Search results for: monitoring and modeling
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 6744

Search results for: monitoring and modeling

2514 The Impact of Sustainable Packaging on Customers’ Willingness to Buy: A Study Based in Rwanda

Authors: Nirere Martine

Abstract:

Purpose –The purpose of this study aims to understand the intention of customers to adopt sustainable packaging and the impact of sustainable packaging on customers’ willingness to buy a product using sustainable packaging. Design/methodology/approach – A new research model based on the technology acceptance model (TAM) and structural equation modeling are used to examine causality and test relationship based on the data collected from 251 Rwanda samples. Findings – The findings indicated that perceived ease of use positively affects perceived usefulness. However, perceived usefulness and perceived ease of use positively affect the intention to adopt sustainable packaging. However, perceived risk and perceived cost negatively affect the intention to adopt sustainable packaging. The intention to adopt sustainable packaging positively affects the willingness to buy a product using sustainable packaging. Originality/value – Many researchers have investigated the issue of a consumers’ behavior to purchase a product. In particular, they have examined whether customers are willing to pay extra for a packaging product. There has been no study that has examined the impact of sustainable packaging on customers’ willingness to buy. The results of this study can help manufacturers form a better understanding of customers’ willingness to purchase a product using sustainable packaging.

Keywords: consumers’ behavioral, sustainable packaging, TAM, Rwanda

Procedia PDF Downloads 174
2513 Comparative Analysis of the Computer Methods' Usage for Calculation of Hydrocarbon Reserves in the Baltic Sea

Authors: Pavel Shcherban, Vlad Golovanov

Abstract:

Nowadays, the depletion of hydrocarbon deposits on the land of the Kaliningrad region leads to active geological exploration and development of oil and natural gas reserves in the southeastern part of the Baltic Sea. LLC 'Lukoil-Kaliningradmorneft' implements a comprehensive program for the development of the region's shelf in 2014-2023. Due to heterogeneity of reservoir rocks in various open fields, as well as with ambiguous conclusions on the contours of deposits, additional geological prospecting and refinement of the recoverable oil reserves are carried out. The key element is use of an effective technique of computer stock modeling at the first stage of processing of the received data. The following step uses information for the cluster analysis, which makes it possible to optimize the field development approaches. The article analyzes the effectiveness of various methods for reserves' calculation and computer modelling methods of the offshore hydrocarbon fields. Cluster analysis allows to measure influence of the obtained data on the development of a technical and economic model for mining deposits. The relationship between the accuracy of the calculation of recoverable reserves and the need of modernization of existing mining infrastructure, as well as the optimization of the scheme of opening and development of oil deposits, is observed.

Keywords: cluster analysis, computer modelling of deposits, correction of the feasibility study, offshore hydrocarbon fields

Procedia PDF Downloads 156
2512 Developing and Evaluating Clinical Risk Prediction Models for Coronary Artery Bypass Graft Surgery

Authors: Mohammadreza Mohebbi, Masoumeh Sanagou

Abstract:

The ability to predict clinical outcomes is of great importance to physicians and clinicians. A number of different methods have been used in an effort to accurately predict these outcomes. These methods include the development of scoring systems based on multivariate statistical modelling, and models involving the use of classification and regression trees. The process usually consists of two consecutive phases, namely model development and external validation. The model development phase consists of building a multivariate model and evaluating its predictive performance by examining calibration and discrimination, and internal validation. External validation tests the predictive performance of a model by assessing its calibration and discrimination in different but plausibly related patients. A motivate example focuses on prediction modeling using a sample of patients undergone coronary artery bypass graft (CABG) has been used for illustrative purpose and a set of primary considerations for evaluating prediction model studies using specific quality indicators as criteria to help stakeholders evaluate the quality of a prediction model study has been proposed.

Keywords: clinical prediction models, clinical decision rule, prognosis, external validation, model calibration, biostatistics

Procedia PDF Downloads 284
2511 Mathematical Modeling of Thin Layer Drying Behavior of Bhimkol (Musa balbisiana) Pulp

Authors: Ritesh Watharkar, Sourabh Chakraborty, Brijesh Srivastava

Abstract:

Reduction of water from the fruits and vegetables using different drying techniques is widely employed to prolong the shelf life of these food commodities. Heat transfer occurs inside the sample by conduction and mass transfer takes place by diffusion in accordance with temperature and moisture concentration gradient respectively during drying. This study was undertaken to study and model the thin layer drying behavior of Bhimkol pulp. The drying was conducted in a tray drier at 500c temperature with 5, 10 and 15 % concentrations of added maltodextrin. The drying experiments were performed at 5mm thickness of the thin layer and the constant air velocity of 0.5 m/s.Drying data were fitted to different thin layer drying models found in the literature. Comparison of fitted models was based on highest R2(0.9917), lowest RMSE (0.03201), and lowest SSE (0.01537) revealed Middle equation as the best-fitted model for thin layer drying with 10% concentration of maltodextrin. The effective diffusivity was estimated based on the solution of Fick’s law of diffusion which is found in the range of 3.0396 x10-09 to 5.0661 x 10-09. There was a reduction in drying time with the addition of maltodextrin as compare to the raw pulp.

Keywords: Bhimkol, diffusivity, maltodextrine, Midilli model

Procedia PDF Downloads 195
2510 Support Vector Regression Combined with Different Optimization Algorithms to Predict Global Solar Radiation on Horizontal Surfaces in Algeria

Authors: Laidi Maamar, Achwak Madani, Abdellah El Ahdj Abdellah

Abstract:

The aim of this work is to use Support Vector regression (SVR) combined with dragonfly, firefly, Bee Colony and particle swarm Optimization algorithm to predict global solar radiation on horizontal surfaces in some cities in Algeria. Combining these optimization algorithms with SVR aims principally to enhance accuracy by fine-tuning the parameters, speeding up the convergence of the SVR model, and exploring a larger search space efficiently; these parameters are the regularization parameter (C), kernel parameters, and epsilon parameter. By doing so, the aim is to improve the generalization and predictive accuracy of the SVR model. Overall, the aim is to leverage the strengths of both SVR and optimization algorithms to create a more powerful and effective regression model for various cities and under different climate conditions. Results demonstrate close agreement between predicted and measured data in terms of different metrics. In summary, SVM has proven to be a valuable tool in modeling global solar radiation, offering accurate predictions and demonstrating versatility when combined with other algorithms or used in hybrid forecasting models.

Keywords: support vector regression (SVR), optimization algorithms, global solar radiation prediction, hybrid forecasting models

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2509 The Use of the TRIGRS Model and Geophysics Methodologies to Identify Landslides Susceptible Areas: Case Study of Campos do Jordao-SP, Brazil

Authors: Tehrrie Konig, Cassiano Bortolozo, Daniel Metodiev, Rodolfo Mendes, Marcio Andrade, Marcio Moraes

Abstract:

Gravitational mass movements are recurrent events in Brazil, usually triggered by intense rainfall. When these events occur in urban areas, they end up becoming disasters due to the economic damage, social impact, and loss of human life. To identify the landslide-susceptible areas, it is important to know the geotechnical parameters of the soil, such as cohesion, internal friction angle, unit weight, hydraulic conductivity, and hydraulic diffusivity. The measurement of these parameters is made by collecting soil samples to analyze in the laboratory and by using geophysical methodologies, such as Vertical Electrical Survey (VES). The geophysical surveys analyze the soil properties with minimal impact in its initial structure. Statistical analysis and mathematical models of physical basis are used to model and calculate the Factor of Safety for steep slope areas. In general, such mathematical models work from the combination of slope stability models and hydrological models. One example is the mathematical model TRIGRS (Transient Rainfall Infiltration and Grid-based Regional Slope- Stability Model) which calculates the variation of the Factor of Safety of a determined study area. The model relies on changes in pore-pressure and soil moisture during a rainfall event. TRIGRS was written in the Fortran programming language and associates the hydrological model, which is based on the Richards Equation, with the stability model based on the principle of equilibrium limit. Therefore, the aims of this work are modeling the slope stability of Campos do Jordão with TRIGRS, using geotechnical and geophysical methodologies to acquire the soil properties. The study area is located at southern-east of Sao Paulo State in the Mantiqueira Mountains and has a historic landslide register. During the fieldwork, soil samples were collected, and the VES method applied. These procedures provide the soil properties, which were used as input data in the TRIGRS model. The hydrological data (infiltration rate and initial water table height) and rainfall duration and intensity, were acquired from the eight rain gauges installed by Cemaden in the study area. A very high spatial resolution digital terrain model was used to identify the slopes declivity. The analyzed period is from March 6th to March 8th of 2017. As results, the TRIGRS model calculates the variation of the Factor of Safety within a 72-hour period in which two heavy rainfall events stroke the area and six landslides were registered. After each rainfall, the Factor of Safety declined, as expected. The landslides happened in areas identified by the model with low values of Factor of Safety, proving its efficiency on the identification of landslides susceptible areas. This study presents a critical threshold for landslides, in which an accumulated rainfall higher than 80mm/m² in 72 hours might trigger landslides in urban and natural slopes. The geotechnical and geophysics methods are shown to be very useful to identify the soil properties and provide the geological characteristics of the area. Therefore, the combine geotechnical and geophysical methods for soil characterization and the modeling of landslides susceptible areas with TRIGRS are useful for urban planning. Furthermore, early warning systems can be developed by combining the TRIGRS model and weather forecast, to prevent disasters in urban slopes.

Keywords: landslides, susceptibility, TRIGRS, vertical electrical survey

Procedia PDF Downloads 160
2508 Constitutive Modeling of Different Types of Concrete under Uniaxial Compression

Authors: Mostafa Jafarian Abyaneh, Khashayar Jafari, Vahab Toufigh

Abstract:

The cost of experiments on different types of concrete has raised the demand for prediction of their behavior with numerical analysis. In this research, an advanced numerical model has been presented to predict the complete elastic-plastic behavior of polymer concrete (PC), high-strength concrete (HSC), high performance concrete (HPC) along with different steel fiber contents under uniaxial compression. The accuracy of the numerical response was satisfactory as compared to other conventional simple models such as Mohr-Coulomb and Drucker-Prager. In order to predict the complete elastic-plastic behavior of specimens including softening behavior, disturbed state concept (DSC) was implemented by nonlinear finite element analysis (NFEA) and hierarchical single surface (HISS) failure criterion, which is a failure surface without any singularity.

Keywords: disturbed state concept (DSC), hierarchical single surface (HISS) failure criterion, high performance concrete (HPC), high-strength concrete (HSC), nonlinear finite element analysis (NFEA), polymer concrete (PC), steel fibers, uniaxial compression test

Procedia PDF Downloads 300
2507 A Multi-Criteria Model for Scheduling of Stochastic Single Machine Problem with Outsourcing and Solving It through Application of Chance Constrained

Authors: Homa Ghave, Parmis Shahmaleki

Abstract:

This paper presents a new multi-criteria stochastic mathematical model for a single machine scheduling with outsourcing allowed. There are multiple jobs processing in batch. For each batch, all of job or a quantity of it can be outsourced. The jobs have stochastic processing time and lead time and deterministic due dates arrive randomly. Because of the stochastic inherent of processing time and lead time, we use the chance constrained programming for modeling the problem. First, the problem is formulated in form of stochastic programming and then prepared in a form of deterministic mixed integer linear programming. The objectives are considered in the model to minimize the maximum tardiness and outsourcing cost simultaneously. Several procedures have been developed to deal with the multi-criteria problem. In this paper, we utilize the concept of satisfaction functions to increases the manager’s preference. The proposed approach is tested on instances where the random variables are normally distributed.

Keywords: single machine scheduling, multi-criteria mathematical model, outsourcing strategy, uncertain lead times and processing times, chance constrained programming, satisfaction function

Procedia PDF Downloads 253
2506 Printing Imperfections: Development of Buckling Patterns to Improve Strength of 3D Printed Steel Plated Elements

Authors: Ben Chater, Jingbang Pan, Mark Evernden, Jie Wang

Abstract:

Traditional structural steel manufacturing routes normally produce prismatic members with flat plate elements. In these members, plate instability in the lowest buckling mode often dominates failure. It is proposed in the current study to use a new technology of metal 3D printing to print steel-plated elements with predefined imperfection patterns that can lead to higher modes of failure with increased buckling resistances. To this end, a numerical modeling program is carried out to explore various combinations of predefined buckling waves with different amplitudes in stainless steel square hollow section stub columns. Their stiffness, strength, and material consumption against the traditional structural steel members with the same nominal dimensions are assessed. It is found that depending on the slenderness of the plate elements; it is possible for an ‘imperfect’ steel member to achieve up to a 30% increase in strength with just a 3% increase in the material consumption. The obtained results shed some light on the significant potential of the new metal 3D printing technology in achieving unprecedented material efficiency and economical design in the future steel construction industry.

Keywords: 3D printing, additive manufacturing, buckling resistance, steel plate buckling, structural optimisation

Procedia PDF Downloads 131
2505 Cadmium Concentrations in Breast Milk and Factors of Exposition: Systematic Review

Authors: Abha Cherkani Hassani, Imane Ghanname, Nezha Mouane

Abstract:

Background: This is the first systematic review summarizing 43 years of research from 36 countries in the assessment of cadmium in breast milk; a suitable matrix in human biomonitoring. Objectives: To report from the published literature the levels of cadmium in breast milk and the affecting factors causing the increase of cadmium concentrations; also to gather several quantitative data which might be useful to evaluate the international degrees of maternal and infant exposure. Methods: We reviewed the literature for studies reporting quantitative data about cadmium levels in human breast milk in the world that have been published between 1971 and 2014 and that are available on Pubmed, Science direct and Google scholar. The aim of the study, country, period of samples collection, size of samples, sampling method, time of lactation, mother’s age, area of residence, cadmium concentration and other information were extracted. Results: 67 studies were selected and included in this systematic review. Some concentrations greatly exceed the limit of the WHO, However about 50% of the studies had less than 1 µg/l cadmium concentration (the recommendation of the WHO); as well many factors have shown their implication in breast milk contamination by Cadmium as lactation stage, smoking, diet, supplement intake, interaction with other mineral elements, age of mothers, parity and other parameters. Conclusion: Breast milk is a pathway of maternal excretion of cadmium. It is also a biological indicator of the degree of environmental pollution and cadmium exposure of the lactating women and the nourished infant. Therefore preventive measures and continuous monitoring are necessary.

Keywords: breast milk, cadmium level, factors, systematic review

Procedia PDF Downloads 507
2504 Spatially Distributed Rainfall Prediction Based on Automated Kriging for Landslide Early Warning Systems

Authors: Ekrem Canli, Thomas Glade

Abstract:

The precise prediction of rainfall in space and time is a key element to most landslide early warning systems. Unfortunately, the spatial variability of rainfall in many early warning applications is often disregarded. A common simplification is to use uniformly distributed rainfall to characterize aerial rainfall intensity. With spatially differentiated rainfall information, real-time comparison with rainfall thresholds or the implementation in process-based approaches might form the basis for improved landslide warnings. This study suggests an automated workflow from the hourly, web-based collection of rain gauge data to the generation of spatially differentiated rainfall predictions based on kriging. Because the application of kriging is usually a labor intensive task, a simplified and consequently automated variogram modeling procedure was applied to up-to-date rainfall data. The entire workflow was carried out purely with open source technology. Validation results, albeit promising, pointed out the challenges that are involved in pure distance based, automated geostatistical interpolation techniques for ever-changing environmental phenomena over short temporal and spatial extent.

Keywords: kriging, landslide early warning system, spatial rainfall prediction, variogram modelling, web scraping

Procedia PDF Downloads 273
2503 Cryogenic Separation of CO2 from Molten Carbonate Fuel Cell Anode Outlet—Experimental Guidelines

Authors: Jarosław Milewski, Rafał Bernat

Abstract:

This paper presents an analysis of using cryogenic separation unit for recovering fuel from anode off gas of molten carbonate fuel cells (MCFCs) in order to upgrade the efficiently of the unit. In the proposed solution, the CSU is used for condensing water and carbon dioxide from anode off gas, and re-cycling the rest of the stream to the anode, saving certain amount of fuel (at least 30%). The resulting system efficiency is increased considerably. CSU, virtually consumes power, thus this solution has energy penalty as well, on the other hand, MCFC generates large amount of heat at elevated temperature, thus part of the CSU can be based on absorption chiller. In all cases, a high amount of fuel is obtained after condensation of water and carbon dioxide and re-cycled to the anode inlet. Based on mathematical modeling done previously, the concept and guidelines for forthcoming experimental investigations are presented in this paper. During planned experiments, an existing single cell laboratory stand will be equipped with re-cycle device (a fan, a peristaltic pump, etc.). Parallel, a mixture of anode off gas will be cooled down for determining the proper temperature for the separation of water and carbon dioxide.

Keywords: cryogenic separation, experiments, fuel cells, molten carbonate fuel cells

Procedia PDF Downloads 234
2502 Modeling of Carbon Monoxide Distribution under the Sky-Train Stations

Authors: Suranath Chomcheon, Nathnarong Khajohnsaksumeth, Benchawan Wiwatanapataphee

Abstract:

Carbon monoxide is one of the harmful gases which have colorless, odorless, and tasteless. Too much carbon monoxide taken into the human body causes the reduction of oxygen transportation within human body cells leading to many symptoms including headache, nausea, vomiting, loss of consciousness, and death. Carbon monoxide is considered as one of the air pollution indicators. It is mainly released as soot from the exhaust pipe of the incomplete combustion of the vehicle engine. Nowadays, the increase in vehicle usage and the slowly moving of the vehicle struck by the traffic jam has created a large amount of carbon monoxide, which accumulated in the street canyon area. In this research, we study the effect of parameters such as wind speed and aspect ratio of the height building affecting the ventilation. We consider the model of the pollutant under the Bangkok Transit System (BTS) stations in a two-dimensional geometrical domain. The convention-diffusion equation and Reynolds-averaged Navier-stokes equation is used to describe the concentration and the turbulent flow of carbon monoxide. The finite element method is applied to obtain the numerical result. The result shows that our model can describe the dispersion patterns of carbon monoxide for different wind speeds.

Keywords: air pollution, carbon monoxide, finite element, street canyon

Procedia PDF Downloads 113
2501 Internet Economy: Enhancing Information Communication Technology Adaptation, Service Delivery, Content and Digital Skills for Small Holder Farmers in Uganda

Authors: Baker Ssekitto, Ambrose Mbogo

Abstract:

The study reveals that indeed agriculture employs over 70% of Uganda’s population, of which majority are youth and women. The study further reveals that over 70% of the farmers are smallholder farmers based in rural areas, whose operations are greatly affected by; climate change, weak digital skills, limited access to productivity knowledge along value chains, limited access to quality farm inputs, weak logistics systems, limited access to quality extension services, weak business intelligence, limited access to quality markets among others. It finds that the emerging 4th industrial revolution powered by artificial intelligence, 5G and data science will provide possibilities of addressing some of these challenges. Furthermore, the study finds that despite rapid development of ICT4Agric Innovation, their uptake is constrained by a number of factors including; limited awareness of these innovations, low internet and smart phone penetration especially in rural areas, lack of appropriate digital skills, inappropriate programmes implementation models which are project and donor driven, limited articulation of value addition to various stakeholders among others. Majority of farmers and other value chain actors lacked knowledge and skills to harness the power of ICTs, especially their application of ICTs in monitoring and evaluation on quality of service in the extension system and farm level processes.

Keywords: artificial intelligence, productivity, ICT4agriculture, value chain, logistics

Procedia PDF Downloads 69
2500 Analytical Modelling of Surface Roughness during Compacted Graphite Iron Milling Using Ceramic Inserts

Authors: Ş. Karabulut, A. Güllü, A. Güldaş, R. Gürbüz

Abstract:

This study investigates the effects of the lead angle and chip thickness variation on surface roughness during the machining of compacted graphite iron using ceramic cutting tools under dry cutting conditions. Analytical models were developed for predicting the surface roughness values of the specimens after the face milling process. Experimental data was collected and imported to the artificial neural network model. A multilayer perceptron model was used with the back propagation algorithm employing the input parameters of lead angle, cutting speed and feed rate in connection with chip thickness. Furthermore, analysis of variance was employed to determine the effects of the cutting parameters on surface roughness. Artificial neural network and regression analysis were used to predict surface roughness. The values thus predicted were compared with the collected experimental data, and the corresponding percentage error was computed. Analysis results revealed that the lead angle is the dominant factor affecting surface roughness. Experimental results indicated an improvement in the surface roughness value with decreasing lead angle value from 88° to 45°.

Keywords: CGI, milling, surface roughness, ANN, regression, modeling, analysis

Procedia PDF Downloads 439
2499 Regional Flood-Duration-Frequency Models for Norway

Authors: Danielle M. Barna, Kolbjørn Engeland, Thordis Thorarinsdottir, Chong-Yu Xu

Abstract:

Design flood values give estimates of flood magnitude within a given return period and are essential to making adaptive decisions around land use planning, infrastructure design, and disaster mitigation. Often design flood values are needed at locations with insufficient data. Additionally, in hydrologic applications where flood retention is important (e.g., floodplain management and reservoir design), design flood values are required at different flood durations. A statistical approach to this problem is a development of a regression model for extremes where some of the parameters are dependent on flood duration in addition to being covariate-dependent. In hydrology, this is called a regional flood-duration-frequency (regional-QDF) model. Typically, the underlying statistical distribution is chosen to be the Generalized Extreme Value (GEV) distribution. However, as the support of the GEV distribution depends on both its parameters and the range of the data, special care must be taken with the development of the regional model. In particular, we find that the GEV is problematic when developing a GAMLSS-type analysis due to the difficulty of proposing a link function that is independent of the unknown parameters and the observed data. We discuss these challenges in the context of developing a regional QDF model for Norway.

Keywords: design flood values, bayesian statistics, regression modeling of extremes, extreme value analysis, GEV

Procedia PDF Downloads 62
2498 Modeling of Daily Global Solar Radiation Using Ann Techniques: A Case of Study

Authors: Said Benkaciali, Mourad Haddadi, Abdallah Khellaf, Kacem Gairaa, Mawloud Guermoui

Abstract:

In this study, many experiments were carried out to assess the influence of the input parameters on the performance of multilayer perceptron which is one the configuration of the artificial neural networks. To estimate the daily global solar radiation on the horizontal surface, we have developed some models by using seven combinations of twelve meteorological and geographical input parameters collected from a radiometric station installed at Ghardaïa city (southern of Algeria). For selecting of best combination which provides a good accuracy, six statistical formulas (or statistical indicators) have been evaluated, such as the root mean square errors, mean absolute errors, correlation coefficient, and determination coefficient. We noted that multilayer perceptron techniques have the best performance, except when the sunshine duration parameter is not included in the input variables. The maximum of determination coefficient and correlation coefficient are equal to 98.20 and 99.11%. On the other hand, some empirical models were developed to compare their performances with those of multilayer perceptron neural networks. Results obtained show that the neural networks techniques give the best performance compared to the empirical models.

Keywords: empirical models, multilayer perceptron neural network, solar radiation, statistical formulas

Procedia PDF Downloads 329
2497 Safety Culture Implementation Based on Occupational Health and Safety Assessment

Authors: Nyambayar Davaadorj, Ichiro Koshijima

Abstract:

Safety or the state of being safe can be described as a condition of being not dangerous or not harmful. It is necessary for an individual to avoid dangerous situations every day. Also, an organization is subject to legal requirements for the health and safety of persons inside and around the immediate workplace, or who are exposed to the workplace activities. Although it might be difficult to keep a situation where complete safety is ensured, efforts must nonetheless be made to consider ways of removing any potential danger within an organization. In order to ensure a safe working environment, the capability of responding (i.e., resilience) to signals (i.e., information concerning events that could pose future problems that must be taken into account) that occur in and around corporations is necessary. The ability to evaluate this essential point is thus one way in which safety and security can be managed. This study focuses on OHSAS18001, an internationally applied standard for the construction and operation of occupational health and safety management systems, by using IDEF0 for Function Modeling (IDEF0) and the Resilience Matrix originally made by Bracco. Further, this study discusses a method for evaluating a manner in which Occupational Health and Safety Assessment Series (OHSAS) systematically functions within corporations. Based on the findings, this study clarifies the potential structural objection for corporations when implementing and operating the OHSAS standard.

Keywords: OHSAS18001, IDEF0, resilience engineering, safety culture

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2496 Sustainable Engineering: Synergy of BIM and Environmental Assessment Tools in Hong Kong Construction Industry

Authors: Kwok Tak Kit

Abstract:

The construction industry plays an important role in environmental and carbon emissions as it consumes a huge amount of natural resources and energy. Sustainable engineering involves the process of planning, design, procurement, construction and delivery in which the whole building and construction process resulting from building and construction can be effectively and sustainability managed to achieve the use of natural resources. Implementation of sustainable technology development and innovation, adoption of the advanced construction process and facilitate the facilities management to implement the energy and waste control more accurately and effectively. Study and research in the relationship of BIM and environment assessment tools lack a clear discussion. In this paper, we will focus on the synergy of BIM technology and sustainable engineering in the AEC industry and outline the key factors which enhance the use of advanced innovation, technology and method and define the role of stakeholders to achieve zero-carbon emission toward the Paris Agreement to limit global warming to well below 2ᵒC above pre-industrial levels. A case study of the adoption of Building Information Modeling (BIM) and environmental assessment tools in Hong Kong will be discussed in this paper.

Keywords: sustainability, sustainable engineering, BIM, LEED

Procedia PDF Downloads 136
2495 The Impact of Direct and Indirect Pressure Measuring Systems on the Pressure Mapping for the Medical Compression Garments

Authors: Arash M. Shahidi, Tilak Dias, Gayani K. Nandasiri

Abstract:

While graduated compression is the foundation of treatment and management of many medical complications such as leg ulcer, varicose veins, and lymphedema, monitoring the interface pressure has been conducted using different sensors that operate based on diverse approaches. The variations existed from the pressure readings collected using different interface pressure measurement systems would cause difficulties in taking a decision regarding the compression therapy. It is crucial to acknowledge the differences existing between direct and indirect pressure measurement systems while considering the commercially available systems such as AMI, Picopress and OPM which are under direct measurements systems, and HATRA (BSI), HOSY (RAL-GZ) and FlexiForce which comes under the indirect measurement system. Furthermore, Piezo-resistive sensors (Flexiforce) can measure the changes in resistance corresponding to the applied force on the sensing area. Direct pressure measuring systems are capable of measuring interface pressure on the three-dimensional states, while the indirect pressure measuring systems stretch the fabric in the two-dimensional direction and extrapolate pressure from surface tension measured on the device and neglect the vital factor which is the radius of curvature. In this study, a leg mannequin of known dimensions is selected with a knitted class 3 compression stocking. It has been decided to evaluate the data collected from different available systems (AMI, PicoPress, FlexiForce, and HATRA) and compare the results. The results showed a discrepancy between Hatra, AMI, Picopress, and Flexiforce against the pressure standard used to generate class 3 compression stocking. As predicted a higher pressure value with direct interface measuring systems were monitored against HATRA due to the effect of the radius of curvature.

Keywords: AMI, FlexiForce, graduated compression, HATRA, interface pressure, PicoPress

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2494 Comparison of Several Diagnostic Methods for Detecting Bovine Viral Diarrhea Virus Infection in Cattle

Authors: Azizollah Khodakaram- Tafti, Ali Mohammadi, Ghasem Farjanikish

Abstract:

Bovine viral diarrhea virus (BVDV) is one of the most important viral pathogens of cattle worldwide caused by Pestivirus genus, Flaviviridae family.The aim of the present study was to comparison several diagnostic methods and determine the prevalence of BVDV infection for the first time in dairy herds of Fars province, Iran. For initial screening, a total of 400 blood samples were randomly collected from 12 industrial dairy herds and analyzed using reverse transcription (RT)-PCR on the buffy coat. In the second step, blood samples and also ear notch biopsies were collected from 100 cattle of infected farms and tested by antigen capture ELISA (ACE), RT-PCR and immunohistochemistry (IHC). The results of nested RT-PCR (outer primers 0I100/1400R and inner primers BD1/BD2) was successful in 16 out of 400 buffy coat samples (4%) as acute infection in initial screening. Also, 8 out of 100 samples (2%) were positive as persistent infection (PI) by all of the diagnostic tests similarly including RT-PCR, ACE and IHC on buffy coat, serum and skin samples, respectively. Immunoreactivity for bovine BVDV antigen as brown, coarsely to finely granular was observed within the cytoplasm of epithelial cells of epidermis and hair follicles and also subcutaneous stromal cells. These findings confirm the importance of monitoring BVDV infection in cattle of this region and suggest detection and elimination of PI calves for controlling and eradication of this disease.

Keywords: antigen capture ELISA, bovine viral diarrhea virus, immunohistochemistry, RT-PCR, cattle

Procedia PDF Downloads 349
2493 Correlation of Building Density toward Land Surface Temperature 2018 in Medan City

Authors: Andi Syahputra, R. H. Jatmiko, D. R. Hizbaron

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Land surface temperature (LST) in an area is influenced by conditions of vegetation density, building density, and the number of inhabitants who live in the area. Medan City is one of the largest cities in Indonesia, with a high rate of change from vegetation to developed land. This study aims to identify the relationship between the percentage of building density and land surface temperature in Medan City. Pixel image analysis method is carried out to obtain the value of building density in pixel images of Landsat 8 images with the help of WorldView-2 satellite imagery. The results showed the highest land surface temperature in 2018 of 35, 4°C was found in Medan Perjuangan District, and the lowest was 22.5°C in Medan Belawan District. Building density samples with a density level of 889.17 m were also found in Medan Perjuangan District, while the lowest building density sample was found in Medan Timur District. Linear regression analysis of the effect of building density with land surface temperature obtained a correlation (R) was 0.64, and a coefficient of determination (R²) was 0.411 and modeling of building density based on the LST has a correlation (R), and a coefficient of determination (R²) was 0.72 with The RMSE obtained 0.853.

Keywords: land surface temperature, Landsat, imagery, building density, vegetation, density

Procedia PDF Downloads 139
2492 Role of Social Capital on Consumer Attitudes, Peer Influence and Behavioral Intentions: A Social Media Perspective

Authors: Qazi Mohammed Ahmed, Osman Sadiq Paracha, Iftikhar Hussain

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The study aims to explore the unaddressed relationship between social capital and consumers’ underlying behavioral intentions. The study postulates that this association is mediated by the role of attitudes and peer influence. The research attains evidence from a usable sample of 673 responses. The majority consists of the young and energetic social media users of Pakistan that utilize virtual communities as a way of life. A variance based structural equation modeling has been applied through SmartPLS 3. The results reveal that social capital exerts a statistically supportive association with both attitudes and peer influence. Contrastingly, this predictor variable shows an insignificant linkage with behavioral intentions but this relationship is fully mediated by consumer attitudes and peer influence. The paper enhances marketing literature with respect to an unexplored society of Pakistan. It also provides a lens for the contemporary advertisers, in terms of supporting their social media campaigns with affiliative and cohesive elements. The study also identifies a series of predictor variables that could further be tested with attitudes, subjective norms and behavioral responses.

Keywords: social capital, consumer attitudes, peer influence, behavioral intentions

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2491 Lead and Cadmium Residue Determination in Spices Available in Tripoli City Markets (Libya)

Authors: Mohamed Ziyaina, Ahlam Rajab, Khadija Alkhweldi, Wafia Algami, Omer Al. Toumi, Barbara Rasco1

Abstract:

In recent years, there has been a growing interest in monitoring heavy metal contamination in food products. Spices can improve the taste of food and can also be a source of many bioactive compounds but can unfortunately, also be contaminated with dangerous materials, potentially heavy metals. This study was conducted to investigate lead (Pb) and cadmium (Cd) contamination in selected spices commonly consumed in Libya including Capsicum frutescens (chili pepper) Piper nigrum, (black pepper), Curcuma longa (turmeric), and mixed spices (HRARAT) which consist of a combination of: Alpinia officinarum, Zingiber officinale and Cinnamomum zeylanicum. Spices were analyzed by atomic absorption spectroscopy after digestion with nitric acid/hydrogen peroxide. The highest level of lead (Pb) was found in Curcuma longa and Capsicum frutescens in wholesale markets (1.05 ± 0.01 mg/kg, 0.96 ± 0.06 mg/kg). Cadmium (Cd) levels exceeded FAO/WHO permissible limit. Curcuma longa and Piper nigrum sold in retail markets had a high concentration of Cd (0.36 ± 0.09, 0.35 ± 0.07 mg/kg, respectively) followed by (0.32 ± 0.04 mg/kg) for Capsicum frutescens. Mixed spices purchased from wholesale markets also had high levels of Cd (0.31 ± 0.08 mg/kg). Curcuma longa and Capsicum frutescens may pose a food safety risk due to high levels of lead and cadmium. Cadmium levels exceeded FAO/WHO recommendations (0.2 ppm) for Piper nigrum, Curcuma longa, and mixed spices (HRARAT).

Keywords: heavy metals, lead, cadmium determination, spice

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2490 Contemplating Charge Transport by Modeling of DNA Nucleobases Based Nano Structures

Authors: Rajan Vohra, Ravinder Singh Sawhney, Kunwar Partap Singh

Abstract:

Electrical charge transport through two basic strands thymine and adenine of DNA have been investigated and analyzed using the jellium model approach. The FFT-2D computations have been performed for semi-empirical Extended Huckel Theory using atomistic tool kit to contemplate the charge transport metrics like current and conductance. The envisaged data is further evaluated in terms of transmission spectrum, HOMO-LUMO Gap and number of electrons. We have scrutinized the behavior of the devices in the range of -2V to 2V for a step size of 0.2V. We observe that both thymine and adenine can act as molecular devices when sandwiched between two gold probes. A prominent observation is a drop in HLGs of adenine and thymine when working as a device as compared to their intrinsic values and this is comparative more visible in case of adenine. The current in the thymine based device exhibit linear increase with voltage in spite of having low conductance. Further, the broader transmission peaks represent the strong coupling of electrodes to the scattering molecule (thymine). Moreover, the observed current in case of thymine is almost 3-4 times than that of observed for adenine. The NDR effect has been perceived in case of adenine based device for higher bias voltages and can be utilized in various future electronics applications.

Keywords: adenine, DNA, extended Huckel, thymine, transmission spectra

Procedia PDF Downloads 143
2489 Development of Geo-computational Model for Analysis of Lassa Fever Dynamics and Lassa Fever Outbreak Prediction

Authors: Adekunle Taiwo Adenike, I. K. Ogundoyin

Abstract:

Lassa fever is a neglected tropical virus that has become a significant public health issue in Nigeria, with the country having the greatest burden in Africa. This paper presents a Geo-Computational Model for Analysis and Prediction of Lassa Fever Dynamics and Outbreaks in Nigeria. The model investigates the dynamics of the virus with respect to environmental factors and human populations. It confirms the role of the rodent host in virus transmission and identifies how climate and human population are affected. The proposed methodology is carried out on a Linux operating system using the OSGeoLive virtual machine for geographical computing, which serves as a base for spatial ecology computing. The model design uses Unified Modeling Language (UML), and the performance evaluation uses machine learning algorithms such as random forest, fuzzy logic, and neural networks. The study aims to contribute to the control of Lassa fever, which is achievable through the combined efforts of public health professionals and geocomputational and machine learning tools. The research findings will potentially be more readily accepted and utilized by decision-makers for the attainment of Lassa fever elimination.

Keywords: geo-computational model, lassa fever dynamics, lassa fever, outbreak prediction, nigeria

Procedia PDF Downloads 79
2488 Optimal Design of InGaP/GaAs Heterojonction Solar Cell

Authors: Djaafar F., Hadri B., Bachir G.

Abstract:

We studied mainly the influence of temperature, thickness, molar fraction and the doping of the various layers (emitter, base, BSF and window) on the performances of a photovoltaic solar cell. In a first stage, we optimized the performances of the InGaP/GaAs dual-junction solar cell while varying its operation temperature from 275°K to 375 °K with an increment of 25°C using a virtual wafer fabrication TCAD Silvaco. The optimization at 300°K led to the following result Icc =14.22 mA/cm2, Voc =2.42V, FF =91.32 %, η = 22.76 % which is close with those found in the literature. In a second stage ,we have varied the molar fraction of different layers as well their thickness and the doping of both emitters and bases and we have registered the result of each variation until obtaining an optimal efficiency of the proposed solar cell at 300°K which was of Icc=14.35mA/cm2,Voc=2.47V,FF=91.34,and η =23.33% for In(1-x)Ga(x)P molar fraction( x=0.5).The elimination of a layer BSF on the back face of our cell, enabled us to make a remarkable improvement of the short-circuit current (Icc=14.70 mA/cm2) and a decrease in open circuit voltage Voc and output η which reached 1.46V and 11.97% respectively. Therefore, we could determine the critical parameters of the cell and optimize its various technological parameters to obtain the best performance for a dual junction solar cell. This work opens the way with new prospects in the field of the photovoltaic one. Such structures will thus simplify the manufacturing processes of the cells; will thus reduce the costs while producing high outputs of photovoltaic conversion.

Keywords: modeling, simulation, multijunction, optimization, silvaco ATLAS

Procedia PDF Downloads 609
2487 Study of Sub-Surface Flow in an Unconfined Carbonate Aquifer in a Tropical Karst Area in Indonesia: A Modeling Approach Using Finite Difference Groundwater Model

Authors: Dua K. S. Y. Klaas, Monzur A. Imteaz, Ika Sudiayem, Elkan M. E. Klaas, Eldav C. M. Klaas

Abstract:

Due to its porous nature, karst terrains – geomorphologically developed from dissolved formations, is vulnerable to water shortage and deteriorated water quality. Therefore, a solid comprehension on sub-surface flow of karst landscape is essential to assess the long-term availability of groundwater resources. In this paper, a single-continuum model using a finite difference model, MODLFOW, was constructed to represent an unconfined carbonate aquifer in a tropical karst island of Rote in Indonesia. The model, spatially discretized in 20 x 20 m grid cells, was calibrated and validated using available groundwater level and atmospheric variables. In the calibration and validation steps, Parameter Estimation (PEST) and geostatistical pilot point methods were employed to estimate hydraulic conductivity and specific yield values. The results show that the model is able to represent the sub-surface flow indicated by good model performances both in calibration and validation steps. The final model can be used as a robust representation of the system for future study on climate and land use scenarios.

Keywords: carbonate aquifer, karst, sub-surface flow, groundwater model

Procedia PDF Downloads 140
2486 Interval Type-2 Fuzzy Vibration Control of an ERF Embedded Smart Structure

Authors: Chih-Jer Lin, Chun-Ying Lee, Ying Liu, Chiang-Ho Cheng

Abstract:

The main objective of this article is to present the semi-active vibration control using an electro-rheological fluid embedded sandwich structure for a cantilever beam. ER fluid is a smart material, which cause the suspended particles polarize and connect each other to form chain. The stiffness and damping coefficients of the ER fluid can be changed in 10 micro seconds; therefore, ERF is suitable to become the material embedded in the tunable vibration absorber to become a smart absorber. For the ERF smart material embedded structure, the fuzzy control law depends on the experimental expert database and the proposed self-tuning strategy. The electric field is controlled by a CRIO embedded system to implement the real application. This study investigates the different performances using the Type-1 fuzzy and interval Type-2 fuzzy controllers. The Interval type-2 fuzzy control is used to improve the modeling uncertainties for this ERF embedded shock absorber. The self-tuning vibration controllers using Type-1 and Interval Type-2 fuzzy law are implemented to the shock absorber system. Based on the resulting performance, Internal Type-2 fuzzy is better than the traditional Type-1 fuzzy control for this vibration control system.

Keywords: electro-rheological fluid, semi-active vibration control, shock absorber, type 2 fuzzy control

Procedia PDF Downloads 434
2485 Effect of Project Control Practices on the Performance of Building Construction Companies in Uganda: A Case Study of Kampala City

Authors: Tukundane Hillary

Abstract:

This research paper analytically evaluates the project control practice levels used by the building construction companies within Kampala, Uganda. The research also assesses the outcome of project control practices on the productivity of the companies. The research was performed to ascertain the current control practices among 160 respondents from various construction companies registered with the Uganda Registration Services Bureau. This research used amalgamation from multiple literature to obtain the variables. The research adopts 34 standard control practices from four vital project control duties: planning, monitoring, analyzing, and reporting. These project control tasks were organized using mean response ratings grounded on their relevance to the construction companies. Results showed that evaluating performance with the use of curves (4.32), timely access to information and encouragement (4.55), report representation using quantitative tools 4.75, and cost value comparison application during analysis (4.76) were rated least among the control practices. On the other hand, the top project control practices included formulation of the project schedule (8.88), Project feasibility validation (8.86), Budgeting for each activity (8.84), Key project route definition (8.81), Team awareness of the budget (8.77), Setting realistic targets for projects (8.50) and Consultation from subcontractors (8.74). From the results obtained by the sample respondents specified, it can be concluded that planning is the most vital project control task practiced in the building construction industry in Uganda. In addition, this research ascertained a substantial relationship between project control practices and the performance of building construction companies. Accordingly, this research recommends that project control practices be effectively observed by both contracting and consulting companies to enhance their overall performance and governance.

Keywords: cost value, project control, cost control, time control, project performance, control practices

Procedia PDF Downloads 56