Search results for: reduced modeling

Authors: Cristian Patrascioiu, Loredana Negoita

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This paper is focused on modeling and simulation of the tubular heaters. The paper is structured in four parts: the structure of the tubular convection section, the heat transfer model, the adaptation of the mathematical model and the solving model. The main hypothesis of the heat transfer modeling is that the heat exchanger of the convective tubular heater is a lumped system. In the same time, the model uses the heat balance relations, Newton’s law and criteria relations. The numerical program achieved allows for the estimation of the burn gases outlet temperature and the heated flow outlet temperature.

Keywords: heat exchanger, mathematical modelling, nonlinear equation system, Newton-Raphson algorithm

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Authors: Miral Selim, May Haggag, Ibrahim Abotaleb

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The aging of transportation infrastructure presents significant challenges, particularly concerning the monitoring and maintenance of bridges. This study investigates the application of Random Forest algorithms for predictive modeling of bridge conditions, utilizing data from the US National Bridge Inventory (NBI). The research is significant as it aims to improve bridge management through data-driven insights that can enhance maintenance strategies and contribute to overall safety. Random Forest is chosen for its robustness, ability to handle complex, non-linear relationships among variables, and its effectiveness in feature importance evaluation. The study begins with comprehensive data collection and cleaning, followed by the identification of key variables influencing bridge condition ratings, including age, construction materials, environmental factors, and maintenance history. Random Forest is utilized to examine the relationships between these variables and the predicted bridge conditions. The dataset is divided into training and testing subsets to evaluate the model's performance. The findings demonstrate that the Random Forest model effectively enhances the understanding of factors affecting bridge conditions. By identifying bridges at greater risk of deterioration, the model facilitates proactive maintenance strategies, which can help avoid costly repairs and minimize service disruptions. Additionally, this research underscores the value of data-driven decision-making, enabling better resource allocation to prioritize maintenance efforts where they are most necessary. In summary, this study highlights the efficiency and applicability of Random Forest in predictive modeling for bridge management. Ultimately, these findings pave the way for more resilient and proactive management of bridge systems, ensuring their longevity and reliability for future use.

Keywords: data analysis, random forest, predictive modeling, bridge management

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Authors: Fatima Babar, Majid I. Khan, Malik Najmus Saqib, Muhammad Tahir

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This article provides range based improvements over a well-known single-hop range free localization scheme, Approximate Point in Triangulation (APIT) by proposing an energy efficient Barycentric coordinate based Point-In-Triangulation (PIT) test along with PIT based trilateration. These improvements result in energy efficiency, reduced localization error and improved localization coverage compared to APIT and its variants. Moreover, we propose to embed Received signal strength indication (RSSI) based distance estimation in DV-Hop which is a multi-hop localization scheme. The proposed localization algorithm achieves energy efficiency and reduced localization error compared to DV-Hop and its available improvements. Furthermore, a hybrid multi-hop localization scheme is also proposed that utilize Barycentric coordinate based PIT test and both range based (Received signal strength indicator) and range free (hop count) techniques for distance estimation. Our experimental results provide evidence that proposed hybrid multi-hop localization scheme results in two to five times reduction in the localization error compare to DV-Hop and its variants, at reduced energy requirements.

Keywords: Localization, Trilateration, Triangulation, Wireless Sensor Networks

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Authors: Saeed Zeinali, Nasser Talebbeydokhti, Mehdi Saeidian, Shahrad Vosough

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In this article, bathymetry changes have been studied as a case study for Larak Island, located in The South of Iran. The advanced 2D model of Mike21 has been used for this purpose. A simple procedure has been utilized in this model. First, the hydrodynamic (HD) module of Mike21 has been used to obtain the required output for sediment transport model (ST module). The ST module modeled the area for tidal currents only. Bed level changes are resulted by series of modeling for both HD and ST module in 3 months time step. The final bathymetry in each time step is used as the primary bathymetry for next time step. This consecutive procedure been continued until bathymetry for the year 2020 is obtained.

Keywords: bed level changes, Larak Island, hydrodynamic, sediment transport

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Authors: Jamel Boukhatem, Mouldi Djelassi

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Contrary to the existing literature generally focusing on the role played by Sukuk in enhancing investors' and shareholders' wealth, this paper sheds some light on the Sukuk wealth effect across all economic agents: households, government, and investors by implementing a two-period life-cycle model with overlapping generations to show whether Sukuk is net wealth. The main findings are threefold: i) the effect of a change in Sukuk issuances on the consumers’ utility level will be different from one generation to another, ii) an increase in taxes due to the increase in Sukuk and rents is covered by transfers made by the members of generation 1 in the form of inheritance, and iii) the existence of a positive relationship between the asset prices representative of Sukuk and the real activity.

Keywords: Sukuk, households, investors, overlapping generations model, wealth, modeling

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Authors: Mei-Chun Chang

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Due to digital transformation and social media development in recent years, various real-time interactive digital tools have been developed to meet the design demands for virtual reality avatars, which also promote digital content learners' active participation in the creation process. As a result, new social media design tools have the characteristics of intuitive operation with a simplified interface for fast production, from which works can be simply created. This study carried out observations, records, questionnaire surveys, and interviews on the creation and learning of visual avatars made by students of the National Taiwan University of Science and Technology (NTUST) with the VRoid Studio 3D modeling tool so as to explore their learning effectiveness on the design of visual avatars. According to the results of this study, the VRoid Studio 3D character modeling tool has a positive impact on the learners and helps to improve their learning effectiveness. Students with low academic achievements said that they could complete the conceived modeling with their own thinking by using the design tool, which increased their sense of accomplishment. Conclusions are drawn according to the results, and relevant future suggestions are put forward.

Keywords: virtual avatar, character design, social media, vroid studio, creation, digital learning

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Authors: Kaisy Xinhong Ye, Su Lin Lim, Jialiang Li, Lei Feng

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background: Multiple healthful dietary patterns have been linked with dementia, but limited studies have looked at the role of diet in cognitive health in Asians whose eating habits are very different from their counterparts in the west. This study aimed to derive a dietary pattern that is associated with the risk of cognitive impairment (CI) in the Singaporean population. Method: The analysis was based on 719 community older adults aged 60 and above. Dietary intake was measured using a validated semi-quantitative food-frequency questionnaire (FFQ). Reduced rank regression (RRR) was used to extract dietary pattern from 45 food groups, specifying sugar, dietary fiber, vitamin A, calcium, and the ratio of polyunsaturated fat to saturated fat intake (P:S ratio) as response variables. The RRR-derived dietary patterns were subsequently investigated using multivariate logistic regression models to look for associations with the risk of CI. Results: A dietary pattern characterized by greater intakes of green leafy vegetables, red-orange vegetables, wholegrains, tofu, nuts, and lower intakes of biscuits, pastries, local sweets, coffee, poultry with skin, sugar added to beverages, malt beverages, roti, butter, and fast food was associated with reduced risk of CI [multivariable-adjusted OR comparing extreme quintiles, 0.29 (95% CI: 0.11, 0.77); P-trend =0.03]. This pattern was positively correlated with P:S ratio, vitamin A, and dietary fiber and negatively correlated with sugar. Conclusion: A dietary pattern providing high P:S ratio, vitamin A and dietary fiber, and a low level of sugar may reduce the risk of cognitive impairment in old age. The findings have significance in guiding local Singaporeans to dementia prevention through food-based dietary approaches.

Keywords: dementia, cognitive impairment, diet, nutrient, elderly

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Authors: Te-Jen Chang, I-Hui Pan, Ping-Sheng Huang, Shan-Jen Cheng

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In this paper, a fast multiplication computing method utilizing the complement representation method and canonical recoding technique is proposed. By performing complements and canonical recoding technique, the number of partial products can be reduced. Based on these techniques, we propose an algorithm that provides an efficient multiplication method. On average, our proposed algorithm is to reduce the number of k-bit additions from (0.25k+logk/k+2.5) to (k/6 +logk/k+2.5), where k is the bit-length of the multiplicand A and multiplier B. We can therefore efficiently speed up the overall performance of the multiplication. Moreover, if we use the new proposes to compute common-multiplicand multiplication, the computational complexity can be reduced from (0.5 k+2 logk/k+5) to (k/3+2 logk/k+5) k-bit additions.

Keywords: algorithm design, complexity analysis, canonical recoding, public key cryptography, common-multiplicand multiplication

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Authors: K. Passbakhsh

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Determination of reinforcement forces is one of the most important and main discussions in designing retaining walls. By determining these forces we refrain from conservative planning. By numerically modeling the reinforced soil retaining walls under dynamic loading reinforcement forces can be calculated. In this study we try to approach the gained forces by pseudo-static method according to FHWA code and gained forces from numerical modeling by finite element method, by selecting seismic horizontal coefficient for different wall height. PLAXIS software was used for numerical analysis. Then the effect of reinforcement stiffness and soil type on reinforcement forces is examined.

Keywords: reinforced soil, PLAXIS, reinforcement forces, retaining walls

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Authors: Rouaz Idriss, Bourahla Nour-Eddine, Kahlouche Farah, Rafa Sid Ali

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The stability of structures made of light-gauge steel depends highly on the contribution of Shear Wall Panel (SWP) systems under horizontal forces due to wind or earthquake loads. Steel plate sheathing is often used with these panels made of cold formed steel (CFS) to improve its shear strength. In order to predict the shear strength resistance, two methods are presented in this paper. In the first method, the steel plate sheathing is modeled with plats strip taking into account only the tension and compression force due to the horizontal load, where both track and stud are modeled according to the geometrical and mechanical characteristics of the specimen used in the experiments. The theoretical background and empirical formulations of this method are presented in this paper. However, the second method is based on a micro modeling of the cold formed steel Shear Wall Panel “CFS-SWP” using Abaqus software. A nonlinear analysis was carried out with an in-plan monotonic load. Finally, the comparison between these two methods shows that the micro modeling with Abaqus gives better prediction of shear resistance of SWP than strips method. However, the latter is easier and less time consuming than the micro modeling method.

Keywords: cold formed steel 'CFS', shear wall panel, strip method, finite elements

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Authors: Flackson Tshuma, James Bennett, Pieter Andreas Swanepoel, Johan Labuschagne, Stephan van der Westhuizen, Francis Rayns

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Amongst other things, tillage and synthetic agrochemicals can be effective methods of seedbed preparation and pest control. Nonetheless, frequent and intensive tillage and excessive application of synthetic agrochemicals, such as herbicides and insecticides, can reduce soil microbial enzyme activity. A decline in soil microbial enzyme activity can negatively affect nutrient cycling and crop productivity. In this study, the effects of four tillage treatments; continuous mouldboard plough; shallow tine-tillage to a depth of about 75 mm; no-tillage; and tillage rotation (involving shallow tine-tillage once every four years in rotation with three years of no-tillage), and two rates of synthetic agrochemicals (standard: with regular application of synthetic agrochemicals; and reduced: fewer synthetic agrochemicals in combination with bio-chemicals/ or bio-stimulants) on soil microbial enzyme activity were investigated between 2018 and 2020 in a typical Mediterranean climate zone in South Africa. Four different bio-stimulants applied contained: Trichoderma asperellum, fulvic acid, silicic acid, and Nereocystis luetkeana extracts, respectively. The study was laid out as a complete randomised block design with four replicated blocks. Each block had 14 plots, and each plot measured 50 m x 6 m. The study aimed to assess the combined impact of tillage practices and reduced rates of synthetic agrochemical application on soil microbial enzyme activity in a dryland cropping system. It was hypothesised that the application of bio-stimulants in combination with minimum soil disturbance will lead to a greater increase in microbial enzyme activity than the effect of applying either in isolation. Six soil cores were randomly and aseptically collected from each plot for microbial enzyme activity analysis from the 0-150 mm layer of a field trial under a dryland crop rotation system in the Swartland region. The activities of four microbial enzymes, β-glucosidase, acid phosphatase, alkaline phosphatase and urease, were assessed. The enzymes are essential for the cycling of glucose, phosphorus, and nitrogen, respectively. Microbial enzyme activity generally increased with a reduction of both tillage intensity and synthetic agrochemical application. The use of the mouldboard plough led to the least (P<0.05) microbial enzyme activity relative to the reduced tillage treatments, whereas the system with bio-stimulants (reduced synthetic agrochemicals) led to the highest (P<0.05) microbial enzyme activity relative to the standard systems. The application of bio-stimulants in combination with reduced tillage, particularly no-tillage, could be beneficial for enzyme activity in a dryland farming system.

Keywords: bio-stimulants, soil microbial enzymes, synthetic agrochemicals, tillage

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Authors: V. Pourmostaghimi, M. Zadshakoyan

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Efficiency and productivity of the finish hard turning can be enhanced impressively by utilizing accurate predictive models for cutting tool wear. However, the ability of genetic programming in presenting an accurate analytical model is a notable characteristic which makes it more applicable than other predictive modeling methods. In this paper, the genetic equation for modeling of tool flank wear is developed with the use of the experimentally measured flank wear values and genetic programming during finish turning of hardened AISI D2. Series of tests were conducted over a range of cutting parameters and the values of tool flank wear were measured. On the basis of obtained results, genetic model presenting connection between cutting parameters and tool flank wear were extracted. The accuracy of the genetically obtained model was assessed by using two statistical measures, which were root mean square error (RMSE) and coefficient of determination (R²). Evaluation results revealed that presented genetic model predicted flank wear over the study area accurately (R² = 0.9902 and RMSE = 0.0102). These results allow concluding that the proposed genetic equation corresponds well with experimental data and can be implemented in real industrial applications.

Keywords: cutting parameters, flank wear, genetic programming, hard turning

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Authors: Soulayma Smirani, Mourad Aidi, Taoufik Aguili

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Energy harvesting has arisen as a prominent research area for low power delivery to RF devices. Rectennas have become a key element in this technology. In this paper, electromagnetic modeling of a rectenna system is presented. In our approach, a hybrid technique was demonstrated to associate both the method of auxiliary sources (MAS) and MoM-GEC (the method of moments combined with the generalized equivalent circuit technique). Auxiliary sources were used in order to substitute specific electronic devices. Therefore, a simple and controllable model is obtained. Also, it can easily be interconnected to form different topologies of rectenna arrays for more energy harvesting. At last, simulation results show the feasibility and simplicity of the proposed rectenna model with high precision and computation efficiency.

Keywords: computational electromagnetics, MoM-GEC method, rectennas, RF energy harvesting

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Authors: Saeed Sayyad Hagh Shomar

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Modeling users’ decisions on departure time choice is the main motivation for this research. In particular, it examines the impact of social-demographic features, household, job characteristics and trip qualities on individuals’ departure time choice. Departure time alternatives are presented as adjacent discrete time periods. The choice between these alternatives is done using a discrete choice model. Since a great deal of early morning trips and traffic congestion at that time of the day comprise work trips, the focus of this study is on the work trip over the entire day. Therefore, this study by using the users’ stated preference in questionnaire models users’ departure time choice affected by congestion pricing schemes in high traffic suburban entrance roads of Tehran. The results demonstrate efficient social-demographic impact on work trips’ departure time. These findings have substantial outcomes for the analysis of transportation planning. Particularly, the analysis shows that ignoring the effects of these variables could result in erroneous information and consequently decisions in the field of transportation planning and air quality would fail and cause financial resources loss.

Keywords: congestion pricing, departure time, modeling, travel timing, time of the day, transportation planning

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Authors: Moustafa Osman Mohammed

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The modeling of a spatial-economic database is crucial in recitation economic network structure to social development. Sustainability within the spatial-economic model gives attention to green businesses to comply with Earth’s Systems. The natural exchange patterns of ecosystems have consistent and periodic cycles to preserve energy and materials flow in systems ecology. When network topology influences formal and informal communication to function in systems ecology, ecosystems are postulated to valence the basic level of spatial sustainable outcome (i.e., project compatibility success). These referred instrumentalities impact various aspects of the second level of spatial sustainable outcomes (i.e., participant social security satisfaction). The sustainability outcomes are modeling composite structure based on a network analysis model to calculate the prosperity of panel databases for efficiency value, from 2005 to 2025. The database is modeling spatial structure to represent state-of-the-art value-orientation impact and corresponding complexity of sustainability issues (e.g., build a consistent database necessary to approach spatial structure; construct the spatial-economic-ecological model; develop a set of sustainability indicators associated with the model; allow quantification of social, economic and environmental impact; use the value-orientation as a set of important sustainability policy measures), and demonstrate spatial structure reliability. The structure of spatial-ecological model is established for management schemes from the perspective pollutants of multiple sources through the input–output criteria. These criteria evaluate the spillover effect to conduct Monte Carlo simulations and sensitivity analysis in a unique spatial structure. The balance within “equilibrium patterns,” such as collective biosphere features, has a composite index of many distributed feedback flows. The following have a dynamic structure related to physical and chemical properties for gradual prolong to incremental patterns. While these spatial structures argue from ecological modeling of resource savings, static loads are not decisive from an artistic/architectural perspective. The model attempts to unify analytic and analogical spatial structure for the development of urban environments in a relational database setting, using optimization software to integrate spatial structure where the process is based on the engineering topology of systems ecology.

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

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Authors: Sina Saadati, Mohammadreza Razzazi

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In this article, we have tried to present an agent-based model of human muscle. A suitable model of muscle is necessary for the analysis of mankind's movements. It can be used by clinical researchers who study the influence of motion sicknesses, like Parkinson's disease. It is also useful in the development of a prosthesis that receives the electromyography signals and generates force as a reaction. Since we have focused on computational efficiency in this research, the model can compute the calculations very fast. As far as it concerns prostheses, the model can be known as a charge-efficient method. In this paper, we are about to illustrate an agent-based model. Then, we will use it to simulate the human gait cycle. This method can also be done reversely in the analysis of gait in motion sicknesses.

Keywords: agent-based modeling and simulation, human muscle, gait cycle, motion sickness

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Authors: Mueller Jann, Hoffmann Christian Hugo

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Conventional quantitative risk management in banking is a risk factor of its own, because it rests on assumptions such as independence and availability of data which do not hold when rare events of extreme consequences are involved. There is a growing recognition of the need for alternative risk measures that do not make these assumptions. We propose a novel method for modeling the risk associated with investment products, in particular derivatives, by using a formal language for specifying financial contracts. Expressions in this language are interpreted in the category of values annotated with (a formal representation of) uncertainty. The choice of uncertainty formalism thus becomes a parameter of the model, so it can be adapted to the particular application and it is not constrained to classical probabilities. We demonstrate our approach using a simple logic-based uncertainty model and a case study in which we assess the risk of counter party default in a portfolio of collateralized loans.

Keywords: risk model, uncertainty monad, derivatives, contract algebra

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Authors: Rayhaneh Amooaghaie, Masoomeh Nabaei

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In this study, 200 µM Cd reduced relative seed germination, root elongation tolerance and seed germination tolerance index of Catharanthus roseus. The melatonin improved seed germination, germination velocity, seedling length and vigor index under Cd stress in a dose-dependent manner and the maximum biological responses obtained by 100 μM melatonin. However, 200-400 μM melatonin and 400 μM SNP had negative effects that evidenced as lower germination indices and poor establishment of seedlings. The cadmium suppressed amylase activity and contents of soluble and reducing sugars in germinating seeds, thereby reduced seed germination and subsequent seedling growth whereas increased electrolyte leakage. These Cd-induced inhibitory effects were ameliorated by melatonin.

Keywords: cadmium, Catharanthus roseus, melatonin, seed germination

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Authors: Virendra J. Majarikar, Harikrishnan N. Unni

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This paper sets to demonstrate a modeling of electrokinetic mixing employing electroosmotic stationary and time-dependent microchannel using alternate zeta patches on the lower surface of the micromixer in a lab on chip microfluidic device. Electroosmotic flow is amplified using different 2D and 3D model designs with alternate and geometric zeta potential values such as 25, 50, and 100 mV, respectively, to achieve high concentration mixing in the electrokinetically-driven microfluidic system. The enhancement of electrokinetic mixing is studied using Finite Element Modeling, and simulation workflow is accomplished with defined integral steps. It can be observed that the presence of alternate zeta patches can help inducing microvortex flows inside the channel, which in turn can improve mixing efficiency. Fluid flow and concentration fields are simulated by solving Navier-Stokes equation (implying Helmholtz-Smoluchowski slip velocity boundary condition) and Convection-Diffusion equation. The effect of the magnitude of zeta potential, the number of alternate zeta patches, etc. are analysed thoroughly. 2D simulation reveals that there is a cumulative increase in concentration mixing, whereas 3D simulation differs slightly with low zeta potential as that of the 2D model within the T-shaped micromixer for concentration 1 mol/m³ and 0 mol/m³, respectively. Moreover, 2D model results were compared with those of 3D to indicate the importance of the 3D model in a microfluidic design process.

Keywords: COMSOL Multiphysics®, electrokinetic, electroosmotic, microfluidics, zeta potential

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Authors: Felix U. Asoiro, Kingsley O. Anyichie, Meshack I. Simeon, Chinenye E. Azuka

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The work was aimed at studying the effects of microwave drying (450 W) and hot air oven drying on the drying kinetics and physico-functional properties of yams and cocoyams species. The yams and cocoyams were cut into chips of thicknesses of 3mm, 5mm, 7mm, 9mm, and 11mm. The drying characteristics of yam and cocoyam chips were investigated under microwave drying and hot air oven temperatures (50oC – 90oC). Drying methods, temperature, and thickness had a significant effect on the drying characteristics and physico-functional properties of yam and cocoyam. The result of the experiment showed that an increase in the temperature increased the drying time. The result also showed that the microwave drying method took lesser time to dry the samples than the hot air oven drying method. The iodine affinity of starch for yam was higher than that of cocoyam for the microwaved dried samples over those of hot air oven-dried samples. The results of the analysis would be useful in modeling the drying behavior of yams and cocoyams under different drying methods. It could also be useful in the improvement of shelf life for yams and cocoyams as well as designs of efficient systems for drying, handling, storage, packaging, processing, and transportation of yams and cocoyams.

Keywords: coco yam, drying, microwave, modeling, energy consumption, iodine affinity, drying ate

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Authors: Csaba Tóth, Éva Lakatos, László Pethő, Seoyoung Cho

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The temperature effect on asphalt pavement structure is a crucial factor at the design stage. In this paper, by applying the German guidelines for temperature along the asphalt depth is estimated. The aim is to consider temperature profiles in different seasons in numerical modelling. The model is built with an elastic and isotropic solid element with 19 subdivisions of asphalt layers to reflect the temperature variation. Comparison with the simple three-layer pavement system (asphalt layers, base, and subgrade layers) will be followed to see the difference in result without temperature variation along with the depth. Finally, the fatigue life calculation was checked to prove the validity of the methodology of considering the temperature in the numerical modelling.

Keywords: temperature profile, flexible pavement modeling, finite element method, temperature modeling

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Authors: P. Shrivastava, A. Shukla, K. Verma, S. Rungta

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Parkinson's disease is a chronic neurological disorder that directly affects human gait. It leads to slowness of movement, causes muscle rigidity and tremors. Gait serve as a primary outcome measure for studies aiming at early recognition of disease. Using gait techniques, this paper implements efficient binary bat algorithm for an early detection of Parkinson's disease by selecting optimal features required for classification of affected patients from others. The data of 166 people, both fit and affected is collected and optimal feature selection is done using PSO and Bat algorithm. The reduced dataset is then classified using neural network. The experiments indicate that binary bat algorithm outperforms traditional PSO and genetic algorithm and gives a fairly good recognition rate even with the reduced dataset.

Keywords: parkinson, gait, feature selection, bat algorithm

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Authors: Sergey M. Karabanov, Dmitry V. Suvorov, Dmitry Yu. Tarabrin

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The operating principle of magnetically controlled microelectromechanical system (MEMS) switches is based on controlling the beam movement under the influence of a magnetic field. Currently, there is a MEMS switch design with a flexible ferromagnetic electrode in the form of a fixed-terminal beam, with an electrode fastened on a straight or cranked anchor. The basic performance characteristics of magnetically controlled MEMS switches (service life, sensitivity, contact resistance, fast response) are largely determined by the flexible electrode design. To ensure the stable and controlled motion of the flexible electrode, it is necessary to provide the optimal design of a flexible electrode.

Keywords: flexible electrode, magnetically controlled MEMS, mathematical modeling, mechanical stress

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Authors: Newton Muhury, Armando A. Apan, Tek Maraseni

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This study modelled the relationships between vegetation response and available water below the soil surface using the Terra’s Moderate Resolution Imaging Spectroradiometer (MODIS) generated Normalised Difference Vegetation Index (NDVI) and soil water content (SWC) data. The Soil & Water Assessment Tool (SWAT) interface known as ArcSWAT was used in ArcGIS for the groundwater analysis. The SWAT model was calibrated and validated in SWAT-CUP software using 10 years (2001-2010) of monthly streamflow data. The average Nash-Sutcliffe Efficiency during the calibration and validation was 0.54 and 0.51, respectively, indicating that the model performances were good. Twenty years (2001-2020) of monthly MODIS NDVI data for three different types of vegetation (forest, shrub, and grass) and soil water content for 43 sub-basins were analysed using the WEKA, machine learning tool with a selection of two supervised machine learning algorithms, i.e., support vector machine (SVM) and random forest (RF). The modelling results show that different types of vegetation response and soil water content vary in the dry and wet season. For example, the model generated high positive relationships (r=0.76, 0.73, and 0.81) between the measured and predicted NDVI values of all vegetation in the study area against the groundwater flow (GW), soil water content (SWC), and the combination of these two variables, respectively, during the dry season. However, these relationships were reduced by 36.8% (r=0.48) and 13.6% (r=0.63) against GW and SWC, respectively, in the wet season. On the other hand, the model predicted a moderate positive relationship (r=0.63) between shrub vegetation type and soil water content during the dry season, which was reduced by 31.7% (r=0.43) during the wet season. Our models also predicted that vegetation in the top location (upper part) of the sub-basin is highly responsive to GW and SWC (r=0.78, and 0.70) during the dry season. The results of this study indicate the study region is suitable for seasonal crop production in dry season. Moreover, the results predicted that the growth of vegetation in the top-point location is highly dependent on groundwater flow in both dry and wet seasons, and any instability or long-term drought can negatively affect these floodplain vegetation communities. This study has enriched our knowledge of vegetation responses to groundwater in each season, which will facilitate better floodplain vegetation management.

Keywords: ArcSWAT, machine learning, floodplain vegetation, MODIS NDVI, groundwater

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Authors: P. Charvin, R. Bourrou, F. Lemont, C. Lafon, A. Russello

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For nuclear waste treatment and confinement, a specific IN-CAN melting module based on low-frequency induction heating have been designed. The frequency of 50Hz has been chosen to improve penetration length through metal. In this design, the liquid metal, strongly stirred by electromagnetic effects, presents shape of a dome caused by strong Laplace forces developing in the bulk of bath. Because of a lower density, the glass phase is located above the metal phase and is heated and stirred by metal through interface. Electric parameters (Intensity, frequency) give precious information about metal load and composition (resistivity of alloy) through impedance modification. Then, power supply can be adapted to energy transfer efficiency for suitable process supervision. Modeling of this system allows prediction of metal dome shape (in agreement with experimental measurement with a specific device), glass and metal velocity, heat and motion transfer through interface. MHD modeling is achieved with COMSOL and Fluent. First, a simplified model is used to obtain the shape of the metal dome. Then the shape is fixed to calculate the fluid flow and the thermal part.

Keywords: electromagnetic stirring, induction heating, interface modeling, metal load

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Authors: Hae-Jun Lee, Ji-Sun Shin, Kyung-Tae Lee

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Potentilla species (Rosasease) have been used in traditional medicine to treat different ailment, disease or malady. In this study, we investigated the anti-inflammatory effects of ethanol extracts of NUTT (EPP) in lipopolysaccharide (LPS)-induced Raw 264.7 macrophages and septic mice. EPP suppressed LPS-induced nitric oxide (NO) and prostaglandin E2 (PGE2) production in LPS-induced Raw 264.7 macrophages. Consistent with these observations, EPP reduced the expressions of inducible nitric oxide synthase (iNOS) and cyclooxygenase-2 (COX-2) by downregulation of their promoter activities. EPP inhibited tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6) and interleukin-1β (IL-1β) at production and mRNA levels. Molecularly, EPP attenuated the LPS-induced transcriptional activity, and DNA-binding activity of nuclear factor-κB (NF-κB), and this was associated with a decrease of translocation and phosphorylation of p65 NF-κB by inhibiting the inhibitory κB-α (IκB-α) degradation and IκB kinase-α/β (IKK-α/β) phosphorylation. Furthermore, EPP suppressed the LPS-induced activation of activator protein-1 (AP-1) by reducing the expression of c-Fos and c-Jun in nuclear. EPP also reduced the phosphorylation of mitogen-activated protein kinase (MAPK), such as p38 MAPK and c-Jun N-terminal kinase/stress-activated protein kinase (JNK). In a sepsis model, pretreatment with EPP reduced the LPS-induced lethality. Collectively, these results suggest that the anti-inflammatory effects of EPP were associated with the suppression of NF-κB and AP-1 activation, and support its possible therapeutic role for the treatment of sepsis.

Keywords: anti-inflammation, activator protein-1, nuclear factor κB, Potentilla paradoxa Nutt

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Authors: Mohamed Rabhi, Kouider Halim Benrahou

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The rheological properties of the carbonyl-methylcellulose (CMC), of different concentrations (25000, 50000, 60000, 80000 and 100000 ppm) and different temperatures were studied. We found that the rheological behavior of all CMC solutions presents a pseudo-plastic behavior, it follows the model of Ostwald-de Waele. The objective of this work is the modeling of flow by the CMC Cross model. The Cross model gives us the variation of the viscosity according to the shear rate. This model allowed us to adjust more clearly the rheological characteristics of CMC solutions. A comparison between the Cross model and the model of Ostwald was made. Cross the model fitting parameters were determined by a numerical simulation to make an approach between the experimental curve and those given by the two models. Our study has shown that the model of Cross, describes well the flow of "CMC" for low concentrations.

Keywords: CMC, rheological modeling, Ostwald model, cross model, viscosity

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Authors: Uzoamaka Nwugo Akwiwu

Abstract:

Human Immunodeficiency Virus (HIV) among rural dwellers depletes quality of agricultural labour, and reduces quality of life. Use of Antiretroviral Therapy (ART) has not significantly reduced consequences of infection, as the effort is being compromised by inadequate dietary intake. This study analysed the dietary intake of People Living with HIV/AIDS (PLWHA) in rural communities of Imo State, Nigeria. Data was collected from 114 PLWHA randomly selected from members of two rural support groups with high prevalence of HIV in Imo State using interview schedule. The data was analysed using descriptive statistics, Pearson product moment correlation, and t-test at α0.05. Level of involvement in agriculture was (mean 12.7) and reduced to 7.0 after infection. Extent of involvement in agriculture significantly reduced after infection in Imo (t=8.1). Health status of 42.1% of PLWHA was perceived as poor. Diet diversity score (4.3±1.6) was low among majority (62.3%) of the PLWHA, with diet of 76.3% being inadequate. However, perceived health status had no significant correlation with dietary intake (r=0.09). The study concluded that diet of PLWHA in Imo State was inadequate, thus there is need for agricultural extension agents to collaborate with the health sector to develop nutritional guideline for PLWHA in rural communities.

Keywords: dietary intake, diet diversity, people living With HIV/AIDS, perceived health status

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Authors: H. Meddah, M. Berediaf-Bourahla, B. El-Djouzi, N. Bourahla

Abstract:

Shear walls made of cold formed steel are used as lateral force resisting components in residential and low-rise commercial and industrial constructions. The seismic design analysis of such structures is often complex due to the slenderness of members and their instability prevalence. In this context, a simplified modeling technique across the panel is proposed by using the finite element method. The approach is based on idealizing the whole panel by a nonlinear shear link element which reflects its shear behavior connected to rigid body elements which transmit the forces to the end elements (studs) that resist the tension and the compression. The numerical model of the shear wall panel was subjected to cyclic loads in order to evaluate the seismic performance of the structure in terms of lateral displacement and energy dissipation capacity. In order to validate this model, the numerical results were compared with those from literature tests. This modeling technique is particularly useful for the design of cold formed steel structures where the shear forces in each panel and the axial forces in the studs can be obtained using spectrum analysis.

Keywords: cold-formed steel, cyclic loading, modeling technique, nonlinear analysis, shear wall panel

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Authors: Barzin Rajabloo, Martin Desilets

Abstract:

First, an electrochemical model for the reduction of CO₂ into CH₃OH is developed in which mass and charge transfer, reactions at the surface of the electrodes and fluid flow of the electrolyte are considered. This mathematical model is developed in COMSOL Multiphysics® where both secondary and tertiary current distribution interfaces are coupled to consider concentrations and potentials inside different parts of the cell. Constant reaction rates are assumed as the fitted parameters to minimize the error between experimental data and modeling results. The model is validated through a comparison with experimental data in terms of faradaic efficiency for production of CH₃OH, the current density in different applied cathode potentials as well as current density in different electrolyte flow rates. The comparison between model outputs and experimental measurements shows a good agreement. The model indicates the higher hydrogen evolution in comparison with CH₃OH production as well as mass transfer limitation caused by CO₂ concentration, which are consistent with findings in the literature. After validating the model, in the second part of the study, some design parameters of the cell, such as cathode geometry and catholyte/anolyte channel widths, are modified to reach better performance and higher faradaic efficiency of methanol production.

Keywords: carbon dioxide, electrochemical reduction, methanol, modeling

Procedia PDF Downloads 109