Search results for: estimation of properties of the model

Authors: Faris A. Uriayer, Mehtab Alam

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The concept of using a hybrid composite by combining two or more different materials to produce bilinear stress–strain behaviour has become a subject of interest. Having studied the mechanical properties of steel-CFRP specimens (CFRP Laminate Sandwiched between Mild Steel Strips), full size steel-CFRP composite reinforcement were fabricated and used as a new reinforcing material inside beams in lieu of traditional steel bars. Four beams, three beams reinforced with steel-CFRP composite reinforcement and one beam reinforced with traditional steel bars were cast, cured and tested under quasi-static loading. The flexural test results of the beams reinforced with this composite reinforcement showed that the beams with steel-CFRP composite reinforcement had comparable flexural strength and flexural ductility with beams reinforced with traditional steel bars.

Keywords: CFRP laminate, steel strip, flexural behaviour, modified model, concrete beam

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Authors: Bashar Mahmoud, Lee Mortimer, Michael Fairweather

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New methods have recently been introduced to improve the thermal property values of molten nitrate salts (a binary mixture of NaNO3:KNO3in 60:40 wt. %), by doping them with minute concentration of nanoparticles in the range of 0.5 to 1.5 wt. % to form the so-called: Nano-heat-transfer-fluid, apt for thermal energy transfer and storage applications. The present study aims to assess the stability of these nanofluids using the advanced computational modelling technique, Lagrangian particle tracking. A multi-phase solid-liquid model is used, where the motion of embedded nanoparticles in the suspended fluid is treated by an Euler-Lagrange hybrid scheme with fixed time stepping. This technique enables measurements of various multi-scale forces whose characteristic (length and timescales) are quite different. Two systems are considered, both consisting of 50 nm Al2O3 ceramic nanoparticles suspended in fluids of different density ratios. This includes both water (5 to 95 °C) and molten nitrate salt (220 to 500 °C) at various volume fractions ranging between 1% to 5%. Dynamic properties of both phases are coupled to the ambient temperature of the fluid suspension. The three-dimensional computational region consists of a 1μm cube and particles are homogeneously distributed across the domain. Periodic boundary conditions are enforced. The particle equations of motion are integrated using the fourth order Runge-Kutta algorithm with a very small time-step, Δts, set at 10-11 s. The implemented technique demonstrates the key dynamics of aggregated nanoparticles and this involves: Brownian motion, soft-sphere particle-particle collisions, and Derjaguin, Landau, Vervey, and Overbeek (DLVO) forces. These mechanisms are responsible for the predictive model of aggregation of nano-suspensions. An energy transport-based method of predicting the thermal conductivity of the nanofluids is also used to determine thermal properties of the suspension. The simulation results confirms the effectiveness of the technique. The values are in excellent agreement with the theoretical and experimental data obtained from similar studies. The predictions indicates the role of Brownian motion and DLVO force (represented by both the repulsive electric double layer and an attractive Van der Waals) and its influence in the level of nanoparticles agglomeration. As to the nano-aggregates formed that was found to play a key role in governing the thermal behavior of nanofluids at various particle concentration. The presentation will include a quantitative assessment of these forces and mechanisms, which would lead to conclusions about nanofluids, heat transfer performance and thermal characteristics and its potential application in solar thermal energy plants.

Keywords: thermal energy storage, molten salt, nano-fluids, multi-scale computational modelling

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Authors: Irfan Ali, Srikant Gupta, Aquil Ahmed

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Every country needs a sustainable development (SD) for its economic growth by forming suitable policies and initiative programs for the development of different sectors of the country. This paper is comprised of modeling and optimization of different sectors of India that form a multi-criterion model. In this paper, we developed a fractional goal programming (FGP) model that helps in providing the efficient allocation of resources simultaneously by achieving the sustainable goals in gross domestic product (GDP), electricity consumption (EC) and greenhouse gasses (GHG) emission by the year 2030. Also, a weighted model of FGP is presented to obtain varying solution according to the priorities set by the policy maker for achieving future goals of GDP growth, EC, and GHG emission. The presented models provide a useful insight to the decision makers for implementing strategies in a different sector.

Keywords: sustainable and economic development, multi-objective fractional programming, fuzzy goal programming, weighted fuzzy goal programming

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Authors: Shuge Lei, Haonan Hu, Dasheng Sun, Huabin Zhang, Kehong Yuan, Jian Dai, Yan Tong

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It remains challenging to measure reliability from classification results from different machine learning models. This paper proposes a reliable soup optimization algorithm based on the model weight fusion algorithm Model Soup, aiming to improve reliability by using dual-channel reliability as the objective function to fuse a series of weights in the breast ultrasound classification models. Experimental results on breast ultrasound clinical datasets demonstrate that reliable soup significantly enhances the reliability of breast ultrasound image classification tasks. The effectiveness of the proposed approach was verified via multicenter trials. The results from five centers indicate that the reliability optimization algorithm can enhance the reliability of the breast ultrasound image classification model and exhibit low multicenter correlation.

Keywords: breast ultrasound image classification, feature attribution, reliability assessment, reliability optimization

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Authors: Faruk Ortes, Derya Karabulut, Yunus Ziya Arslan

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Myoelectric features gathering from musculature environment are considered on a preferential basis to perceive muscle activation and control human arm prostheses according to recent experimental researches. EMG (electromyography) signal based human arm prostheses have shown a promising performance in terms of providing basic functional requirements of motions for the amputated people in recent years. However, these assistive devices for neurorehabilitation still have important limitations in enabling amputated people to perform rather sophisticated or functional movements. Surface electromyogram (EMG) is used as the control signal to command such devices. This kind of control consists of activating a motion in prosthetic arm using muscle activation for the same particular motion. Extraction of clear and certain neural information from EMG signals plays a major role especially in fine control of hand prosthesis movements. Many signal processing methods have been utilized for feature extraction from EMG signals. The specific objective of this study was to compare widely used time domain features of EMG signal including integrated EMG(IEMG), root mean square (RMS) and waveform length(WL) for prediction of externally applied forces to human hands. Obtained features were classified using artificial neural networks (ANN) to predict the forces. EMG signals supplied to process were recorded during only type of muscle contraction which is isometric and isotonic one. Experiments were performed by three healthy subjects who are right-handed and in a range of 25-35 year-old aging. EMG signals were collected from muscles of the proximal part of the upper body consisting of: biceps brachii, triceps brachii, pectorialis major and trapezius. The force prediction results obtained from the ANN were statistically analyzed and merits and pitfalls of the extracted features were discussed with detail. The obtained results are anticipated to contribute classification process of EMG signal and motion control of powered human arm prosthetics control.

Keywords: assistive devices for neurorehabilitation, electromyography, feature extraction, force estimation, human arm prosthesis

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Authors: Moomen Chaari, Wolfgang Ecker, Thomas Kruse, Bogdan-Andrei Tabacaru

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In our daily life, we frequently interact with complex systems which facilitate our mobility, enhance our access to information, and sometimes help us recover from illnesses or diseases. The reliance on these systems is motivated by the established evaluation and assessment procedures which are performed during the different phases of the design and manufacturing flow. Such procedures are aimed to qualify the system’s delivered services with respect to their availability, reliability, safety, and other properties generally referred to as dependability attributes. In this paper, we propose a metamodel based generic characterization of dependability concepts and describe an automation methodology to customize this characterization to different standards and contexts. When integrated in concrete design and verification environments, the proposed methodology promotes the reuse of already available dependability assessment tools and reduces the costs and the efforts required to create consistent and efficient artefacts for fault injection or error simulation.

Keywords: dependability analysis, model-driven development, metamodeling, code generation

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Authors: M. Ramesh Kanthan, S. Naga Nandini Sujatha

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The goal of haze removal algorithms is to enhance and recover details of scene from foggy image. In enhancement the proposed method focus into two main categories: (i) image enhancement based on Adaptive contrast Histogram equalization, and (ii) image edge strengthened Gradient model. Many circumstances accurate haze removal algorithms are needed. The de-fog feature works through a complex algorithm which first determines the fog destiny of the scene, then analyses the obscured image before applying contrast and sharpness adjustments to the video in real-time to produce image the fusion strategy is driven by the intrinsic properties of the original image and is highly dependent on the choice of the inputs and the weights. Then the output haze free image has reconstructed using fusion methodology. In order to increase the accuracy, interpolation method has used in the output reconstruction. A promising retrieval performance is achieved especially in particular examples.

Keywords: single image, fusion, dehazing, multi-scale fusion, per-pixel, weight map

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Authors: M. Ghosh, A. Miroux, L. A. I. Kestens

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At molecular or micrometre scale, practically all materials are neither homogeneous nor isotropic. The concept of texture is used to identify the structural features that cause the properties of a material to be anisotropic. For metallic materials, the anisotropy of the mechanical behaviour originates from the crystallographic nature of plastic deformation, and is therefore controlled by the crystallographic texture. Anisotropy in mechanical properties often constitutes a disadvantage in the application of materials, as it is often illustrated by the earing phenomena during drawing. However, advantages may also be attained when considering other properties (e.g. optimization of magnetic behaviour to a specific direction) by controlling texture through thermo-mechanical processing). Nevertheless, in order to have better control over the final properties it is essential to relate texture with materials processing route and subsequently optimise their performance. However, up to date, few studies have been reported about the evolution of texture in 6061 aluminium alloy during warm processing (from room temperature to 250ºC). In present investigation, recrystallized 6061 aluminium alloy samples were subjected to tensile and plane strain compression (PSC) at room and warm temperatures. The gradual change of texture following both deformation modes were measured and discussed. Tensile tests demonstrate the mechanism at low strain while PSC does the same at high strain and eventually simulate the condition of rolling. Cube dominated texture of the initial rolled and recrystallized AA6061 sheets were replaced by domination of S and R components after PSC at room temperature, warm temperature (250ºC) though did not reflect any noticeable deviation from room temperature observation. It was also noticed that temperature has no significant effect on the evolution of grain morphology during PSC. The band contrast map revealed that after 30% deformation the substructure inside the grain is mainly made of series of parallel bands. A tendency for decrease of Cube and increase of Goss was noticed after tensile deformation compared to as-received material. Like PSC, texture does not change after deformation at warm temperature though. n-fibre was noticed for all the three textures from Goss to Cube.

Keywords: AA 6061, deformation, temperature, tensile, PSC, texture

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Authors: Vaibhav Rathi, Soumen Maity, Achu R. Sekhar, Abhijit Banerjee

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Construction sector in India is extremely resource and carbon intensive. It contributes to significantly to national greenhouse emissions. At the resource end the industry consumes significant portions of the output from mining. Resources such as sand and soil are most exploited and their rampant extraction is becoming constant source of impact on environment and society. Cement is another resource that is used in abundance in building and construction and has a direct impact on limestone resources. Though India is rich in cement grade limestone resource, efforts have to be made for sustainable consumption of this resource to ensure future availability. Use of these resources in high volumes in India is a result of rapid urbanization. More cities have grown to a population of million plus in the last decade and million plus cities are growing further. To cater to needs of growing urban population of construction activities are inevitable in the coming future thereby increasing material consumption. Increased construction will also lead to substantial increase in end of life waste generation from Construction and Demolition (C&D). Therefore proper management of C&D waste has the potential to reduce environmental pollution as well as contribute to the resource efficiency in the construction sector. The present study deals with estimation, characterisation and documenting current management practices of C&D waste in 10 Indian cities of different geographies and classes. Based on primary data the study draws conclusions on the potential of C&D waste to be used as an alternative to primary raw materials. The estimation results show that India generates 716 million tons of C&D waste annually, placing the country as second largest C&D waste generator in the world after China. The study also aimed at utilization of C&D waste in to building materials. The waste samples collected from various cities have been used to replace 100% stone aggregates in paver blocks without any decrease in strength. However, management practices of C&D waste in cities still remains poor instead of notification of rules and regulations notified for C&D waste management. Only a few cities have managed to install processing plant and set up management systems for C&D waste. Therefore there is immense opportunity for management and reuse of C&D waste in Indian cities.

Keywords: building materials, construction and demolition waste, cities, environmental pollution, resource efficiency

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Authors: Josef Novák, Alena Kohoutková

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The performance of concrete structures in fire depends on several factors which include, among others, the change in material properties due to the fire. Today, fiber reinforced concrete (FRC) belongs to materials which have been widely used for various structures and elements. While the knowledge and experience with FRC behavior under ambient temperature is well-known, the effect of elevated temperature on its behavior has to be deeply investigated. This paper deals with an experimental investigation and stress‑strain relations for hybrid fiber reinforced concrete (HFRC) which contains siliceous aggregates, polypropylene and steel fibers. The main objective of the experimental investigation is to enhance a database of mechanical properties of concrete composites with addition of fibers subject to elevated temperature as well as to validate existing stress-strain relations for HFRC. Within the investigation, a unique heat transport test, compressive test and splitting tensile test were performed on 150 mm cubes heated up to 200, 400, and 600 °C with the aim to determine a time period for uniform heat distribution in test specimens and the mechanical properties of the investigated concrete composite, respectively. Both findings obtained from the presented experimental test as well as experimental data collected from scientific papers so far served for validating the computational accuracy of investigated stress-strain relations for HFRC which have been developed during last few years. Owing to the presence of steel and polypropylene fibers, HFRC becomes a unique material whose structural performance differs from conventional plain concrete when exposed to elevated temperature. Polypropylene fibers in HFRC lower the risk of concrete spalling as the fibers burn out shortly with increasing temperature due to low ignition point and as a consequence pore pressure decreases. On the contrary, the increase in the concrete porosity might affect the mechanical properties of the material. To validate this thought requires enhancing the existing result database which is very limited and does not contain enough data. As a result of the poor database, only few stress-strain relations have been developed so far to describe the structural performance of HFRC at elevated temperature. Moreover, many of them are inconsistent and need to be refined. Most of them also do not take into account the effect of both a fiber type and fiber content. Such approach might be vague especially when high amount of polypropylene fibers are used. Therefore, the existing relations should be validated in detail based on other experimental results.

Keywords: elevated temperature, fiber reinforced concrete, mechanical properties, stress strain relation

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Authors: Manouchehr Amiri

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This article introduces a general notion of physical bit information that is compatible with the basics of quantum mechanics and incorporates the Shannon entropy as a special case. This notion of physical information leads to the Binary data matrix model (BDM), which predicts the basic results of quantum mechanics, general relativity, and black hole thermodynamics. The compatibility of the model with holographic, information conservation, and Landauer’s principles are investigated. After deriving the “Bit Information principle” as a consequence of BDM, the fundamental equations of Planck, De Broglie, Beckenstein, and mass-energy equivalence are derived.

Keywords: physical theory of information, binary data matrix model, Shannon information theory, bit information principle

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Authors: Slim Chokri

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Load forecasting is one of the central functions in power systems operations. Electricity cannot be stored, which means that for electric utility, the estimate of the future demand is necessary in managing the production and purchasing in an economically reasonable way. A majority of the recently reported approaches are based on neural network. The attraction of the methods lies in the assumption that neural networks are able to learn properties of the load. However, the development of the methods is not finished, and the lack of comparative results on different model variations is a problem. This paper presents a new approach in order to predict the Tunisia daily peak load. The proposed method employs a computational intelligence scheme based on the Fuzzy neural network (FNN) and support vector regression (SVR). Experimental results obtained indicate that our proposed FNN-SVR technique gives significantly good prediction accuracy compared to some classical techniques.

Keywords: neural network, load forecasting, fuzzy inference, machine learning, fuzzy modeling and rule extraction, support vector regression

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Authors: Elsheikh Asser

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Time and cost are the main goals of the construction project management. The first schedule developed may not be a suitable schedule for beginning or completing the project to achieve the target completion time at a minimum total cost. In general, there are trade-offs between time and cost (TCT) to complete the activities of a project. This research presents genetic algorithms (GAs) multi-objective model for project scheduling considering different scenarios such as least cost, least time, and target time.

Keywords: genetic algorithms, time-cost trade-off, multi-objective model, project scheduling

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Authors: Jenny Radeva, Anke-Gundula Roth, Christian Goebbert, Robert Niestroj-Pahl, Lars Daehne, Axel Wolfram, Juergen WIese

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The presented investigation studies the correlation between the process parameters of Layer-by-Layer (LbL) coatings and properties of the produced hybrid membranes for water treatment. The coating of alumina ceramic support membrane with polyelectrolyte multilayers on top results in hybrid membranes with increased fouling resistant behavior, high retention (up to 90%) of salt ions and various pharmaceuticals, selectivity to various organic molecules as known from LbL coated polyether sulfone membranes and the possibility of pH response control. Chosen polyelectrolytes were added to the support using the LbL-coating process. Parameters like the type of polyelectrolyte, ionic strength, and pH were varied in order to find the most suitable process conditions and to study how they influence the properties of the final product. The applied LbL-films was investigated in respect to its homogeneity and penetration depth. The analysis of the layer buildup was performed using fluorescence labeled polyelectrolyte molecules and Confocal Laser Scanning Microscopy as well as Scanning and Transmission Electron Microscopy. Furthermore, the influence of the coating parameters on the porosity, surface potential, retention, and permeability of the developed hybrid membranes were estimated. In conclusion, a comparison was drawn between the filtration performance of the uncoated alumina ceramic membrane and modified hybrid membranes.

Keywords: water treatment, membranes, ceramic membranes, hybrid membranes, layer-by-layer modification

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Authors: Saeed Qaisrani

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The study was conducted to observe carbon and nutrient loss by burning of rice residues on rice-wheat cropping system The rice crop was harvested to conduct the experiment in a randomized complete block design (RCBD) with factors and 4 replications with a net plot size of 10 m x 20 m. Rice stubbles were managed by two methods i.e. Incorporation & burning of rice residues. Soil samples were taken to a depth of 30 cm before sowing & after harvesting of wheat. Wheat was sown after harvesting of rice by three practices i.e. Conventional tillage, Minimum tillage and Zero tillage to observe best tillage practices. Laboratory and field experiments were conducted on wheat to assess best tillage practice and residues management method with estimation of carbon losses. Data on the following parameters; establishment count, plant height, spike length, number of grains per spike, biological yield, fat content, carbohydrate content, protein content, and harvest index were recorded to check wheat quality & ensuring food security in the region. Soil physico-chemical analysis i.e. pH, electrical conductivity, organic matter, nitrogen, phosphorus, potassium, and carbon were done in soil fertility laboratory. Substantial results were found on growth, yield and related parameters of wheat crop. The collected data were examined statistically with economic analysis to estimate the cost-benefit ratio of using different tillage techniques and residue management practices. Obtained results depicted that Zero tillage method have positive impacts on growth, yield and quality of wheat, Moreover, it is cost effective methodology. Similarly, Incorporation is suitable and beneficial method for soil due to more nutrients provision and reduce the need of fertilizers. Burning of rice stubbles has negative impact including air pollution, nutrient loss, microbes died and carbon loss. Recommended the zero tillage technology to reduce carbon losses along with food security in Pakistan.

Keywords: agricultural agronomy, food security, carbon sequestration, rice-wheat cropping system

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Authors: Babak H. Tabrizi, Seyed Farid Ghaderi

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Concurrent planning of the resource constraint project scheduling and material ordering problems have received significant attention within the last decades. Hence, the issue has been investigated here with the aim to minimize total project costs. Furthermore, the presented model considers different discount options in order to approach the real world conditions. The incorporated alternatives consist of all-unit and incremental discount strategies. On the other hand, a modified version of the genetic algorithm is applied in order to solve the model for larger sizes, in particular. Finally, the applicability and efficiency of the given model is tested by different numerical instances.

Keywords: genetic algorithm, material ordering, project management, project scheduling

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Authors: Meltem Agar, Maisem Laabei, Hannah Leese, Pedro Estrela

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Pathogenic bacteria and the diseases they cause have become a global problem. Their early detection is vital and can only be possible by detecting the bacteria causing the disease accurately and rapidly. Great progress has been made in this field with the use of biosensors. Molecularly imprinted polymers have gain broad interest because of their excellent properties over natural receptors, such as being stable in a variety of conditions, inexpensive, biocompatible and having long shelf life. These properties make molecularly imprinted polymers an attractive candidate to be used in biosensors. In this study it is aimed to produce an aptamer-molecularly imprinted polymer based electrochemical sensor by utilizing the properties of molecularly imprinted polymers coupled with the enhanced specificity offered by DNA aptamers. These ‘apta-MIP’ sensors were used for the detection of Staphylococcus aureus and Escherichia coli. The experimental parameters for the fabrication of sensor were optimized, and detection of the bacteria was evaluated via Electrochemical Impedance Spectroscopy. Sensitivity and selectivity experiments were conducted. Furthermore, molecularly imprinted polymer only and aptamer only electrochemical sensors were produced separately, and their performance were compared with the electrochemical sensor produced in this study. Aptamer-molecularly imprinted polymer based electrochemical sensor showed good sensitivity and selectivity in terms of detection of Staphylococcus aureus and Escherichia coli. The performance of the sensor was assessed in buffer solution and tap water.

Keywords: aptamer, electrochemical sensor, staphylococcus aureus, molecularly imprinted polymer

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Authors: Mahesh Kothari, K. D. Gharde

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The ANN and fuzzy logic (FL) models were developed to predict the runoff and sediment yield for catchment of Kal river, India using 21 years (1991 to 2011) rainfall and other hydrological data (evaporation, temperature and streamflow lag by one and two day) and 7 years data for sediment yield modelling. The ANN model performance improved with increasing the input vectors. The fuzzy logic model was performing with R value more than 0.95 during developmental stage and validation stage. The comparatively FL model found to be performing well to ANN in prediction of runoff and sediment yield for Kal river.

Keywords: transferred function, sigmoid, backpropagation, membership function, defuzzification

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Authors: Kanchan Vishwakarma, Shivesh Sharma, Nitin Kumar

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Soil is incoherent matter on Earth’s surface having organic and mineral content. The spatial variation of 4 soil enzyme activities and microbial biomass were assessed for two seasons’ viz. monsoon and winter along the latitudinal gradient in North-central India as the area of this study is fettered with respect to national status. The study was facilitated to encompass the effect of climate change, enzyme activity and biomass on nutrient cycling. Top soils were sampled from 4 sites in North-India. There were significant correlations found between organic C, N & P wrt to latitude gradient in two seasons. This distribution of enzyme activities and microbial biomass was consequence of alterations in temperature and moisture of soil because of which soil properties change along the latitude transect.

Keywords: latitude gradient, microbial biomass, moisture, soil, organic carbon, temperature

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Authors: Rodrigo T. Sepulveda-Hirose, Ana B. Carrera-Aguilar, Francisco Andree Ramirez-Casas, Alondra Orozco-Gomez, Miguel Angel Sanchez-Caro, Carlos Herrera-Ventosa

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High concentrations of particulate matter in the atmosphere pose a threat to human health, especially over areas with high concentrations of population; however, field air pollution monitoring is expensive and time-consuming. In order to achieve reduced costs and global coverage of the whole urban area, remote sensing can be used. This study evaluates PM2.5 concentrations, over the Mexico City´s metropolitan area, are estimated using atmospheric reflectance from LANDSAT 8, satellite imagery and historical PM2.5 measurements of the Automatic Environmental Monitoring Network of Mexico City (RAMA). Through the processing of the available satellite images, a preliminary model was generated to evaluate the optimal bands for the generation of the final model for Mexico City. Work on the final model continues with the results of the preliminary model. It was found that infrared bands have helped to model in other cities, but the effectiveness that these bands could provide for the geographic and climatic conditions of Mexico City is still being evaluated.

Keywords: air pollution modeling, Landsat 8, PM2.5, remote sensing

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Authors: Virginia Martin Torrejon, Song Hang

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Gelatine foams are widely explored materials due to their biodegradability, biocompatibility, and availability. They exhibit outstanding properties and are currently subject to increasing scientific research due to their potential use in different applications, such as biocompatible cellular materials for biomedical products or biofoams as an alternative to fossil-fuel-derived packaging. Gelatine is a highly surface-active polymer, and its concentrated solutions usually do not require surfactants to achieve low surface tension. Still, anionic surfactants like sodium dodecyl sulfate (SDS) strongly interact with gelatine, impacting its viscosity and rheological properties and, in turn, their foaming behaviour. Foaming behaviour is a key parameter for cellular solids produced by mechanical foaming as it has a significant effect on the processing and properties of cellular materials. Foamability mainly impacts the density and the mechanical properties of the foams, while foam stability is crucial to achieving foams with low shrinkage and desirable pore morphology. This work aimed to investigate the influence of SDS on the foaming behaviour of concentrated gelatine foams by using a dynamic foam analyser. The study of maximum foam height created, foam formation behaviour, drainage behaviour, and foam structure with regard to bubble size and distribution were carried out in 10 wt% gelatine solutions prepared at different SDS/gelatine concentration ratios. Comparative rheological and viscometry measurements provided a good correlation with the data from the dynamic foam analyser measurements. SDS incorporation at optimum dosages and gelatine gelation led to highly stable foams at high expansion ratios. The viscosity increase of the hydrogel solution at SDS content increased was a key parameter for foam stabilization. In addition, the impact of SDS content on gelling time and gel strength also considerably impacted the foams' stability and pore structure.

Keywords: dynamic foam analyser, gelatine foams stability and foamability, gelatine-surfactant foams, gelatine-SDS rheology, gelatine-SDS viscosity

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Authors: Alia Abdul Ghaffar, Tom Richardson

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A model reference adaptive control and a fixed gain LQR control were implemented in the height controller of a quadrotor that has parametric uncertainties due to the act of picking up an object of unknown dimension and mass. It is shown that an adaptive control, unlike a fixed gain control, is capable of ensuring a stable tracking performance under such condition, although adaptive control suffers from several limitations. The combination of both adaptive and fixed gain control in the controller architecture results in an enhanced tracking performance in the presence of parametric uncertainties.

Keywords: UAV, quadrotor, robotic arm augmentation, model reference adaptive control, LQR control

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Authors: Z. Karahaliloğlu, C. Hacker, M. Demirbilek, G. Seide, E. B. Denkbaş, T. Gries

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Currently, textile industry has played an important role in world’s economy, especially in developing countries. Dyes and pigments used in textile industry are significant pollutants. Most of theirs are azo dyes that have chromophore (-N=N-) in their structure. There are many methods for removal of the dyes from wastewater such as chemical coagulation, flocculation, precipitation and ozonation. But these methods have numerous disadvantages and alternative methods are needed for wastewater decolorization. Titanium-mediated photodegradation has been used generally due to non-toxic, insoluble, inexpensive, and highly reactive properties of titanium dioxide semiconductor (TiO2). Melt electrospinning is an attractive manufacturing process for thin fiber production through electrospinning from PP (Polyprophylene). PP fibers have been widely used in the filtration due to theirs unique properties such as hydrophobicity, good mechanical strength, chemical resistance and low-cost production. In this study, we aimed to investigate the effect of titanium nanoparticle localization and amine modification on the dye degradation. The applicability of the prepared chemical activated composite and pristine fabrics for a novel treatment of dyeing wastewater were evaluated.In this study, a photocatalyzer material was prepared from nTi (titanium dioxide nanoparticles) and PP by a melt-electrospinning technique. The electrospinning parameters of pristine PP and PP/nTi nanocomposite fabrics were optimized. Before functionalization with nTi, the surface of fabrics was activated by a technique using glutaraldehyde (GA) and polyethyleneimine to promote the dye degredation. Pristine PP and PP/nTi nanocomposite melt-electrospun fabrics were characterized using scanning electron microscopy (SEM) and X-Ray Photon Spectroscopy (XPS). Methyl orange (MO) was used as a model compound for the decolorization experiments. Photocatalytic performance of nTi-loaded pristine and nanocomposite melt-electrospun filters was investigated by varying initial dye concentration 10, 20, 40 mg/L). nTi-PP composite fabrics were successfully processed into a uniform, fibrous network of beadless fibers with diameters of 800±0.4 nm. The process parameters were determined as a voltage of 30 kV, a working distance of 5 cm, a temperature of the thermocouple and hotcoil of 260–300 ºC and a flow rate of 0.07 mL/h. SEM results indicated that TiO2 nanoparticles were deposited uniformly on the nanofibers and XPS results confirmed the presence of titanium nanoparticles and generation of amine groups after modification. According to photocatalytic decolarization test results, nTi-loaded GA-treated pristine or nTi-PP nanocomposite fabric filtern have superior properties, especially over 90% decolorization efficiency at GA-treated pristine and nTi-PP composite PP fabrics. In this work, as a photocatalyzer for wastewater treatment, surface functionalized with nTi melt-electrospun fabrics from PP were prepared. Results showed melt-electrospun nTi-loaded GA-tretaed composite or pristine PP fabrics have a great potential for use as a photocatalytic filter to decolorization of wastewater and thus, requires further investigation.

Keywords: titanium oxide nanoparticles, polyprophylene, melt-electrospinning

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Authors: Manish Gupta

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Following the E-Commerce era, M-Commerce is the next big phase in the technology involvement and advancement. This paper intends to explore how Indian consumers are influenced to adopt the M-commerce. In this paper, the revised Technology Acceptance Model (TAM) has been presented on the basis of the most dominant factors that affect the adoption of M-Commerce in Indian scenario. Furthermore, an analytical questionnaire approach was carried out to collect data from Indian consumers. These collected data were further used for the validation of the presented model. Findings indicate that customization, convenience, instant connectivity, compatibility, security, download speed in M-Commerce affect the adoption behavior. Furthermore, the findings suggest that perceived usefulness and attitude towards M-Commerce are positively influenced by number of M-Commerce drivers (i.e. download speed, compatibility, convenience, security, customization, connectivity, and input mechanism).

Keywords: M-Commerce, perceived usefulness, technology acceptance model, perceived ease of use

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Authors: Shengzhu Cao, Hui Zhou, Gan Wu, Lanxi Wanhg, Kaifeng Zhang, Rui Wang, Hu Wang

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The functional micro and nanostructures, which can endow material surface with unique properties such as super-absorptance, hydrophobic and drag reduction. Recently, femtosecond laser ablation has been demonstrated to be a promising technology for surface functional micro and nanostructures fabrication. In this paper, using femtosecond laser ablation processing technique, we fabricated functional micro and nanostructures on Ti and Al alloy surfaces, test results showed that processed surfaces have 82%~96% absorptance over a broad wavelength range from ultraviolet to infrared. The surface function properties, which determined by micro and nanostructures, could be modulated by variation laser parameters. These functional surfaces may find applications in such areas as photonics, plasmonics, spaceborne devices, thermal radiation sources, solar energy absorbers and biomedicine.

Keywords: surface functional, micro and nanostructures, femtosecond laser, ablation

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Authors: Shir Daphna-Tekoah, Nurit Eitan-Gutman, Uri Balla

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Background: Systemic documentation is essential in social work practice. Collaboration between an institution of higher education and social work health care services enabled adaptation of the medical documentation model of SOAP in the field of social work, by creating the ISOAPS model (Introduction, Subjective, Objective, Assessment, Plan, Summary) model. Aims: The article describes the ISOAPS model and its implementation in the field of social work, as a tool for standardization of documentation and the enhancement of multidisciplinary collaboration. Methods: We examined the changes in standardization using a mixed methods study, both before and after implementation of the model. A review of social workers’ documentation was carried out by medical staff and social workers in the Clalit Healthcare Services, the largest provider of public and semi-private health services in Israel. After implementation of the model, semi-structured qualitative interviews were undertaken. Main findings: The percentage of reviewers who evaluated their documentation as correct increased from 46%, prior to implementation, to 61% after implementation. After implementation, 81% of the social workers noted that their documentation had become standardized. The training process prepared them for the change in documentation and most of them (83%) started using the model on a regular basis. The qualitative data indicate that the use of the ISOAPS model creates uniform documentation, improves standards and is important to teach social work students. Conclusions: The ISOAPS model standardizes documentation and promotes communication between social workers and medical staffs. Implications for practice: In the intricate realm of healthcare, efficient documentation systems are pivotal to ensuring coherent interdisciplinary communication and patient care. The ISOAPS model emerges as a quintessential instrument, meticulously tailored to the nuances of social work documentation. While it extends its utility across the broad spectrum of social work, its specificity is most pronounced in the medical domain. This model not only exemplifies rigorous academic and professional standards but also serves as a testament to the potential of contextualized documentation systems in elevating the overall stature of social work within healthcare. Such a strategic documentation tool can not only streamline the intricate processes inherent in medical social work but also underscore the indispensable role that social workers play in the broader healthcare ecosystem.

Keywords: ISOAPS, professional documentation, medial social-work, social work

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Authors: P. V. Pramila , V. Mahesh

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Pulmonary Function Tests are important non-invasive diagnostic tests to assess respiratory impairments and provides quantifiable measures of lung function. Spirometry is the most frequently used measure of lung function and plays an essential role in the diagnosis and management of pulmonary diseases. However, the test requires considerable patient effort and cooperation, markedly related to the age of patients esulting in incomplete data sets. This paper presents, a nonlinear model built using Multivariate adaptive regression splines and Random forest regression model to predict the missing spirometric features. Random forest based feature selection is used to enhance both the generalization capability and the model interpretability. In the present study, flow-volume data are recorded for N= 198 subjects. The ranked order of feature importance index calculated by the random forests model shows that the spirometric features FVC, FEF 25, PEF,FEF 25-75, FEF50, and the demographic parameter height are the important descriptors. A comparison of performance assessment of both models prove that, the prediction ability of MARS with the `top two ranked features namely the FVC and FEF 25 is higher, yielding a model fit of R2= 0.96 and R2= 0.99 for normal and abnormal subjects. The Root Mean Square Error analysis of the RF model and the MARS model also shows that the latter is capable of predicting the missing values of FEV1 with a notably lower error value of 0.0191 (normal subjects) and 0.0106 (abnormal subjects). It is concluded that combining feature selection with a prediction model provides a minimum subset of predominant features to train the model, yielding better prediction performance. This analysis can assist clinicians with a intelligence support system in the medical diagnosis and improvement of clinical care.

Keywords: FEV, multivariate adaptive regression splines pulmonary function test, random forest

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Authors: S. Hasan, I. Beshara

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Infrastructure maintenance is a great challenge facing sustainable development of infrastructure assets due to the high cost of passive implementation of a sustainable maintenance plan. An assessment model of sustainable maintenance for highway infrastructure projects in Egypt is developed in this paper. It helps in improving the implementation of sustainable maintenance criteria. Thus, this paper has applied the analytical hierarchy processes (AHP) to rank and explore the weight of 26 assessment indicators using three hierarchy levels containing the main sustainable categories and subcategories with related indicators. Overall combined weight of each indicator for sustainable maintenance evaluation has been calculated to sum up to a sustainable maintenance performance index (SMI). The results show that the factor "Preventive maintenance cost" has the highest relative contribution factor among others (13.5%), while two factors of environmental performance have the least weights (0.7%). The developed model aims to provide decision makers with information about current maintenance performance and support them in the decision-making process regarding future directions of maintenance activities. It can be used as an assessment performance tool during the operation and maintenance stage. The developed indicators can be considered during designing the maintenance plan. Practices for successful implementation of the model are also presented.

Keywords: analytical hierarchy process, assessment performance Model, KPIs for sustainable maintenance, sustainable maintenance index

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Authors: Sahbi Farhani

Abstract:

This study investigates the relationship between external debt and military spending in case of India over the period of 1970–2012. In doing so, we have applied the structural break unit root tests to examine stationarity properties of the variables. The Auto-Regressive Distributed Lag (ARDL) bounds testing approach is used to test whether cointegration exists in presence of structural breaks stemming in the series. Our results indicate the cointegration among external debt, military spending, debt servicing, and economic growth. Moreover, military spending and debt servicing add in external debt. Economic growth helps in lowering external debt. The Vector Error Correction Model (VECM) analysis and Granger causality test reveal that military spending and economic growth cause external debt. The feedback effect also exists between external debt and debt servicing in case of India.

Keywords: external debt, military spending, ARDL approach, India

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Authors: Ge Zheng, Jun Peng

Abstract:

Unbalanced power output from individual cells of Proton Exchange Membrane Fuel Cell (PEMFC) has direct effects on PEMFC stack performance, in particular under transient operation. In the paper, a multi-layer ANN (Artificial Neural Network) model Radial Basis Functions (RBF) has been developed for predicting cells' output profiles by applying gas supply parameters, cooling conditions, temperature measurement of individual cells, etc. The feed-forward ANN model was validated with experimental data. Influence of relevant parameters of RBF on the network accuracy was investigated. After adequate model training, the modelling results show good correspondence between actual measurements and reconstructed output profiles. Finally, after the model was used to optimize the stack output performance under steady-state and transient operating conditions, it suggested that the developed ANN control model can help PEMFC stack to have obvious improvement on power output under fast acceleration process.

Keywords: proton exchange membrane fuel cell, PEMFC, artificial neural network, ANN, cell output profile, transient

Procedia PDF Downloads 157