Search results for: background noise statistical modeling

Authors: Jamerson Felipe Pereira Lima, Jeane Cecília Bezerra de Melo

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The difficulty and cost related to obtaining of protein tertiary structure information through experimental methods, such as X-ray crystallography or NMR spectroscopy, helped raising the development of computational methods to do so. An approach used in these last is prediction of tridimensional structure based in the residue chain, however, this has been proved an NP-hard problem, due to the complexity of this process, explained by the Levinthal paradox. An alternative solution is the prediction of intermediary structures, such as the secondary structure of the protein. Artificial Intelligence methods, such as Bayesian statistics, artificial neural networks (ANN), support vector machines (SVM), among others, were used to predict protein secondary structure. Due to its good results, artificial neural networks have been used as a standard method to predict protein secondary structure. Recent published methods that use this technique, in general, achieved a Q3 accuracy between 75% and 83%, whereas the theoretical accuracy limit for protein prediction is 88%. Alternatively, to achieve better results, support vector machines prediction methods have been developed. The statistical evaluation of methods that use different AI techniques, such as ANNs and SVMs, for example, is not a trivial problem, since different training sets, validation techniques, as well as other variables can influence the behavior of a prediction method. In this study, we propose a prediction method based on artificial neural networks, which is then compared with a selected SVM method. The chosen SVM protein secondary structure prediction method is the one proposed by Huang in his work Extracting Physico chemical Features to Predict Protein Secondary Structure (2013). The developed ANN method has the same training and testing process that was used by Huang to validate his method, which comprises the use of the CB513 protein data set and three-fold cross-validation, so that the comparative analysis of the results can be made comparing directly the statistical results of each method.

Keywords: artificial neural networks, protein secondary structure, protein structure prediction, support vector machines

Procedia PDF Downloads 624

Authors: Dimitri Bacco, Arianna Trentini, Fabiana Scotto, Flavio Rovere, Daniele Foscoli, Cinzia Para, Paolo Veronesi, Silvia Sandrini, Claudia Zigola, Michela Comandini, Marilena Montalti, Marco Zamagni, Vanes Poluzzi

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The Po Valley, in the north of Italy, is one of the most polluted areas in Europe. The air quality of the area is linked not only to anthropic activities but also to its geographical characteristics and stagnant weather conditions with frequent inversions, especially in the cold season. Even the coastal areas present high values of particulate matter (PM10 and PM2.5) because the area closed between the Adriatic Sea and the Apennines does not favor the dispersion of air pollutants. The aim of the present work was to identify the main sources of particulate matter in Rimini, a tourist city in northern Italy. Two sampling campaigns were carried out in 2018, one in winter (60 days) and one in summer (30 days), in 4 sites: an urban background, a city hotspot, a suburban background, and a rural background. The samples are characterized by the concentration of the ionic composition of the particulates and of the main a hydro-sugars, in particular levoglucosan, a marker of the biomass burning, because one of the most important anthropogenic sources in the area, both in the winter and surprisingly even in the summer, is the biomass burning. Furthermore, three sampling points were chosen in order to maximize the contribution of a specific biomass source: a point in a residential area (domestic cooking and domestic heating), a point in the agricultural area (weed fires), and a point in the tourist area (restaurant cooking). In these sites, the analyzes were enriched with the quantification of the carbonaceous component (organic and elemental carbon) and with measurement of the particle number concentration and aerosol size distribution (6 - 600 nm). The results showed a very significant impact of the combustion of biomass due to domestic heating in the winter period, even though many intense peaks were found attributable to episodic wood fires. In the summer season, however, an appreciable signal was measured linked to the combustion of biomass, although much less intense than in winter, attributable to domestic cooking activities. Further interesting results were the verification of the total absence of sea salt's contribution in the particulate with the lower diameter (PM2.5), and while in the PM10, the contribution becomes appreciable only in particular wind conditions (high wind from north, north-east). Finally, it is interesting to note that in a small town, like Rimini, in summer, the traffic source seems to be even more relevant than that measured in a much larger city (Bologna) due to tourism.

Keywords: aerosol, biomass burning, seacoast, urban area

Procedia PDF Downloads 136

Authors: Alireza Hashemi

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In recent decades, language teaching methodology has undergone significant changes due to the advent of computers and the growth of educational software. French language education has also benefited from these developments, and various software has been produced to facilitate the learning of this language. However, the question arises whether these software programs meet the educational needs of Iranian learners, particularly in Semnan Province. The aim of this study is to evaluate the efficiency and effectiveness of French language educational software for learners in Semnan Province, considering educational, cultural, and technical criteria. In this study, content analysis and performance evaluation methods were used to examine the educational software ‘Français Facile’. This software was evaluated based on criteria such as teaching methods, cultural compatibility, and technical features. To collect data, standardized questionnaires and semi-structured interviews with learners in Semnan Province were used. Additionally, the SPSS statistical software was employed for quantitative data analysis, and the thematic analysis method was used for qualitative data. The results indicated that the ‘Français Facile’ software has strengths such as providing diverse educational content and an interactive learning environment. However, some weaknesses include the lack of alignment of educational content with the learning culture of learners in Semnan Province and technical issues in software execution. Statistical data showed that 65% of learners were satisfied with the educational content, but 55% reported issues related to cultural alignment with their needs. This study indicates that to enhance the efficiency of French language educational software, there is a need to localize educational content and improve technical infrastructure. Producing locally adapted educational software can improve the quality of language learning and increase the motivation of learners in Semnan Province. This research emphasizes the importance of understanding the cultural and educational needs of learners in the development of educational software and recommends that developers of educational software pay special attention to these aspects.

Keywords: educational software, French language, Iran, learners in Semnan province

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Authors: Ebrahim Ghasemi Ardi, Ai Bing Yu, Run Yu Yang

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Current study is aimed to develop an available in-house discrete element method (DEM) code and link it with direct breakage event. So, it became possible to determine the particle breakage and then its fragments size distribution, simultaneous with DEM simulation. It directly applies the particle breakage inside the DEM computation algorithm and if any breakage happens the original particle is replaced with daughters. In this way, the calculation will be followed based on a new updated particles list which is very similar to the real grinding environment. To validate developed model, a grinding ball impacting an unconfined particle bed was simulated. Since considering an entire ball mill would be too computationally demanding, this method provided a simplified environment to test the model. Accordingly, a representative volume of the ball mill was simulated inside a box, which could emulate media (ball)–powder bed impacts in a ball mill and during particle bed impact tests. Mono, binary and ternary particle beds were simulated to determine the effects of granular composition on breakage kinetics. The results obtained from the DEM simulations showed a reduction in the specific breakage rate for coarse particles in binary mixtures. The origin of this phenomenon, commonly known as cushioning or decelerated breakage in dry milling processes, was explained by the DEM simulations. Fine particles in a particle bed increase mechanical energy loss, and reduce and distribute interparticle forces thereby inhibiting the breakage of the coarse component. On the other hand, the specific breakage rate of fine particles increased due to contacts associated with coarse particles. Such phenomenon, known as acceleration, was shown to be less significant, but should be considered in future attempts to accurately quantify non-linear breakage kinetics in the modeling of dry milling processes.

Keywords: particle bed, breakage models, breakage kinetic, discrete element method

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Authors: Ismaila Oladunni Muhammed, Adegbenga Raphael Ashiru

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Construction industry has been attributed to be the engine growth of Nigerian economic and infrastructural development. It promotes infrastructural development and grows an average output of Nigerian Gross Domestic Profit. However, from this great prospect, yearly reports show that consistent accidents on construction sites in Zamfara State has affected a substantial number of workers as they become temporarily or permanently disabled, thereby making many construction sites a death trap. This posed a great threat to the industry’s sustainability, de- motivate workers from working in the industry, and further have negative impact on the economy as well. It is as a result of high construction site accident currently experiencing in Zamfara state that this research was carried out to appraise the sustainability of health and safety of construction workers on sites. The proper practice and compliance to Construction Health and safety laws are very vital to the output and growth of Zamfara State construction sector. However, a quantitative approach was adopted to justify the aforesaid statement which will provide a broader understanding of the study. Descriptive statistical analysis was obtained through Statistical Package for the Social Sciences (SPSS Version 20). Furthermore, the findings from the research highlighted that the performance and output of construction workers on construction sites depends on the proper practice of health and safety. The research findings also recommended ways to enhance employers and employee’s compliance with existing laws guiding health and safety on Zamfara State construction sites. Nevertheless, the purpose of the paper is to appraise the sustainability of Health and Safety on Zamfara State construction sites. This study further provided thorough information for resolving challenges of construction sites accidents to improve construction firm productivity and also ensured construction worker’s safety on site.

Keywords: construction industry, health and safety regulations, causes of accident, construction safety practices

Procedia PDF Downloads 216

Authors: Saied Farham-Nia, Alireza Ghaffari-Hadigheh

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Game theory is a mathematical tool to study the behaviors of a rational and strategic decision-makers, that analyze existing equilibrium in interest conflict situation and provides an appropriate mechanisms for cooperation between two or more player. Game theory is applicable for any strategic and interest conflict situation in politics, management and economics, sociology and etc. Real worlds’ decisions are usually made in the state of indeterminacy and the players often are lack of the information about the other players’ payoffs or even his own, which leads to the games in uncertain environments. When historical data for decision parameters distribution estimation is unavailable, we may have no choice but to use expertise belief degree, which represents the strength with that we believe the event will happen. To deal with belief degrees, we have use uncertainty theory which is introduced and developed by Liu based on normality, duality, subadditivity and product axioms to modeling personal belief degree. As we know, the personal belief degree heavily depends on the personal knowledge concerning the event and when personal knowledge changes, cause changes in the belief degree too. Uncertainty theory not only theoretically is self-consistent but also is the best among other theories for modeling belief degree on practical problem. In this attempt, we primarily reintroduced Expected Utility Function in uncertainty environment according to uncertainty theory axioms to extract payoffs. Then, we employed Nash Equilibrium to investigate the solutions. For more practical issues, Stackelberg leader-follower Game and Bertrand Game, as a benchmark models are discussed. Compared to existing articles in the similar topics, the game models and solution concepts introduced in this article can be a framework for problems in an uncertain competitive situation based on experienced expert’s belief degree.

Keywords: game theory, uncertainty theory, belief degree, uncertain expected value, Nash equilibrium

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Authors: Kanchan Mondal, Dasharath Koulage, Dattatray Manerikar, Asmita Ghate

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This paper presents an additive reliability model using warranty data and Finite Element Analysis (FEA) data. Warranty data for any product gives insight to its underlying issues. This is often used by Reliability Engineers to build prediction model to forecast failure rate of parts. But there is one major limitation in using warranty data for prediction. Warranty periods constitute only a small fraction of total lifetime of a product, most of the time it covers only the infant mortality and useful life zone of a bathtub curve. Predicting with warranty data alone in these cases is not generally provide results with desired accuracy. Failure rate of a mechanical part is driven by random issues initially and wear-out or usage related issues at later stages of the lifetime. For better predictability of failure rate, one need to explore the failure rate behavior at wear out zone of a bathtub curve. Due to cost and time constraints, it is not always possible to test samples till failure, but FEA-Fatigue analysis can provide the failure rate behavior of a part much beyond warranty period in a quicker time and at lesser cost. In this work, the authors proposed an Additive Weibull Model, which make use of both warranty and FEA fatigue analysis data for predicting failure rates. It involves modeling of two data sets of a part, one with existing warranty claims and other with fatigue life data. Hazard rate base Weibull estimation has been used for the modeling the warranty data whereas S-N curved based Weibull parameter estimation is used for FEA data. Two separate Weibull models’ parameters are estimated and combined to form the proposed Additive Weibull Model for prediction.

Keywords: bathtub curve, fatigue, FEA, reliability, warranty, Weibull

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Authors: Xavier Lorang, Ahmadali Tahmasebimoradi, Chetra Mang, Sylvain Girard

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The additive manufacturing processes (e.g. selective laser melting) allow us to produce lattice structures which have less weight, higher impact absorption capacity, and better thermal exchange property compared to the classical structures. Unfortunately, geometric imperfections (defects) in the lattice structures are by-products results of the manufacturing process. These imperfections decrease the lifetime and the strength of the lattice structures and alternate their mechanical responses. The objective of the paper is to present a simulation strategy which allows us to take into account the effect of the geometric imperfections on the mechanical response of the lattice structure. In the first part, an identification method of geometric imperfection parameters of the lattice structure based on point clouds is presented. These point clouds are based on tomography measurements. The point clouds are fed into the platform LATANA (LATtice ANAlysis) developed by IRT-SystemX to characterize the geometric imperfections. This is done by projecting the point clouds of each microbeam along the beam axis onto a 2D surface. Then, by fitting an ellipse to the 2D projections of the points, the geometric imperfections are characterized by introducing three parameters of an ellipse; semi-major/minor axes and angle of rotation. With regard to the calculated parameters of the microbeam geometric imperfections, a statistical analysis is carried out to determine a probability density law based on a statistical hypothesis. The microbeam samples are randomly drawn from the density law and are used to generate lattice structures. In the second part, a finite element model for the lattice structure with the simplified geometric imperfections (ellipse parameters) is presented. This numerical model is used to simulate the generated lattice structures. The propagation of the uncertainties of geometric imperfections is shown through the distribution of the computed mechanical responses of the lattice structures.

Keywords: additive manufacturing, finite element model, geometric imperfections, lattice structures, propagation of uncertainty

Procedia PDF Downloads 191

Authors: Mohammed Islam, Jungyong Wang, Dong Cheol Seo

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The Smoothed Particle Hydrodynamics (SPH) method is a novel, meshless, and Lagrangian technique based numerical method that has shown promises to accurately predict the hydrodynamics of water and structure interactions in violent flow conditions. The main goal of this study is to build confidence on the versatility of the Smoothed Particle Hydrodynamics (SPH) based tool, to use it as a complementary tool to the physical model testing capabilities and support research need for the performance evaluation of ships and offshore platforms exposed to an extreme and harsh environment. In the current endeavor, an open-sourced SPH-based tool was used and validated for modeling and predictions of the hydrodynamic interactions of a 6-DOF ship and bergy bits. The study involved the modeling of a modern generic drillship and simplified bergy bits in floating and towing scenarios and in regular and irregular wave conditions. The predictions were validated using the model-scale measurements on a moored ship towed at multiple oblique angles approaching a floating bergy bit in waves. Overall, this study results in a thorough comparison between the model scale measurements and the prediction outcomes from the SPH tool for performance and accuracy. The SPH predicted ship motions and forces were primarily within ±5% of the measurements. The velocity and pressure distribution and wave characteristics over the free surface depicts realistic interactions of the wave, ship, and the bergy bit. This work identifies and presents several challenges in preparing the input file, particularly while defining the mass properties of complex geometry, the computational requirements, and the post-processing of the outcomes.

Keywords: SPH, ship and bergy bit, hydrodynamic interactions, model validation, physical model testing

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Authors: Ece A. Irmak, Amdulla O. Mekhrabov, M. Vedat Akdeniz

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There is a growing interest in the modeling and simulation of magnetic nanoalloys by various computational methods. Magnetic crystalline/amorphous nanoparticles (NP) are interesting materials from both the applied and fundamental points of view, as their properties differ from those of bulk materials and are essential for advanced applications such as high-performance permanent magnets, high-density magnetic recording media, drug carriers, sensors in biomedical technology, etc. As an important magnetic material, Fe-Ni based nanoalloys have promising applications in the chemical industry (catalysis, battery), aerospace and stealth industry (radar absorbing material, jet engine alloys), magnetic biomedical applications (drug delivery, magnetic resonance imaging, biosensor) and computer hardware industry (data storage). The physical and chemical properties of the nanoalloys depend not only on the particle or crystallite size but also on composition and atomic ordering. Therefore, computer modeling is an essential tool to predict structural, electronic, magnetic and optical behavior at atomistic levels and consequently reduce the time for designing and development of new materials with novel/enhanced properties. Although first-principles quantum mechanical methods provide the most accurate results, they require huge computational effort to solve the Schrodinger equation for only a few tens of atoms. On the other hand, molecular dynamics method with appropriate empirical or semi-empirical inter-atomic potentials can give accurate results for the static and dynamic properties of larger systems in a short span of time. In this study, structural evolutions, magnetic and electronic properties of Fe-Ni based nanoalloys have been studied by using molecular dynamics (MD) method in Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) and Density Functional Theory (DFT) in the Vienna Ab initio Simulation Package (VASP). The effects of particle size (in 2-10 nm particle size range) and temperature (300-1500 K) on stability and structural evolutions of amorphous and crystalline Fe-Ni bulk/nanoalloys have been investigated by combining molecular dynamic (MD) simulation method with Embedded Atom Model (EAM). EAM is applicable for the Fe-Ni based bimetallic systems because it considers both the pairwise interatomic interaction potentials and electron densities. Structural evolution of Fe-Ni bulk and nanoparticles (NPs) have been studied by calculation of radial distribution functions (RDF), interatomic distances, coordination number, core-to-surface concentration profiles as well as Voronoi analysis and surface energy dependences on temperature and particle size. Moreover, spin-polarized DFT calculations were performed by using a plane-wave basis set with generalized gradient approximation (GGA) exchange and correlation effects in the VASP-MedeA package to predict magnetic and electronic properties of the Fe-Ni based alloys in bulk and nanostructured phases. The result of theoretical modeling and simulations for the structural evolutions, magnetic and electronic properties of Fe-Ni based nanostructured alloys were compared with experimental and other theoretical results published in the literature.

Keywords: density functional theory, embedded atom model, Fe-Ni systems, molecular dynamics, nanoalloys

Procedia PDF Downloads 249

Authors: Supanitayanon Lalita, Dechkunakorn Surachai, Anuwongnukroh Niwat, Srikhirin Toemsak, Roongrujimek Pitchaya, Tua-Ngam Peerapong

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Objective: To compare maximum load, percentage of elongation, physical characteristics of 4 types of dental floss: (1) Thai Silk Floss (silk, waxed), (2) Oral B® Essential Floss (nylon, waxed), (3) Experimental Floss Xu (nylon, unwaxed), (4) Experimental Floss Xw (nylon, waxed). Materials & method: Four types of floss were tested (n=30) with a Universal Testing Machine (Instron®). Each sample (30 cm long, 5 cm segment) was fixed, and pulled apart with load cell of 100 N and a test speed of 100 mm/min. Physical characteristics were investigated by digital microscope under 2.5×10 magnification, and scanning electron microscope under 1×100 and 5×100 magnification. The size of the filaments was measured in micron (μm) and the fineness were measured in Denier. Statistical analysis: For mechanical properties, the maximum load and the percentage of elongation were presented as mean ± SD. The distribution of the data was calculated by the Kolmogorov-Smirnov test. One-way ANOVA and multiple comparison (Tukey HSD) were used to analyze the differences among the groups with the level of a statistical difference at p < 0.05. Results: The maximum load of Floss Xu, Floss Xw, Oral B and Thai Silk were 47.39, 46.46, 25.38, and 23.70 N, respectively. The percentage of elongation of Oral B, Floss Xw, Floss Xu and Thai Silk were 72.43, 44.62, 31.25, and 16.44%, respectively. All 4 types of dental floss showed statistically differences in both the maximum load and percentage of elongation at p < 0.05, except for maximum load between Floss Xw and Floss Xu that showed no statistically significant difference. Physical characteristics of Thai silk revealed the most disintegrated, the smallest, and the least fine filaments. Conclusion: Floss Xu had the highest maximum load. Oral B had the highest percentage of elongation. Wax coating on Floss X increased the elongation but had no significant effect on the maximum load. The physical characteristics of Thai Silk resulted in the lowest mechanical properties values.

Keywords: dental floss, maximum load, mechanical property, percentage of elongation, physical property

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Authors: A. Abdullah, S. Abushalmat, A. Bakshwain, A. Basuhail, A. Aslam

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GIS (Geographic Information System) applications require geo-referenced data, this data could be available as databases or in the form of digital or hard-copy agro-meteorological maps. These parameter maps are color-coded with different regions corresponding to different parameter values, converting these maps into a database is not very difficult. However, text and different planimetric elements overlaid on these maps makes an accurate image to database conversion a challenging problem. The reason being, it is almost impossible to exactly replace what was underneath the text or icons; thus, pointing to the need for inpainting. In this paper, we propose a probabilistic inpainting approach that uses the probability of spatial locality of colors in the map for replacing overlaid elements with underlying color. We tested the limits of our proposed technique using non-textual simulated data and compared text removing results with a popular image editing tool using public domain data with promising results.

Keywords: noise, image, GIS, digital map, inpainting

Procedia PDF Downloads 356

Authors: Hamidreza Sahaleh

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Because of the stringent prerequisite of low sulfur and heavier raw oil feedstock more hydrogen will be devoured in the refineries. Specifically if huge scale limits are the reaction to an expanded hydrogen request, certain configuration and building background are obliged with, which will be depicted in this paper with an illustration. Chosen procedure plan prerequisite will be recorded and portrayed in agreement to the flowsheet. Also, a determination of imaginative outline elements, similar to process condensate reuse, safe reformer start up and prerequisites will be highlighted.

Keywords: low sulfur, raw oil, refineries, flowsheet

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Authors: Syed Misbahuddin, Sagufta Kapadia

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Autonomous indoor drone navigation has been posed with various challenges, including the inability to use a Global Positioning System (GPS). As of now, Unmanned Aerial Vehicles (UAVs) either rely on 3D mapping systems or utilize external camera arrays to track the UAV in an enclosed environment. The objective of this paper is to develop an algorithm that utilizes Kalman Filtering to reduce noise, allowing the UAV to be navigated indoors using only the flight controller and an onboard companion computer. In this paper, open-source libraries are used to control the UAV, which will only use the onboard accelerometer on the flight controller to estimate the position through double integration. One of the advantages of such a system is that it allows for low-cost and lightweight UAVs to autonomously navigate indoors without advanced mapping of the environment or the use of expensive high-precision-localization sensors.

Keywords: accelerometer, indoor-navigation, Kalman-filtering, position-control

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Authors: Lu Ren, You-Liang Fang, Yan-Gang Zhao

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In recent years, the application of BIM (Building Information Modelling) to construction schedule plan has been the focus of more and more researchers. In order to assess the reasonable level of the BIM-based construction schedule plan, that is whether the schedule can be completed on time, some researchers have introduced reliability theory to evaluate. In the process of evaluation, the uncertain factors affecting the construction schedule plan are regarded as random variables, and probability distributions of the random variables are assumed to be normal distribution, which is determined using two parameters evaluated from the mean and standard deviation of statistical data. However, in practical engineering, most of the uncertain influence factors are not normal random variables. So the evaluation results of the construction schedule plan will be unreasonable under the assumption that probability distributions of random variables submitted to the normal distribution. Therefore, in order to get a more reasonable evaluation result, it is necessary to describe the distribution of random variables more comprehensively. For this purpose, cubic normal distribution is introduced in this paper to describe the distribution of arbitrary random variables, which is determined by the first four moments (mean, standard deviation, skewness and kurtosis). In this paper, building the BIM model firstly according to the design messages of the structure and making the construction schedule plan based on BIM, then the cubic normal distribution is used to describe the distribution of the random variables due to the collecting statistical data of the random factors influencing construction schedule plan. Next the reliability analysis of the construction schedule plan based on BIM can be carried out more reasonably. Finally, the more accurate evaluation results can be given providing reference for the implementation of the actual construction schedule plan. In the last part of this paper, the more efficiency and accuracy of the proposed methodology for the reliability analysis of the construction schedule plan based on BIM are conducted through practical engineering case.

Keywords: BIM, construction schedule plan, cubic normal distribution, reliability analysis

Procedia PDF Downloads 152

Authors: Pierre Mintom, Ebai Patricia, Merlin Dasse, Marlyse Chantal Nyangon Ndongo, Aicha Aretouyap Kouotou, Felix Essiben, Christine Fernande Nyangono Biyegue

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Background: The death of women during and after pregnancy remains a major concern in public health policy in Cameroon. Among the causes of this mortality is eclampsia which is a consequence of the Pre-eclampsia characterized by the double burden of pregnancy-induced hypertension and albuminuria in pregnant women. Objective: To determine the various factors associated with the pre-eclampsia in pregnant women of Foumban. Methodology: A cross-sectional and analytical study was carried out during the period from July to August 2020 and supplemented by another study carried out from August 05 to September 05, 2022, at the Foumban district hospital. A questionnaire was administered to pregnant women. It focused on socio-demographic parameters, the state nutritional, health status, and maternal parameters. Blood pressure was taken using an electronic blood pressure monitor, and urinary albumin was measuring using urine dipstick. Pre-eclampsia was defined by three types of double burden: double burden systolic hypertension–hyperalbuminuria (SHH), defined for SBP≥140 mmHg and hyperalbuminuria ≥1+ on urine dipstick, double burden diastolic hypertension–hyperalbuminuria (DHH), defined for PAD≥90 mmHg and hyperalbuminuria ≥1+ on the urine dipstick, and the double burden systolodiastolic arterial hypertension– hyperalbuminuria (SDHH), defined for SBP ≥ 140mmHg, PAD≥90 mmHg and hyperalbuminuria ≥1+ on urine dipstick. IBM SPSS Software was used for statistical analysis. Results: The results of this study show that the prevalence of pre-eclampsia was 17.3% for the double burden SHH, 19.9% for the double burden DHH and 14.1% for double burden SDHH. Associated factors with pre-eclampsia according to the three types of double burden were marital status (P<0.05), religion (P<0.05), history of hypertension before pregnancy (P<0.05). Associated factors for the double burden of DHH and SDHH were the nutritional status before the pregnancy (P<0.05) and the number of prenatal consultations (P<0.05). In terms of food groups, regular consumption of spices significantly increased the risk of pre-eclampsia by 5.318, 6.277 and 11.271 times respectively for the SHH, DHH and SDHH double burdens, while regular consumption of sweets regular consumption of sweets increased by 2.42 times and 2.053 times respectively the double DHH and SDHH burdens respectively. Conclusion: Our study made it possible to redefine pre-eclampsia by considering the subtypes of hypertension. Certain socio-demographic parameters and certain dietary habits influence the occurrence of pre-eclampsia characterized by the double burden Hypertension-hyperalbuminuria in pregnant women, which may later lead to the occurrence of eclampsia. Moreover, albuminemia could be a good predicitive factor of pre-eclampsia and could be explored.

Keywords: hypertension, hyperalbuminuria, pregnant women, foumban

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Authors: Madre Paarlber, Alwiena Blignaut

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Background: Medication administration errors remains a global patient safety problem targeted by the WHO (World Health Organization), yet research on this matter is sparce within the South African context. Objective: The aim was to explore and describe nurses’ (medication administrators) perceptions regarding medication administration safety-related culture, incidence, causes, and reporting in the Gauteng Province of South Africa, and to determine any relationships between perceived variables concerned with medication safety (safety culture, incidences, causes, reporting of incidences, and reasons for non-reporting). Method: A quantitative research design was used through which self-administered online surveys were sent to 768 nurses (medication administrators) (n=217). The response rate was 28.26%. The survey instrument was synthesised from the Agency of Healthcare Research and Quality (AHRQ) Hospital Survey on Patient Safety Culture, the Registered Nurse Forecasting (RN4CAST) survey, a survey list prepared from a systematic review aimed at generating a comprehensive list of medication administration error causes and the Medication Administration Error Reporting Survey from Wakefield. Exploratory and confirmatory factor analyses were used to determine the validity and reliability of the survey. Descriptive and inferential statistical data analysis were used to analyse quantitative data. Relationships and correlations were identified between items, subscales and biographic data by using Spearmans’ Rank correlations, T-Tests and ANOVAs (Analysis of Variance). Nurses reported on their perceptions of medication administration safety-related culture, incidence, causes, and reporting in the Gauteng Province. Results: Units’ teamwork deemed satisfactory, punitive responses to errors accentuated. “Crisis mode” working, concerns regarding mistake recording and long working hours disclosed as impacting patient safety. Overall medication safety graded mostly positively. Work overload, high patient-nurse ratios, and inadequate staffing implicated as error-inducing. Medication administration errors were reported regularly. Fear and administrative response to errors effected non-report. Non-report of errors’ reasons was affected by non-punitive safety culture. Conclusions: Medication administration safety improvement is contingent on fostering a non-punitive safety culture within units. Anonymous medication error reporting systems and auditing nurses’ workload are recommended in the quest of improved medication safety within Gauteng Province private hospitals.

Keywords: incidence, medication administration errors, medication safety, reporting, safety culture

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Authors: Jairo Vega, Fabian Chamba, Jordy Urgiles

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In this work, the implementation of a Matlabcontrolled Musical Tesla Coil and external audio signals was presented. First, the audio signal was obtained from a mobile device and processed in Matlab to modify it, adding noise or other desired effects. Then, the processed signal was passed through a preamplifier to increase its amplitude to a level suitable for further amplification through a power amplifier, which was part of the current driver circuit of the Tesla coil. To get the Tesla coil to generate music, a circuit capable of modulating and generating the audio signal by manipulating electrical discharges was used. To visualize and listen to these discharges, a small Faraday cage was built to attenuate the external electric fields. Finally, the implementation of the musical Tesla coil was concluded. However, it was observed that the audio signal volume was very low, and the components used heated up quickly. Due to these limitations, it was determined that the project could not be connected to power for long periods of time.

Keywords: Tesla coil, plasma, electrical signals, GNU Radio

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Authors: Mohammed El Raey, Moustafa Osman Mohammed

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The spatial-ecological modeling is relating sustainable dispersions with social development. Sustainability with spatial-ecological model gives attention to urban environments in the design review management to comply with Earth’s System. Naturally exchange patterns of ecosystems have consistent and periodic cycles to preserve energy flows and materials in Earth’s System. The probabilistic risk assessment (PRA) technique is utilized to assess the safety of industrial complex. The other analytical approach is the Failure-Safe Mode and Effect Analysis (FMEA) for critical components. The plant safety parameters are identified for engineering topology as employed in assessment safety of industrial ecology. In particular, the most severe accidental release of hazardous gaseous is postulated, analyzed and assessment in industrial region. The IAEA- safety assessment procedure is used to account the duration and rate of discharge of liquid chlorine. The ecological model of plume dispersion width and concentration of chlorine gas in the downwind direction is determined using Gaussian Plume Model in urban and ruler areas and presented with SURFER®. The prediction of accident consequences is traced in risk contour concentration lines. The local greenhouse effect is predicted with relevant conclusions. The spatial-ecological model is also predicted the distribution schemes from the perspective of pollutants that considered multiple factors of multi-criteria analysis. The data extends input–output analysis to evaluate the spillover effect, and conducted Monte Carlo simulations and sensitivity analysis. Their unique structure is balanced within “equilibrium patterns”, such as the biosphere and collective a composite index of many distributed feedback flows. These dynamic structures are related to have their physical and chemical properties and enable a gradual and prolonged incremental pattern. While this spatial model structure argues from ecology, resource savings, static load design, financial and other pragmatic reasons, the outcomes are not decisive in artistic/ architectural perspective. The hypothesis is an attempt to unify analytic and analogical spatial structure for development urban environments using optimization software and applied as an example of integrated industrial structure where the process is based on engineering topology as optimization approach of systems ecology.

Keywords: spatial-ecological modeling, spatial structure orientation impact, composite structure, industrial ecology

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Authors: Najibullah M, Soumendra Nath Kuiry

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Dams and reservoirs are perceived for their estimable alms to irrigation, water supply, flood control, electricity generation, etc. which civilize the prosperity and wealth of society across the world. Meantime the dam breach could cause devastating flood that can threat to the human lives and properties. Failures of large dams remain fortunately very seldom events. Nevertheless, a number of occurrences have been recorded in the world, corresponding in an average to one to two failures worldwide every year. Some of those accidents have caused catastrophic consequences. So it is decisive to predict the dam break flow for emergency planning and preparedness, as it poses high risk to life and property. To mitigate the adverse impact of dam break, modeling is necessary to gain a good understanding of the temporal and spatial evolution of the dam-break floods. This study will mainly deal with one-dimensional (1D) dam break modeling. Less commonly used in the hydraulic research community, another possible option for modeling the rapidly varied dam-break flows is the extended Boussinesq equations (BEs), which can describe the dynamics of short waves with a reasonable accuracy. Unlike the Shallow Water Equations (SWEs), the BEs taken into account the wave dispersion and non-hydrostatic pressure distribution. To capture the dam-break oscillations accurately it is very much needed of at least fourth-order accurate numerical scheme to discretize the third-order dispersion terms present in the extended BEs. The scope of this work is therefore to develop an 1D fourth-order accurate in both space and time Boussinesq model for dam-break flow analysis by using finite-volume / finite difference scheme. The spatial discretization of the flux and dispersion terms achieved through a combination of finite-volume and finite difference approximations. The flux term, was solved using a finite-volume discretization whereas the bed source and dispersion term, were discretized using centered finite-difference scheme. Time integration achieved in two stages, namely the third-order Adams Basforth predictor stage and the fourth-order Adams Moulton corrector stage. Implementation of the 1D Boussinesq model done using PYTHON 2.7.5. Evaluation of the performance of the developed model predicted as compared with the volume of fluid (VOF) based commercial model ANSYS-CFX. The developed model is used to analyze the risk of cascading dam failures similar to the Panshet dam failure in 1961 that took place in Pune, India. Nevertheless, this model can be used to predict wave overtopping accurately compared to shallow water models for designing coastal protection structures.

Keywords: Boussinesq equation, Coastal protection, Dam-break flow, One-dimensional model

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Authors: Penchuk A. Vovkanych

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The adaptive changes in the respiratory system provide the background for the increase of aerobic capacity and sport results on the middle and long distances runners. Effect of such adaptive changes in the sport orienteering remains poorly investigated. Therefore our study was undertaken to reveal the adaptive changes in the respiration indices of high skilled orienteer athletes.

Keywords: adaptation, external, functional state, respiration, running, sport orienteering

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Authors: Mohamed Elghorab, Vendra C. Madhav Rao, Jennifer X. Wen

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Turbulence modelling is still evolving, and efforts are on to improve and develop numerical methods to simulate the real turbulence structures by using the empirical and experimental information. The monotonically integrated large eddy simulation (MILES) is an attractive approach for modelling turbulence in high Re flows, which is based on the solving of the unfiltered flow equations with no explicit sub-grid scale (SGS) model. In the current work, this approach has been used, and the action of the SGS model has been included implicitly by intrinsic nonlinear high-frequency filters built into the convection discretization schemes. The MILES solver is developed using the opensource CFD OpenFOAM libraries. The role of flux limiters schemes namely, Gamma, superBee, van-Albada and van-Leer, is studied in predicting turbulent statistical quantities for a fully developed channel flow with a friction Reynolds number, Re_T = 180, and compared the numerical predictions with the well-established Direct Numerical Simulation (DNS) results for studying the wall generated turbulence. It is inferred from the numerical predictions that Gamma, van-Leer and van-Albada limiters produced more diffusion and overpredicted the velocity profiles, while superBee scheme reproduced velocity profiles and turbulence statistical quantities in good agreement with the reference DNS data in the streamwise direction although it deviated slightly in the spanwise and normal to the wall directions. The simulation results are further discussed in terms of the turbulence intensities and Reynolds stresses averaged in time and space to draw conclusion on the flux limiter schemes performance in OpenFOAM context.

Keywords: flux limiters, implicit SGS, MILES, OpenFOAM, turbulence statistics

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Authors: Gholamreza Ghodrati Amiri, Mojtaba Jafarian Abyaneh, Ali Zare Hosseinzadeh

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This paper presents an effective model updating strategy for damage localization and quantification in frames by defining damage detection problem as an optimization issue. A generalized version of the Modal Residual Force (MRF) is employed for presenting a new damage-sensitive cost function. Then, Grey Wolf Optimization (GWO) algorithm is utilized for solving suggested inverse problem and the global extremums are reported as damage detection results. The applicability of the presented method is investigated by studying different damage patterns on the benchmark problem of the IASC-ASCE, as well as a planar shear frame structure. The obtained results emphasize good performance of the method not only in free-noise cases, but also when the input data are contaminated with different levels of noises.

Keywords: frame, grey wolf optimization algorithm, modal residual force, structural damage detection

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Authors: Hatice Akbıyık, Hülya Gökmen Özel, Nagehan Emiralioğlu, Elmas Ebru Güneş Yalçın, Deniz Doğru Ersöz, Hayriye Uğur Özçelik, Nural Kiper

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Background: Dietary recommendations in cystic fibrosis (CF) are based on the need to compensate for the increased energy needs of infection, the increased energy cost of breathing and the losses, incurred from malabsorption. Studies in CF indicate that dietary recommendations for CF patients can be difficult to achieve Aim: The aim of this study was to evaluate the energy and nutrient intakes and to compare in accordance with CF dietary guidelines in CF. Methods: One-hundred sixty patients with CF, aged between 2 to 20 years (mean±SD= 7.4±4.8 years) attending Hacettepe University, Faculty of Medicine, Department of Pediatric Pulmonary Diseases were included. Energy and nutrient intakes from foods and enteral products were calculated using a-24-hour dietary recall method with BEBIS 7.2 programme. Percentages of energy and nutrient intakes were compared in accordance with CF dietary guidelines. Patients or/and parents completed a questionnaire showing mealtime problems, usage of alternative therapies and type of nutrition. Statistical analyses were done using SPSS 16.0 programme. Results: It was obtained that 14.5% and 46.9% of the total energy intake were from proteins and carbohydrates, respectively. The actual contribution of total, saturated, monounsaturated and polyunsaturated fats to the total caloric intake was 37.5%, 14.3%, 14.9%, 9.9%, respectively. It was found that 87.7% of energy, 85% of protein 91.7% of carbohydrate, 81.1% of fat intakes were met, when compared CF recommended intakes of 120% RDA. Additionally 67%, 69.5%, 68.2% and 68.9% of the subjects did not achieve CF recommended intakes of 120% RDA for energy, protein, carbohydrate and fat, respectively. Patients with CF had low intakes for age for almost all vitamins and minerals, although supplementation was given. Especially most patients did not achieve the minimum recommended vitamin K intake of 120% RDA. The percentage meeting 120% RDA was 75.9% for vitamin K. It was shown that 41% of the patients had mealtime problems and they skipped the breakfast. Moreover 25.4% of the patients used alternative products outside the standard treatment (such as omega-3, ginger, turmeric, local honey). It was also showed that 60.8% of patients were using enteral products in addition to normal foods, the remaining patients were on only normal foods. Conclusion: The aims of improving nutritional status in children are to achieve normal weight gain and growth; optimize vitamin and mineral status; and slow the rate of clinical decline. In this study although enteral products were used in patients with CF, it was found that energy and nutrient requirements were unable to meet. Because dietary assessment is essential to identify the need for earlier nutritional intervention, in each visit patients need to be referred to CF specialist dietitian.

Keywords: cystic fibrosis, energy and nutrient intakes, mealtime problems, malabsorbtion

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Authors: D. Calogine, O. Chau, S. Dotti, O. Ramiarinjanahary, P. Rasoavonjy, F. Tovondahiniriko

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Mafate is a natural circus in the north-western part of Reunion Island, without an electrical grid and road network. A micro-grid concept is being experimented in this area, composed of a photovoltaic production combined with electrochemical batteries, in order to meet the local population for self-consumption of electricity demands. This work develops a discrete model as well as a stochastic model in order to reach an optimal equilibrium between production and consumptions for a cluster of houses. The management of the energy power leads to a large linearized programming system, where the time interval of interest is 24 hours The experimental data are solar production, storage energy, and the parameters of the different electrical devices and batteries. The unknown variables to evaluate are the consumptions of the various electrical services, the energy drawn from and stored in the batteries, and the inhabitants’ planning wishes. The objective is to fit the solar production to the electrical consumption of the inhabitants, with an optimal use of the energies in the batteries by satisfying as widely as possible the users' planning requirements. In the discrete model, the different parameters and solutions of the linear programming system are deterministic scalars. Whereas in the stochastic approach, the data parameters and the linear programming solutions become random variables, then the distributions of which could be imposed or established by estimation from samples of real observations or from samples of optimal discrete equilibrium solutions.

Keywords: photovoltaic production, power consumption, battery storage resources, random variables, stochastic modeling, estimations of probability distributions, mixed integer linear programming, smart micro-grid, self-consumption of electricity.

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Authors: T. Sanches, K. Bousson

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As part of the development of a 4D autopilot system for unmanned aerial vehicles (UAVs), i.e. a time-dependent robust trajectory generation and control algorithm, this work addresses the problem of optimal path control based on the flight sensors data output that may be unreliable due to noise on data acquisition and/or transmission under certain circumstances. Although several filtering methods, such as the Kalman-Bucy filter or the Linear Quadratic Gaussian/Loop Transfer Recover Control (LQG/LTR), are available, the utter complexity of the control system, together with the robustness and reliability required of such a system on a UAV for airworthiness certifiable autonomous flight, required the development of a proper robust filter for a nonlinear system, as a way of further mitigate errors propagation to the control system and improve its ,performance. As such, a nonlinear algorithm based upon the LQG/LTR, is validated through computational simulation testing, is proposed on this paper.

Keywords: autonomous flight, LQG/LTR, nonlinear state estimator, robust flight control

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Authors: V. Sacca, A. Sarica, F. Novellino, S. Barone, T. Tallarico, E. Filippelli, A. Granata, P. Valentino, A. Quattrone

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In the last few years, resting-state functional MRI (rs-fMRI) was widely used to investigate the architecture of brain networks by investigating the Blood Oxygenation Level Dependent response. This technique represented an interesting, robust and reliable approach to compare pathologic and healthy subjects in order to investigate neurodegenerative diseases evolution. On the other hand, the elaboration of rs-fMRI data resulted to be very prone to noise due to confounding factors especially the head motion. Head motion has long been known to be a source of artefacts in task-based functional MRI studies, but it has become a particularly challenging problem in recent studies using rs-fMRI. The aim of this work was to evaluate in MS patients a well-known motion correction algorithm from the FMRIB's Software Library - MCFLIRT - that could be applied to minimize the head motion distortions, allowing to correctly interpret rs-fMRI results.

Keywords: head motion correction, MCFLIRT algorithm, multiple sclerosis, resting state fMRI

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Authors: Francisco Velez, Juan David Gomez

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Dispersion effects on the Scattering for a semicircular canyon in a micropolar continuum are analyzed, by using a computational finite element scheme. The presence of microrotational waves and the dispersive SV waves affects the propagation of elastic waves. Here, a contrast with the classic model is presented, and the dependence with the micropolar parameters is studied.

Keywords: scattering, semicircular canyon, wave dispersion, micropolar medium, FEM modeling

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Authors: Maram Shahad Dana Anfal

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This research paper presents the design of a surveillance drone with computer-aided durability and model analyses that provides a cost-effective and efficient solution for various applications. The quadcopter's design is based on a lightweight and strong structure made of materials such as aluminum and titanium, which provide a durable structure for the quadcopter. The structure of this product and the computer-aided durability system are both designed to ensure frequent repairs or replacements, which will save time and money in the long run. Moreover, the study discusses the drone's ability to track, investigate, and deliver objects more quickly than traditional methods, makes it a highly efficient and cost-effective technology. In this paper, a comprehensive analysis of the quadcopter's operation dynamics and limitations is presented. In both simulation and experimental data, the computer-aided durability system and the drone's design demonstrate their effectiveness, highlighting the potential for a variety of applications, such as search and rescue missions, infrastructure monitoring, and agricultural operations. Also, the findings provide insights into possible areas for improvement in the design and operation of the drone. Ultimately, this paper presents a reliable and cost-effective solution for surveillance applications by designing a drone with computer-aided durability and modeling. With its potential to save time and money, increase reliability, and enhance safety, it is a promising technology for the future of surveillance drones. operation dynamic equations have been evaluated successfully for different flight conditions of a quadcopter. Also, CAE modeling techniques have been applied for the modal risk assessment at operating conditions.Stress analysis have been performed under the loadings of the worst-case combined motion flight conditions.

Keywords: drone, material, solidwork, hypermesh

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Authors: Andreea Molnar, Amalia Ardeljan, Lexi Frankel, Marissa Dallara, Brittany Nagel, Omar Rashid

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Background: Escherichia coli is a gram-negative, facultative anaerobic bacteria that belongs to the family Enterobacteriaceae and resides in the intestinal tracts of individuals. E.Coli has numerous strains grouped into serogroups and serotypes based on differences in antigens in their cell walls (somatic, or “O” antigens) and flagella (“H” antigens). More than 700 serotypes of E. coli have been identified. Although most strains of E. coli are harmless, a few strains, such as E. coli O157:H7 which produces Shiga toxin, can cause intestinal infection with symptoms of severe abdominal cramps, bloody diarrhea, and vomiting. Infection with E. Coli can lead to the development of systemic inflammation as the toxin exerts its effects. Chronic inflammation is now known to contribute to cancer development in several organs, including the prostate. The purpose of this study was to evaluate the correlation between E. Coli and the incidence of prostate cancer. Methods: Data collected in this cohort study was provided by a Health Insurance Portability and Accountability Act (HIPAA) compliant national database to evaluate patients infected with E.Coli infection and prostate cancer using the International Classification of Disease (ICD-10 and ICD-9 codes). Permission to use the database was granted by Holy Cross Health, Fort Lauderdale for the purpose of academic research. Data analysis was conducted through the use of standard statistical methods. Results: Between January 2010 and December 2019, the query was analyzed and resulted in 81, 037 patients after matching in both infected and control groups, respectively. The two groups were matched by Age Range and CCI score. The incidence of prostate cancer was 2.07% and 1,680 patients in the E. Coli group compared to 5.19% and 4,206 patients in the control group. The difference was statistically significant by a p-value p<2.2x10-16 with an Odds Ratio of 0.53 and a 95% CI. Based on the specific treatment for E.Coli, the infected group vs control group were matched again with a result of 31,696 patients in each group. 827 out of 31,696 (2.60%) patients with a prior E.coli infection and treated with antibiotics were compared to 1634 out of 31,696 (5.15%) patients with no history of E.coli infection (control) and received antibiotic treatment. Both populations subsequently developed prostate carcinoma. Results remained statistically significant (p<2.2x10-16), Odds Ratio=0.55 (95% CI 0.51-0.59). Conclusion: This retrospective study shows a statistically significant correlation between E.Coli infection and a decreased incidence of prostate cancer. Further evaluation is needed in order to identify the impact of E.Coli infection and prostate cancer development.

Keywords: E. Coli, prostate cancer, protective, microbiology

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