveness, conduct disorder, oppositional disorder, etc.) behaviors. Furthermore, at the time of writing, to our best knowledge, no research has yet tested the reverse effect, namely, that of the child's internalized and/or externalized behaviors on the onset and/or maintenance of parental burnout symptoms. Goals and hypotheses: The present pioneering research proposes to fill an important gap in the existing literature related to PB by investigating the bidirectional effect between PB and the child’s internalized and/or externalized behaviors. Relying on a cross-lagged longitudinal study with three waves of data collection (4 months apart), our study tests a transactional model with bidirectional and recursive relations between observed variables and at the three waves, as well as autoregressive paths and cross-sectional correlations. Methods: As we write this, wave-two data are being collected via Qualtrics, and we expect a final sample of about 600 participants composed of French-speaking (snowball sample) and English-speaking (Prolific sample) parents. Structural equation modeling is employed using Stata version 17. In order to retain as much statistical power as possible, we use all available data and therefore apply the maximum likelihood with a missing value (mlmv) as the method of estimation to compute the parameter estimates. To limit (in so far is possible) the shared method variance bias in the evaluation of the child’s behavior, the study relies on a multi-informant evaluation approach. Expected results: We expect our three-wave longitudinal study to show that PB symptoms (measured at T1) raise the occurrence/intensity of the child’s externalized and/or internalized behaviors (measured at T2 and T3). We further expect the child’s occurrence/intensity of externalized and/or internalized behaviors (measured at T1) to augment the risk for PB (measured at T2 and T3). Conclusion: Should our hypotheses be confirmed, our results will make an important contribution to the understanding of both PB and children’s behavioral issues, thereby opening interesting theoretical and clinical avenues.Keywords: exhaustion, structural equation modeling, cross-lagged longitudinal study, violence and neglect, child-parent relationship
Procedia PDF Downloads 64334 The Chinese Inland-Coastal Inequality: The Role of Human Capital and the Crisis Watershed
Authors: Iacopo Odoardi, Emanuele Felice, Dario D'Ingiullo
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We investigate the role of human capital in the Chinese inland-coastal inequality and how the consequences of the 2007-2008 crisis may induce China to refocus its development path on human capital. We compare panel data analyses for two periods for the richer/coastal and the relatively poor/inland provinces. Considering the rapid evolution of the Chinese economy and the changes forced by the international crisis, we wonder if these events can lead to rethinking local development paths, fostering greater attention on the diffusion of higher education. We expect that the consequences on human capital may, in turn, have consequences on the inland/coastal dualism. The focus on human capital is due to the fact that the growing differences between inland and coastal areas can be explained by the different local endowments. In this respect, human capital may play a major role and should be thoroughly investigated. To assess the extent to which human capital has an effect on economic growth, we consider a fixed-effects model where differences among the provinces are considered parametric shifts in the regression equation. Data refer to the 31 Chinese provinces for the periods 1998-2008 and 2009-2017. Our dependent variable is the annual variation of the provincial gross domestic product (GDP) at the prices of the previous year. Among our regressors, we include two proxies of advanced human capital and other known factors affecting economic development. We are aware of the problem of conceptual endogeneity of variables related to human capital with respect to GDP; we adopt an instrumental variable approach (two-stage least squares) to avoid inconsistent estimates. Our results suggest that the economic strengths that influenced the Chinese take-off and the dualism are confirmed in the first period. These results gain relevance in comparison with the second period. An evolution in local economic endowments is taking place: first, although human capital can have a positive effect on all provinces after the crisis, not all types of advanced education have a direct economic effect; second, the development path of the inland area is changing, with an evolution towards more productive sectors which can favor higher returns to human capital. New strengths (e.g., advanced education, transport infrastructures) could be useful to foster development paths of inland-coastal desirable convergence, especially by favoring the poorer provinces. Our findings suggest that in all provinces, human capital can be useful to promote convergence in growth paths, even if investments in tertiary education seem to have a negative role, most likely due to the inability to exploit the skills of highly educated workers. Furthermore, we observe important changes in the economic characteristics of the less developed internal provinces. These findings suggest an evolution towards more productive economic sectors, a greater ability to exploit both investments in fixed capital and the available infrastructures. All these aspects, if connected with the improvement in the returns to human capital (at least at the secondary level), lead us to assume a better reaction (i.e., resilience) of the less developed provinces to the crisis effects.Keywords: human capital, inland-coastal inequality, Great Recession, China
Procedia PDF Downloads 195333 Effectiveness of Prehabilitation on Improving Emotional and Clinical Recovery of Patients Undergoing Open Heart Surgeries
Authors: Fatma Ahmed, Heba Mostafa, Bassem Ramdan, Azza El-Soussi
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Background: World Health Organization stated that by 2020 cardiac disease will be the number one cause of death worldwide and estimates that 25 million people per year will suffer from heart disease. Cardiac surgery is considered an effective treatment for severe forms of cardiovascular diseases that cannot be treated by medical treatment or cardiac interventions. In spite of the benefits of cardiac surgery, it is considered a major stressful experience for patients who are candidate for surgery. Prehabilitation can decrease incidences of postoperative complications as it prepares patients for surgical stress through enhancing their defenses to meet the demands of surgery. When patients anticipate the postoperative sequence of events, they will prepare themselves to act certain behaviors, identify their roles and actively participate in their own recovery, therefore, anxiety levels are decreased and functional capacity is enhanced. Prehabilitation programs can comprise interventions that include physical exercise, psychological prehabilitation, nutritional optimization and risk factor modification. Physical exercises are associated with improvements in the functioning of the various physiological systems, reflected in increased functional capacity, improved cardiac and respiratory functions and make patients fit for surgical intervention. Prehabilitation programs should also prepare patients psychologically in order to cope with stress, anxiety and depression associated with postoperative pain, fatigue, limited ability to perform the usual activities of daily living through acting in a healthy manner. Notwithstanding the benefits of psychological preparations, there are limited studies which investigated the effect of psychological prehabilitation to confirm its effect on psychological, quality of life and physiological outcomes of patients who had undergone cardiac surgery. Aim of the study: The study aims to determine the effect of prehabilitation interventions on outcomes of patients undergoing cardiac surgeries. Methods: Quasi experimental study design was used to conduct this study. Sixty eligible and consenting patients were recruited and divided into two groups: control and intervention group (30 participants in each). One tool namely emotional, physiological, clinical, cognitive and functional capacity outcomes of prehabilitation intervention assessment tool was utilized to collect the data of this study. Results: Data analysis showed significant improvement in patients' emotional state, physiological and clinical outcomes (P < 0.000) with the use of prehabilitation interventions. Conclusions: Cardiac prehabilitation in the form of providing information about surgery, circulation exercise, deep breathing exercise, incentive spirometer training and nutritional education implemented daily by patients scheduled for elective open heart surgery one week before surgery have been shown to improve patients' emotional state, physiological and clinical outcomes.Keywords: emotional recovery, clinical recovery, coronary artery bypass grafting patients, prehabilitation
Procedia PDF Downloads 195332 Pavement Management for a Metropolitan Area: A Case Study of Montreal
Authors: Luis Amador Jimenez, Md. Shohel Amin
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Pavement performance models are based on projections of observed traffic loads, which makes uncertain to study funding strategies in the long run if history does not repeat. Neural networks can be used to estimate deterioration rates but the learning rate and momentum have not been properly investigated, in addition, economic evolvement could change traffic flows. This study addresses both issues through a case study for roads of Montreal that simulates traffic for a period of 50 years and deals with the measurement error of the pavement deterioration model. Travel demand models are applied to simulate annual average daily traffic (AADT) every 5 years. Accumulated equivalent single axle loads (ESALs) are calculated from the predicted AADT and locally observed truck distributions combined with truck factors. A back propagation Neural Network (BPN) method with a Generalized Delta Rule (GDR) learning algorithm is applied to estimate pavement deterioration models capable of overcoming measurement errors. Linear programming of lifecycle optimization is applied to identify M&R strategies that ensure good pavement condition while minimizing the budget. It was found that CAD 150 million is the minimum annual budget to good condition for arterial and local roads in Montreal. Montreal drivers prefer the use of public transportation for work and education purposes. Vehicle traffic is expected to double within 50 years, ESALS are expected to double the number of ESALs every 15 years. Roads in the island of Montreal need to undergo a stabilization period for about 25 years, a steady state seems to be reached after.Keywords: pavement management system, traffic simulation, backpropagation neural network, performance modeling, measurement errors, linear programming, lifecycle optimization
Procedia PDF Downloads 452331 DNA Methylation Score Development for In utero Exposure to Paternal Smoking Using a Supervised Machine Learning Approach
Authors: Cristy Stagnar, Nina Hubig, Diana Ivankovic
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The epigenome is a compelling candidate for mediating long-term responses to environmental effects modifying disease risk. The main goal of this research is to develop a machine learning-based DNA methylation score, which will be valuable in delineating the unique contribution of paternal epigenetic modifications to the germline impacting childhood health outcomes. It will also be a useful tool in validating self-reports of nonsmoking and in adjusting epigenome-wide DNA methylation association studies for this early-life exposure. Using secondary data from two population-based methylation profiling studies, our DNA methylation score is based on CpG DNA methylation measurements from cord blood gathered from children whose fathers smoked pre- and peri-conceptually. Each child’s mother and father fell into one of three class labels in the accompanying questionnaires -never smoker, former smoker, or current smoker. By applying different machine learning algorithms to the accessible resource for integrated epigenomic studies (ARIES) sub-study of the Avon longitudinal study of parents and children (ALSPAC) data set, which we used for training and testing of our model, the best-performing algorithm for classifying the father smoker and mother never smoker was selected based on Cohen’s κ. Error in the model was identified and optimized. The final DNA methylation score was further tested and validated in an independent data set. This resulted in a linear combination of methylation values of selected probes via a logistic link function that accurately classified each group and contributed the most towards classification. The result is a unique, robust DNA methylation score which combines information on DNA methylation and early life exposure of offspring to paternal smoking during pregnancy and which may be used to examine the paternal contribution to offspring health outcomes.Keywords: epigenome, health outcomes, paternal preconception environmental exposures, supervised machine learning
Procedia PDF Downloads 179330 Resisting Adversarial Assaults: A Model-Agnostic Autoencoder Solution
Authors: Massimo Miccoli, Luca Marangoni, Alberto Aniello Scaringi, Alessandro Marceddu, Alessandro Amicone
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The susceptibility of deep neural networks (DNNs) to adversarial manipulations is a recognized challenge within the computer vision domain. Adversarial examples, crafted by adding subtle yet malicious alterations to benign images, exploit this vulnerability. Various defense strategies have been proposed to safeguard DNNs against such attacks, stemming from diverse research hypotheses. Building upon prior work, our approach involves the utilization of autoencoder models. Autoencoders, a type of neural network, are trained to learn representations of training data and reconstruct inputs from these representations, typically minimizing reconstruction errors like mean squared error (MSE). Our autoencoder was trained on a dataset of benign examples; learning features specific to them. Consequently, when presented with significantly perturbed adversarial examples, the autoencoder exhibited high reconstruction errors. The architecture of the autoencoder was tailored to the dimensions of the images under evaluation. We considered various image sizes, constructing models differently for 256x256 and 512x512 images. Moreover, the choice of the computer vision model is crucial, as most adversarial attacks are designed with specific AI structures in mind. To mitigate this, we proposed a method to replace image-specific dimensions with a structure independent of both dimensions and neural network models, thereby enhancing robustness. Our multi-modal autoencoder reconstructs the spectral representation of images across the red-green-blue (RGB) color channels. To validate our approach, we conducted experiments using diverse datasets and subjected them to adversarial attacks using models such as ResNet50 and ViT_L_16 from the torch vision library. The autoencoder extracted features used in a classification model, resulting in an MSE (RGB) of 0.014, a classification accuracy of 97.33%, and a precision of 99%.Keywords: adversarial attacks, malicious images detector, binary classifier, multimodal transformer autoencoder
Procedia PDF Downloads 101329 Border Security: Implementing the “Memory Effect” Theory in Irregular Migration
Authors: Iliuta Cumpanasu, Veronica Oana Cumpanasu
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This paper focuses on studying the conjunction between the new emerged theory of “Memory Effect” in Irregular Migration and Related Criminality and the notion of securitization, and its impact on border management, bringing about a scientific advancement in the field by identifying the patterns corresponding to the linkage of the two concepts, for the first time, and developing a theoretical explanation, with respect to the effects of the non-military threats on border security. Over recent years, irregular migration has experienced a significant increase worldwide. The U.N.'s refugee agency reports that the number of displaced people is at its highest ever - surpassing even post-World War II numbers when the world was struggling to come to terms with the most devastating event in history. This is also the fresh reality within the core studied coordinate, the Balkan Route of Irregular Migration, which starts from Asia and Africa and continues to Turkey, Greece, North Macedonia or Bulgaria, Serbia, and ends in Romania, where thousands of migrants find themselves in an irregular situation concerning their entry to the European Union, with its important consequences concerning the related criminality. The data from the past six years was collected by making use of semi-structured interviews with experts in the field of migration and desk research within some organisations involved in border security, pursuing the gathering of genuine insights from the aforementioned field, which was constantly addressed the existing literature and subsequently subjected to the mixed methods of analysis, including the use of the Vector Auto-Regression estimates model. Thereafter, the analysis of the data followed the processes and outcomes in Grounded Theory, and a new Substantive Theory emerged, explaining how the phenomena of irregular migration and cross-border criminality are the decisive impetus for implementing the concept of securitization in border management by using the proposed pattern. The findings of the study are therefore able to capture an area that has not yet benefitted from a comprehensive approach in the scientific community, such as the seasonality, stationarity, dynamics, predictions, or the pull and push factors in Irregular Migration, also highlighting how the recent ‘Pandemic’ interfered with border security. Therefore, the research uses an inductive revelatory theoretical approach which aims at offering a new theory in order to explain a phenomenon, triggering a practically handy contribution for the scientific community, research institutes or Academia and also usefulness to organizational practitioners in the field, among which UN, IOM, UNHCR, Frontex, Interpol, Europol, or national agencies specialized in border security. The scientific outcomes of this study were validated on June 30, 2021, when the author defended his dissertation for the European Joint Master’s in Strategic Border Management, a two years prestigious program supported by the European Commission and Frontex Agency and a Consortium of six European Universities and is currently one of the research objectives of his pending PhD research at the West University Timisoara.Keywords: migration, border, security, memory effect
Procedia PDF Downloads 80328 Levels of CTX1 in Premenopausal Osteoporotic Women Study Conducted in Khyberpuktoonkhwa Province, Pakistan
Authors: Mehwish Durrani, Rubina Nazli, Muhammad Abubakr, Muhammad Shafiq
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Objectives: To evaluate the high socio-economic status, urbanization, and decrease ambulation can lead to early osteoporosis in women reporting from Peshawar region. Study Design: Descriptive cross-sectional study was done. Sample size was 100 subjects, using 30% proportion of osteoporosis, 95% confidence level, and 9% margin of error under WHO software for sample size determination. Place and Duration of study: This study was carried out in the tertiary referral health care facilities of Peshawar viz PGMI Hayatabad Medical Complex, Peshawar, Khyber Pakhtunkhwa Province, Pakistan. Ethical approval for the study was taken from the Institutional Ethical Research board (IERD) at Post Graduate Medical Institute, Hayatabad Medical Complex, and Peshawar.The study was done in six months time period. Patients and Methods: Levels of CTX1 as a marker of bone degradation in radiographically assessed perimenopausal women was determined. These females were randomly selected and screened for osteoporosis. Hemoglobin in gm/dl, ESR by Westergren method as millimeter in 1 hour, Serum Ca mg/dl, Serum alkaline Phosphatase international units per liter radiographic grade of osteoporosis according to Singh index as 1-6 and CTX 1 level in pg/ml. Results: High levels of CTX1 was observed in perimenopausal osteoporotic women which were radiographically diagnosed as osteoporotic patients. The High socio-economic class also predispose to osteoporosis. Decrease ambulation another risk factor showed significant association with the increased levels of CTX1. Conclusion: The results of this study propose that minimum ambulation and high socioeconomic class both had significance association with the increase levels of serum CTX1, which in turn will lead to osteoporosis and to its complications.Keywords: osteoporosis, CTX1, perimenopausal women, Hayatabad Medical Complex, Khyberpuktoonkhwa
Procedia PDF Downloads 324327 Fault Tolerant and Testable Designs of Reversible Sequential Building Blocks
Authors: Vishal Pareek, Shubham Gupta, Sushil Chandra Jain
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With increasing high-speed computation demand the power consumption, heat dissipation and chip size issues are posing challenges for logic design with conventional technologies. Recovery of bit loss and bit errors is other issues that require reversibility and fault tolerance in the computation. The reversible computing is emerging as an alternative to conventional technologies to overcome the above problems and helpful in a diverse area such as low-power design, nanotechnology, quantum computing. Bit loss issue can be solved through unique input-output mapping which require reversibility and bit error issue require the capability of fault tolerance in design. In order to incorporate reversibility a number of combinational reversible logic based circuits have been developed. However, very few sequential reversible circuits have been reported in the literature. To make the circuit fault tolerant, a number of fault model and test approaches have been proposed for reversible logic. In this paper, we have attempted to incorporate fault tolerance in sequential reversible building blocks such as D flip-flop, T flip-flop, JK flip-flop, R-S flip-flop, Master-Slave D flip-flop, and double edge triggered D flip-flop by making them parity preserving. The importance of this proposed work lies in the fact that it provides the design of reversible sequential circuits completely testable for any stuck-at fault and single bit fault. In our opinion our design of reversible building blocks is superior to existing designs in term of quantum cost, hardware complexity, constant input, garbage output, number of gates and design of online testable D flip-flop have been proposed for the first time. We hope our work can be extended for building complex reversible sequential circuits.Keywords: parity preserving gate, quantum computing, fault tolerance, flip-flop, sequential reversible logic
Procedia PDF Downloads 536326 Early Prediction of Diseases in a Cow for Cattle Industry
Authors: Ghufran Ahmed, Muhammad Osama Siddiqui, Shahbaz Siddiqui, Rauf Ahmad Shams Malick, Faisal Khan, Mubashir Khan
Abstract:
In this paper, a machine learning-based approach for early prediction of diseases in cows is proposed. Different ML algos are applied to extract useful patterns from the available dataset. Technology has changed today’s world in every aspect of life. Similarly, advanced technologies have been developed in livestock and dairy farming to monitor dairy cows in various aspects. Dairy cattle monitoring is crucial as it plays a significant role in milk production around the globe. Moreover, it has become necessary for farmers to adopt the latest early prediction technologies as the food demand is increasing with population growth. This highlight the importance of state-ofthe-art technologies in analyzing how important technology is in analyzing dairy cows’ activities. It is not easy to predict the activities of a large number of cows on the farm, so, the system has made it very convenient for the farmers., as it provides all the solutions under one roof. The cattle industry’s productivity is boosted as the early diagnosis of any disease on a cattle farm is detected and hence it is treated early. It is done on behalf of the machine learning output received. The learning models are already set which interpret the data collected in a centralized system. Basically, we will run different algorithms on behalf of the data set received to analyze milk quality, and track cows’ health, location, and safety. This deep learning algorithm draws patterns from the data, which makes it easier for farmers to study any animal’s behavioral changes. With the emergence of machine learning algorithms and the Internet of Things, accurate tracking of animals is possible as the rate of error is minimized. As a result, milk productivity is increased. IoT with ML capability has given a new phase to the cattle farming industry by increasing the yield in the most cost-effective and time-saving manner.Keywords: IoT, machine learning, health care, dairy cows
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