Search results for: modelica modelling

Authors: Hesam Khajehsaeid, Naeimeh Alagheband

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Magnetorheological fluids (MRF) are a category of smart materials. They exhibit a reversible change from a Newtonian-like fluid to a semi-solid state upon application of an external magnetic field. In contrast to ordinary fluids, MRFs can tolerate shear stresses up to a threshold value called yield stress which strongly depends on the strength of the magnetic field, magnetic particles volume fraction and temperature. Even beyond the yield, a magnetic field can increase MR fluid viscosity up to several orders. As yield stress is an important parameter in the design of MR devices, in this work, the effects of magnetic field intensity and magnetic particle concentration on the yield stress of MRFs are investigated. Four MRF samples with different particle concentrations are developed and tested through flow-ramp analysis to obtain the flow curves at a range of magnetic field intensity as well as shear rate. The viscosity of the fluids is determined by means of the flow curves. The results are then used to determine the yield stresses by means of the steady stress sweep method. The yield stresses are then determined by means of a modified form of the dipole model as well as empirical models. The exponential distribution function is used to describe the orientation of particle chains in the dipole model under the action of the external magnetic field. Moreover, the modified dipole model results in a reasonable distribution of chains compared to previous similar models.

Keywords: magnetorheological fluids, yield stress, particles concentration, dipole model

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Authors: Lukasz Baka

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Objective. The study aimed to investigate the direct and indirect - mediated through insomnia - effect of coronavirus anxiety on exhaustion from the perspective of Hobfol Conservation of Resources (COR) theory. According to COR theory, critical events (e.g. the coronavirus epidemic) make people fearful of losing their valuable resources. A prolonged state of anxiety may lead to sleep troubles, which over time, results in an increase in exhaustion. Materials and Methods: Data were collected among 440 Polish healthcare providers, including nurses and midwives, doctors, paramedics, medical assistance, and wardens. Three measurements were used: Coronavirus Anxiety Scale (CAS), Copenhagen Psychosocial Questionnaire (COPSOQ, sleep trouble subscale) and Oldenburg Burnout Inventory (OLBI, exhaustion subscale). Hypotheses were tested by the use of Structural Equation Modelling (SEM). Results: The obtained results fully support the hypotheses. Both the direct and indirect relationships between coronavirus anxiety and exhaustion were observed. Specifically, high coronavirus anxiety increased insomnia, which in turn contributed to the development of exhaustion. Conclusion: The results are consistent with the COR theory. Prolonged coronavirus anxiety and sleep problems depleted healthcare providers’ resources and made them feel exhausted. Exhaustion among these workers can have serious consequences not only for themselves but also for the health of their patients, therefore researches into effective ways to deal with coronavirus anxiety are needed.

Keywords: coronavirus anxiety, front-line healt-care workers, insomnia, job burnout

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Authors: Gertraud Koch, Teresa Stumpf, Alejandra Tijerina García

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Discourse analysis research approaches belong to the central research strategies applied throughout the humanities; they focus on the countless forms and ways digital texts and images shape present-day notions of the world. Despite the constantly growing number of relevant digital, multimodal discourse resources, digital humanities (DH) methods are thus far not systematically developed and accessible for discourse analysis approaches. Specifically, the significance of multimodality and meaning plurality modelling are yet to be sufficiently addressed. In order to address this research gap, the D-WISE project aims to develop a prototypical working environment as digital support for the sociology of knowledge approach to discourse analysis and new IT-analysis approaches for the use of context-oriented embedding representations. Playing an essential role throughout our research endeavor is the constant optimization of hermeneutical methodology in the use of (semi)automated processes and their corresponding epistemological reflection. Among the discourse analyses, the sociology of knowledge approach to discourse analysis is characterised by the reconstructive and accompanying research into the formation of knowledge systems in social negotiation processes. The approach analyses how dominant understandings of a phenomenon develop, i.e., the way they are expressed and consolidated by various actors in specific arenas of discourse until a specific understanding of the phenomenon and its socially accepted structure are established. This article presents insights and initial findings from D-WISE, a joint research project running since 2021 between the Institute of Anthropological Studies in Culture and History and the Language Technology Group of the Department of Informatics at the University of Hamburg. As an interdisciplinary team, we develop central innovations with regard to the availability of relevant DH applications by building up a uniform working environment, which supports the procedure of the sociology of knowledge approach to discourse analysis within open corpora and heterogeneous, multimodal data sources for researchers in the humanities. We are hereby expanding the existing range of DH methods by developing contextualized embeddings for improved modelling of the plurality of meaning and the integrated processing of multimodal data. The alignment of this methodological and technical innovation is based on the epistemological working methods according to grounded theory as a hermeneutic methodology. In order to systematically relate, compare, and reflect the approaches of structural-IT and hermeneutic-interpretative analysis, the discourse analysis is carried out both manually and digitally. Using the example of current discourses on digitization in the healthcare sector and the associated issues regarding data protection, we have manually built an initial data corpus of which the relevant actors and discourse positions are analysed in conventional qualitative discourse analysis. At the same time, we are building an extensive digital corpus on the same topic based on the use and further development of entity-centered research tools such as topic crawlers and automated newsreaders. In addition to the text material, this consists of multimodal sources such as images, video sequences, and apps. In a blended reading process, the data material is filtered, annotated, and finally coded with the help of NLP tools such as dependency parsing, named entity recognition, co-reference resolution, entity linking, sentiment analysis, and other project-specific tools that are being adapted and developed. The coding process is carried out (semi-)automated by programs that propose coding paradigms based on the calculated entities and their relationships. Simultaneously, these can be specifically trained by manual coding in a closed reading process and specified according to the content issues. Overall, this approach enables purely qualitative, fully automated, and semi-automated analyses to be compared and reflected upon.

Keywords: entanglement of structural IT and hermeneutic-interpretative analysis, multimodality, plurality of meaning, sociology of knowledge approach to discourse analysis

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Authors: Atousa Khodadadyan, Ali Rostami

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The objective of off-site construction manufacturing is to utilise the workforce and machinery in a controlled environment without external interference for higher productivity and quality. The usage of prefabricated components can save up to 14% of the total energy consumption in comparison with the equivalent number of cast-in-place ones. Despite the benefits of prefabrication construction, its current project practices encompass technical and managerial issues. Building design, precast components’ production, logistics, and prefabrication installation processes are still mostly discontinued and fragmented. Furthermore, collaboration among prefabrication manufacturers, transportation parties, and on-site assemblers rely on real-time information such as the status of precast components, delivery progress, and the location of components. From the technical point of view, in this industry, geometric variability is still prevalent, which can be caused during the transportation or production of components. These issues indicate that there are still many aspects of prefabricated construction that can be developed using disruptive technologies. Practical real-time risk analysis can be used to address these issues as well as the management of safety, quality, and construction environment issues. On the other hand, the lack of research about risk assessment and the absence of standards and tools hinder risk management modeling in prefabricated construction. It is essential to note that no risk management standard has been established explicitly for prefabricated construction projects, and most software packages do not provide tailor-made functions for this type of projects.

Keywords: project risk management, risk analysis, risk modelling, prefabricated construction projects

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Authors: T. Malmir, U. Eicker

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Landfilling of organic waste is still the predominant waste management method in the USA and Canada. Strategic plans for waste diversion from landfills are needed to increase material recovery and energy generation from waste. In this paper, we carried out a statistical survey on waste flow in the two cities New York and Montréal and estimated the energy recovery potential for each case. Data collection and analysis of the organic waste (food waste, yard waste, etc.), paper and cardboard, metal, glass, plastic, carton, textile, electronic products and other materials were done based on the reports published by the Department of Sanitation in New York and Service de l'Environnement in Montréal. In order to calculate the gas generation potential of organic waste, Buswell equation was used in which the molar mass of the elements was calculated based on their atomic weight and the amount of organic waste in New York and Montréal. Also, the higher and lower calorific value of the organic waste (solid base) and biogas (gas base) were calculated. According to the results, only 19% (598 kt) and 45% (415 kt) of New York and Montréal waste were diverted from landfills in 2017, respectively. The biogas generation potential of the generated food waste and yard waste amounted to 631 million m³ in New York and 173 million m³ in Montréal. The higher and lower calorific value of food waste were 3482 and 2792 GWh in New York and 441 and 354 GWh in Montréal, respectively. In case of yard waste, they were 816 and 681 GWh in New York and 636 and 531 GWh in Montréal, respectively. Considering the higher calorific value, this amount would mean a contribution of around 2.5% energy in these cities.

Keywords: energy recovery, organic waste, urban energy modelling with INSEL, waste flow

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Authors: Nuo Duan, Yi Pik Cheng

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This paper presents the data of a series of two-dimensional Discrete Element Method (DEM) simulations of a large-diameter rigid monopile subjected to cyclic loading under a high gravitational force. At present, monopile foundations are widely used to support the tall and heavy wind turbines, which are also subjected to significant from wind and wave actions. A safe design must address issues such as rotations and changes in soil stiffness subject to these loadings conditions. Design guidance on the issue is limited, so are the availability of laboratory and field test data. The interpretation of these results in sand, such as the relation between loading and displacement, relies mainly on empirical correlations to pile properties. Regarding numerical models, most data from Finite Element Method (FEM) can be found. They are not comprehensive, and most of the FEM results are sensitive to input parameters. The micro scale behaviour could change the mechanism of the soil-structure interaction. A DEM model was used in this paper to study the cyclic lateral loads behaviour. A non-dimensional framework is presented and applied to interpret the simulation results. The DEM data compares well with various set of published experimental centrifuge model test data in terms of lateral deflection. The accumulated permanent pile lateral displacements induced by the cyclic lateral loads were found to be dependent on the characteristics of the applied cyclic load, such as the extent of the loading magnitudes and directions.

Keywords: cyclic loading, DEM, numerical modelling, sands

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Authors: Alam Zeb, Glen W. Armstrong, Muhammad Qasim

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Loss of forest cover is one of the most important land cover changes and has been of great concern to policy makers. This study quantified forest cover changes over pre logging ban (1973-1993) and post logging ban (1993-2015) to examine the role of geophysical factors and spatial attributes of land in the two periods. We show that despite a complete ban on green felling, forest cover decreased by 28% and mostly converted to rangeland. Nevertheless, the logging ban was completely effective in controlling agriculture expansion. The binary logistic regression revealed that the south facing aspects at low elevation witnessed more deforestation in the pre-ban period compared to post-ban. Opposite to deforestation, forest degradation was more prominent on the northern aspects at higher elevation during the policy period. Agriculture expansion was widespread in the low elevation flat areas with gentle slope, while during the policy period agriculture contraction in the form of regeneration was observed on the low elevation areas of north facing slopes. All proximity variables, except distance to administrative boundary, showed a similar trend across the two periods and were important explanatory variables in understanding forest and agriculture expansion. The changes in determinants of forest and agriculture expansion and contraction over the two periods might be attributed to the influence of policy and a general decrease in resource availability.

Keywords: forest conservation , wood harvesting ban, logistic regression, deforestation, forest degradation, agriculture expansion, Chitral, Pakistan

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Authors: Prajwal Eachempati, Laurent Muzellec, Ashish Kumar Jha

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We use Facebook as a case study to investigate the complex relationship between the firm’s public discourse (and actions) surrounding data privacy and the performance of a business model based on monetizing user’s data. We do so by looking at the evolution of public discourse over time (2004–2021) and relate topics to revenue and stock market evolution Drawing from archival sources like Zuckerberg We use LDA topic modelling algorithm to reveal 19 topics regrouped in 6 major themes. We first show how, by using persuasive and convincing language that promises better protection of consumer data usage, but also emphasizes greater user control over their own data, the privacy issue is being reframed as one of greater user control and responsibility. Second, we aim to understand and put a value on the extent to which privacy disclosures have a potential impact on the financial performance of social media firms. There we found significant relationship between the topics pertaining to privacy and social media/technology, sentiment score and stock market prices. Revenue is found to be impacted by topics pertaining to politics and new product and service innovations while number of active users is not impacted by the topics unless moderated by external control variables like Return on Assets and Brand Equity.

Keywords: public discourses, data protection, social media, privacy, topic modeling, business models, financial performance

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Authors: Adesoji Tunbosun Jaiyeola, Josiah Adeyemo

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Sediment yield can be considered to be the total sediment load that leaves a drainage basin. The knowledge of the quantity of sediments present in a river at a particular time can lead to better flood capacity in reservoirs and consequently help to control over-bane flooding. Furthermore, as sediment accumulates in the reservoir, it gradually loses its ability to store water for the purposes for which it was built. The development of hydrological models to forecast the quantity of sediment present in a reservoir helps planners and managers of water resources systems, to understand the system better in terms of its problems and alternative ways to address them. The application of artificial intelligence models and technique to such real-life situations have proven to be an effective approach of solving complex problems. This paper makes an extensive review of literature relevant to the theories and applications of evolutionary algorithms, and most especially genetic programming. The successful applications of genetic programming as a soft computing technique were reviewed in sediment modelling and other branches of knowledge. Some fundamental issues such as benchmark, generalization ability, bloat and over-fitting and other open issues relating to the working principles of GP, which needs to be addressed by the GP community were also highlighted. This review aim to give GP theoreticians, researchers and the general community of GP enough research direction, valuable guide and also keep all stakeholders abreast of the issues which need attention during the next decade for the advancement of GP.

Keywords: benchmark, bloat, generalization, genetic programming, over-fitting, sediment yield

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Authors: W. Wen, G. Jackson, S. Maskill, D. G. McCartney, W. Sun

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CoNiCrAlY alloys have been widely used as bond coats for thermal barrier coating (TBC) systems because of low cost, improved control of composition, and the feasibility to tailor the coatings microstructures. Coatings are in general very thin structures, and therefore it is impossible to characterize the mechanical responses of the materials via conventional mechanical testing methods. Due to this reason, miniature specimen testing methods, such as the small punch test technique, have been developed. This paper presents some of the recent research in evaluating the mechanical properties of the CoNiCrAlY coatings at room and high temperatures, through the use of small punch testing and the developed miniature specimen tensile testing, applicable to a range of temperature, to investigate the elastic-plastic and creep behavior as well as ductile-brittle transition temperature (DBTT) behavior. An inverse procedure was developed to derive the mechanical properties from such tests for the coating materials. A two-layer specimen test method is also described. The key findings include: 1) the temperature-dependent coating properties can be accurately determined by the miniature tensile testing within a wide range of temperature; 2) consistent DBTTs can be identified by both the SPT and miniature tensile tests (~ 650 °C); and 3) the FE SPT modelling has shown good capability of simulating the early local cracking. In general, the temperature-dependent material behaviors of the CoNiCrAlY coating has been effectively characterized using miniature specimen testing and inverse method.

Keywords: NiCoCrAlY coatings, mechanical properties, DBTT, miniature specimen testing

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Authors: Suraj Nair, Aravindkumar Vijayalingam, Alexander Perzylo, Alois Knoll

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In the last decade robotics research and development activities have grown rapidly, especially in the domain of service robotics. Integrating service robots into human occupied spaces such as homes, offices, hospitals, etc. has become increasingly worked upon. The primary motive is to ease daily lives of humans by taking over some of the household/office chores. However, several challenges remain in systematically integrating such systems in human shared work-spaces. In addition to sensing and indoor-navigation challenges, programmability of such systems is a major hurdle due to the fact that the potential user cannot be expected to have knowledge in robotics or similar mechatronic systems. In this paper, we propose a cognitive system for service robotics which allows non-expert users to easily model system behaviour in an underspecified manner through abstract tasks and objects associated with them. The system uses domain knowledge expressed in the form of an ontology along with logical reasoning mechanisms to infer all the missing pieces of information required for executing the tasks. Furthermore, the system is also capable of recovering from failed tasks arising due to on-line disturbances by using the knowledge base and inferring alternate methods to execute the same tasks. The system is demonstrated through a coffee fetching scenario in an office environment using a mobile robot equipped with sensors and software capabilities for autonomous navigation and human-interaction through natural language.

Keywords: cognitive robotics, reasoning, service robotics, task based systems

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Authors: Supriya Patibanda, Xiaopeng Gong, Krishna N. Jonnalagadda, Ralph Abrahams

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Yttria stabilized zirconia (YSZ) is used as a top coat in thermal barrier coatings in high-temperature turbine/jet engine applications. The mechanical behaviour of YSZ depends on the microstructural features like crack density and porosity, which are a result of coating method. However, experimentally ascertaining their individual effect is difficult due to the inherent challenges involved like material synthesis and handling. The current work deals with the development of a phenomenological model to replicate the tensile behavior of air plasma sprayed YSZ obtained from experiments. Initially, uniaxial tensile experiments were performed on freestanding YSZ coatings of ~300 µm thick for different crack densities and porosities. The coatings exhibited a nonlinear behavior and also a huge variation in strength values. With the obtained experimental tensile curve as a base and crack density and porosity as prime variables, a phenomenological model was developed using ABAQUS interface with new user material defined employing VUMAT sub routine. The relation between the tensile stress and the crack density was empirically established. Further, a parametric study was carried out to investigate the effect of the individual features on the non-linearity in these coatings. This work enables to generate new coating designs by varying the key parameters and predicting the mechanical properties with the help of a simulation, thereby minimizing experiments.

Keywords: crack density, finite element method, plasma sprayed coatings, VUMAT

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Authors: Cristina Isabrl de Oliveira SAntos

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The study aims to investigate how transferrable and effective career conversations could be, in the context of general track Portuguese secondary schools, with the view of improving students’ career competencies. It does so by analysing: 1) the extent to which students’ perceptions of career conversations relate with their existing career competencies, 2) the extent to which each of the parameters; perceptions of career conversations and student career competencies, relate with student situational and personal characteristics, 3) how patterns in perceptions of headteachers and of teachers at a school, regarding the implementation of career conversations, correlate to the views of students regarding career conversations and to school contextual characteristics. Data were collected from 27 secondary schools out of 32 in the same district of Aveiro, in Portugal. Interviews were performed individually, with 27 headteachers, and in groups, with a total of 10 teacher groups and 11 student groups. Survey responses were also collected from742 studentsand 310 teachers. Interview responses were coded and analysed using grounded theory principles. Data from questionnaires is currently beingscrutinised through descriptive statistics with SPSS, and Structural Equation Modelling (SEM). Triangulation during different stages of data analysis uses the principles of retroduction and abduction of the realist evaluation framework. Conclusions from the pilot-study indicate that student perceptions scores on content and relationship in career conversations change according to their career competencies and the type of school. Statistically significant differences in perceptions of career conversations were found for subgroups based on gender and parent educational level.

Keywords: career conversations, career competencies, secondary education, teachers

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Authors: Michael A. Kraus, Navid Pourmoghaddam, Martin Botz, Jens Schneider, Geralt Siebert

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Fragmentation analysis of tempered glass gives insight into the quality of the tempering process and defines a certain degree of safety as well. Different standard such as the European EN 12150-1 or the American ASTM C 1048/CPSC 16 CFR 1201 define a minimum number of fragments required for soda-lime safety glass on the basis of fragmentation test results for classification. This work presents an approach for the glass breakage pattern prediction using a Voronoi Tesselation over Random Fields. The random Voronoi tessellation is trained with and validated against data from several breakage patterns. The fragments in observation areas of 50 mm x 50 mm were used for training and validation. All glass specimen used in this study were commercially available soda-lime glasses at three different thicknesses levels of 4 mm, 8 mm and 12 mm. The results of this work form a Bayesian framework for the training and prediction of breakage patterns of tempered soda-lime glass using a Voronoi Random Field Tesselation. Uncertainties occurring in this process can be well quantified, and several statistical measures of the pattern can be preservation with this method. Within this work it was found, that different Random Fields as basis for the Voronoi Tesselation lead to differently well fitted statistical properties of the glass breakage patterns. As the methodology is derived and kept general, the framework could be also applied to other random tesselations and crack pattern modelling purposes.

Keywords: glass breakage predicition, Voronoi Random Field Tessellation, fragmentation analysis, Bayesian parameter identification

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Authors: Davies Obaromi, Qin Yongsong, James Ndege, Azeez Adeboye, Akinwumi Odeyemi

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The basic model usually used in disease mapping, is the Besag, York and Mollie (BYM) model and which combines the spatially structured and spatially unstructured priors as random effects. Bayesian Conditional Autoregressive (CAR) model is a disease mapping method that is commonly used for smoothening the relative risk of any disease as used in the Besag, York and Mollie (BYM) model. This model (CAR), which is also usually assigned as a prior to one of the spatial random effects in the BYM model, successfully uses information from adjacent sites to improve estimates for individual sites. To our knowledge, there are some unrealistic or counter-intuitive consequences on the posterior covariance matrix of the CAR prior for the spatial random effects. In the conventional BYM (Besag, York and Mollie) model, the spatially structured and the unstructured random components cannot be seen independently, and which challenges the prior definitions for the hyperparameters of the two random effects. Therefore, the main objective of this study is to construct and utilize an extended Bayesian spatial CAR model for studying tuberculosis patterns in the Eastern Cape Province of South Africa, and then compare for flexibility with some existing CAR models. The results of the study revealed the flexibility and robustness of this alternative extended CAR to the commonly used CAR models by comparison, using the deviance information criteria. The extended Bayesian spatial CAR model is proved to be a useful and robust tool for disease modeling and as a prior for the structured spatial random effects because of the inclusion of an extra hyperparameter.

Keywords: Besag2, CAR models, disease mapping, INLA, spatial models

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Authors: Gordon Newlove Asamoah

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This study’s objective is to determine the impact of the African Continental Free Trade Area (AfCFTA) on Ghana using computable general equilibrium (CGE) modelling. The trade data for the simulation was drawn from the standard GTAP database version 10. The study estimated the Ad valorem equivalent (AVE) of Non-Tariff Measures (NTMs) for the Ghanaian sectors which were used for the analysis. Simulations were performed to remove import tariffs and export taxes for 90% of the tariff lines as well as 50% of the NTMs for all the AfCFTA participating countries. The NTMs' reduction was simulated using these two mechanisms: iceberg costs, also known as import augmenting technological change (AMS), and exporter costs (AXS). The study finds that removing the tariffs and NTMs in the AfCFTA regions has a positive impact on Ghana’s GDP, export and import volumes, terms of trade and welfare as measured by the equivalent variations. However, Ghana recorded a deficit of US$4766.69 million as a trade balance due to its high importation bills. This is not by chance, as Ghana is an importer of high-value-added goods but an exporter of basic agricultural raw materials with low export earnings. The study also finds much larger positive impacts for the AfCFTA regions for both importers and exporters when the NTMs that work as iceberg costs and export costs are reduced. It further finds that by reducing the export cost that increases the cost of intermediate inputs, trade among the AfCFTA regions (intra-AfCFTA trade) is enhanced.

Keywords: impact, AfCFTA, NTMs, Ghana, CGE

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Authors: Lukman Thalib, Luis Furuya-Kanamori, Rachel Walker, Brigid Gillespie, Suhail Doi

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Background and objectives: There are many topical treatments available for Pressure Injury (PI) treatment, yet there is a lack of evidence with regards to the most effective treatment. The objective of this study was to compare the effect of various topical treatments and identify the best treatment choice(s) for PI healing. Methods: Network meta-analysis of published randomized controlled trials that compared the two or more of the following dressing groups: basic, foam, active, hydroactive, and other wound dressings. The outcome complete healing following treatment and the generalised pair-wise modelling framework was used to generate mixed treatment effects against hydroactive wound dressing, currently the standard of treatment for PIs. All treatments were then ranked by their point estimates. Main Results: 40 studies (1,757 participants) comparing 5 dressing groups were included in the analysis. All dressings groups ranked better than basic (i.e. saline gauze or similar inert dressing). The foam (RR 1.18; 95%CI 0.95-1.48) and active wound dressing (RR 1.16; 95%CI 0.92-1.47) ranked better than hydroactive wound dressing in terms of healing of PIs when the latter was used as the reference group. Conclusion & Recommendations: There was considerable uncertainty around the estimates, yet, the use of hydroactive wound dressings appear to perform better than basic dressings. Foam and active wound dressing groups show promise and need further investigation. High-quality research on clinical effectiveness of the topical treatments are warranted to identify if foam and active wound dressings do provide advantages over hydroactive dressings.

Keywords: Net work Meta Analysis, Pressure Injury, Dresssing, Pressure Ulcer

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Authors: R. Suresh, Pavan Kumar Nimmagadda, Ming Zo Tan, Shane Hart, Sharp Ugwuocha

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Polycrystalline diamond compact (PDC) drill bits are extensively used in the oil and gas industry as well as the mining industry. Industry engineers continually improve upon PDC drill bit designs and hydraulic conditions. Optimized injection nozzles play a key role in improving the drilling performance and efficiency of these ever changing PDC drill bits. In the first part of this study, computational fluid dynamics (CFD) modelling is performed to investigate the hydrodynamic characteristics of drilling fluid flow around the PDC drill bit. An Open-source CFD software – OpenFOAM simulates the flow around the drill bit, based on the field input data. A specifically developed console application integrates the entire CFD process including, domain extraction, meshing, and solving governing equations and post-processing. The results from the OpenFOAM solver are then compared with that of the ANSYS Fluent software. The data from both software programs agree. The second part of the paper describes the parametric study of the PDC drill bit nozzle to determine the effect of parameters such as number of nozzles, nozzle velocity, nozzle radial position and orientations on the flow field characteristics and bit washing patterns. After analyzing a series of nozzle configurations, the best configuration is identified and recommendations are made for modifying the PDC bit design.

Keywords: ANSYS Fluent, computational fluid dynamics, nozzle configuration, OpenFOAM, PDC dill bit

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Authors: Sandeep Kaur, Jenny Vuong, Marcel Julliard, Sean O'Donoghue

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Time-series data are useful for modelling as they can enable model-evaluation. However, when reconstructing models from phosphoproteomic data, often non-exact methods are utilised, as the knowledge regarding the network structure, such as, which kinases and phosphatases lead to the observed phosphorylation state, is incomplete. Thus, such reactions are often hypothesised, which gives rise to uncertainty. Here, we propose a framework, implemented via a web-based tool (as an extension to Minardo), which given time-series phosphoproteomic datasets, can generate κ models. The incompleteness and uncertainty in the generated model and reactions are clearly presented to the user via the visual method. Furthermore, we demonstrate, via a toy EGF signalling model, the use of algorithmic verification to verify κ models. Manually formulated requirements were evaluated with regards to the model, leading to the highlighting of the nodes causing unsatisfiability (i.e. error causing nodes). We aim to integrate such methods into our web-based tool and demonstrate how the identified erroneous nodes can be presented to the user via the visual method. Thus, in this research we present a framework, to enable a user to explore phosphorylation proteomic time-series data in the context of models. The observer can visualise which reactions in the model are highly uncertain, and which nodes cause incorrect simulation outputs. A tool such as this enables an end-user to determine the empirical analysis to perform, to reduce uncertainty in the presented model - thus enabling a better understanding of the underlying system.

Keywords: κ-models, model verification, time-series phosphoproteomic datasets, uncertainty and error visualisation

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Authors: Jeremiah Madzimure

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In order to stay competitive in business and improve performance, Small and Medium Enterprises (SMEs) need to make use of business networking and logistics integration. Strategic networking and logistics integration in business companies have become critical as they allow supplier partnering, exchange of vital information/ access to valuable resources allowing innovation, gaining access to additional resources, sharing risks and costs which is required for enhancing company performance. The purpose of this study was to examine the influence of strategic networks and logistics integration on company performance: the case of small and medium enterprises in South Africa. A quantitative research design was adopted in this study, and 137 SMEs owners and managers completed and returned the survey questionnaire. Confirmatory Factor Analysis (CFA) was conducted using the Analysis of Moment Structures (AMOS), version 24.0 to assess psychometric properties of the measurement scales. Path modelling techniques were used to test the proposed hypothesis. Three research hypotheses were postulated. The results indicate that strategic networks had a positive and significant influence on logistics integration and company performance. As well logistics integration had a strong positive and significant influence on company performance. This study provides a useful model for analysing the relationship between strategic networks and logistics integration on company performance. Moreover, the findings of the study provide useful insights into how SMEs should benefit from business networking and logistics integration so as to improve their performance. The implications of the study are discussed, and finally, limitations and recommendations are indicated.

Keywords: strategic networking, logistics integration, company performance, SMEs

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Authors: Fadlan Atmaja Nursiwan, Ugi Kurnia Gusti

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Garba Hill, located in Tekana Village, South Sumatera Province is comprised to South Sumatra Basin and classified as back arc basin. This area is entered as an active margin of Sundaland which experiences subduction several times since Mesozoic to recent time. The traces of Mesozoic subduction in the southern part of Sumatra island are exposed in Garba Hill area. The aim of this investigation is to study the tectonic changes in the first phase in Mesozoic era at the active margin of Sundaland which causes the rocks assemblage in Garba hill consist of continental and oceanic plate rocks which the correlation between those rocks show indistinct relation. This investigation is conducted by field observation in Tekana village and Lubar Village, Muara Dua, South Sumatra along with laboratory analysis included fossil and geochemistry analysis of radiolarian chert, petrography analysis of granite and basalt, and structural modelling. Fossil and geochemistry analysis of radiolarian chert and geochemistry of granite rocks shown the relation between the two rocks and Mesozoic subduction of Woyla terrane on western margin of Sundaland. Petrography analysis from granite and basalt depict the tectonic affinity of rocks. Moreover, structural analysis showed the changes of lineation direction from N-S to WNW-ESE.

Keywords: granite, mesozoic, radiolarian, subduction traces

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Authors: Bavneet Kaur Sidhu, Manoj Tiwari

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Global Developmental Delay (GDD) is a common pediatric condition. Etiologies of GDD might, however, differ in developing countries. In the last decade, sporadic families are being reported in various countries. As to the author’s best knowledge, many risk factors and their correlation with the prevalence of GDD have been studied but its statistical correlation has not been done. Thus we propose the present study by targeting the risk factor, prevalence and their statistical correlation with GDD. FMR1 gene was studied to confirm the disease and its penetrance. A complete questionnaire-based performance was designed for the statistical studies having a personal, past and present medical history along with their socio-economic status as well. Methods: We distributed the children’s age in 4 different age groups having 5-year intervals and applied structural equation modeling (SEM) techniques, Spearman’s rank correlation coefficient, Karl Pearson correlation coefficient, and chi-square test.Result: A total of 1100 families were enrolled for this study; among them, 330 were clinically and biologically confirmed (radiological studies) for the disease, 204 were males (61.8%), 126 were females (38.18%). We found that 27.87% were genetic and 72.12 were sporadic, out of 72.12 %, 43.277% cases from urban and 56.72% from the rural locality, the mothers' literacy rate was 32.12% and working women numbers were 41.21%. Conclusions: There is a significant association between mothers' age and GDD prevalence, which is also followed by mothers' literacy rate and mothers' occupation, whereas there was no association between fathers' age and GDD.

Keywords: global developmental delay, FMR1 gene, spearman’ rank correlation coefficient, structural equation modeling

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Authors: Sara Torabi, Sadegh Khazalpour, Mahdi Jamshidi

Abstract:

Nitro aromatic compounds are valuable materials because of their applications in the preparation of chemical intermediates for the synthesis of dyes, plastics, perfumes, energetic materials, and pharmaceuticals. Chemical and electrochemical procedures are reported for nitration of aromatic compounds. Flavonoid derivatives are present in many vegetables and fruits and are constituent of many common pharmaceuticals and dietary supplements. Electrochemistry provides very versatile means for the electrosynthesis, mechanistic and kinetic studies. To the best of our knowledge, and despite the importance of these compounds in numerous scientific fields, there are no reports on the electrochemical nitration of Quercetin derivatives. Herein, we describe a green electrochemical synthesis of a nitro compound. In this work, electrochemical oxidation of Quercetin has been studied in the presence of nitrite ion as a nucleophile in acetate buffer solution (c = 0.2 M, pH = 6.0), by means of cyclic voltammetry and controlled-potential coulometry. The results indicate the participation of produced o-benzoquinones in Michael reaction with nitrite ion (in the divided cell) to form the corresponding nitro diol (EC mechanism). The purity of product and characterization was done using ¹H NMR, ¹³C NMR, FTIR spectroscopic techniques. The presented strategies use a water/ethanol mixture as solvent. Ethanol as cosolvent was also used in the previous studies because of its low cost, safety, easy availability, recyclability, bioproductability, and biodegradability. These strategies represent a one-pot and facile process for the synthesis of nitro compound in high yield and purity under green conditions.

Keywords: electrochemical synthesis, green chemistry, cyclic voltammetry, molecular docking

Procedia PDF Downloads 146

Authors: Balimu Mwiya, Mundia Muya, Chabota Kaliba, Peter Mukalula

Abstract:

Factors affecting construction unit cost vary depending on a country’s political, economic, social and technological inclinations. Factors affecting construction costs have been studied from various perspectives. Analysis of cost factors requires an appreciation of a country’s practices. Identified cost factors provide an indication of a country’s construction economic strata. The purpose of this paper is to identify the essential factors that affect unit cost estimation and their breakdown using artificial neural networks. Twenty-five (25) identified cost factors in road construction were subjected to a questionnaire survey and employing SPSS factor analysis the factors were reduced to eight. The 8 factors were analysed using the neural network (NN) to determine the proportionate breakdown of the cost factors in a given construction unit rate. NN predicted that political environment accounted 44% of the unit rate followed by contractor capacity at 22% and financial delays, project feasibility, overhead and profit each at 11%. Project location, material availability and corruption perception index had minimal impact on the unit cost from the training data provided. Quantified cost factors can be incorporated in unit cost estimation models (UCEM) to produce more accurate estimates. This can create improvements in the cost estimation of infrastructure projects and establish a benchmark standard to assist the process of alignment of work practises and training of new staff, permitting the on-going development of best practises in cost estimation to become more effective.

Keywords: construction cost factors, neural networks, roadworks, Zambian construction industry

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Authors: Anna Dolinayova, Juraj Camaj, Martin Loch

Abstract:

Presently it is necessary to ensure the sustainable development of passenger and freight transport. Increasing performance of road freight have been a negative impact to environment and society. It is therefore necessary to increase the competitiveness of intermodal transport, which is more environmentally friendly. The study describe the effectiveness of logistical centers realization for companies and society and research how the partial internalization of external costs reflected in the efficient use of these centers and increase the competitiveness of intermodal transport to road freight. In our research, we use the method of comparative analysis and market research to describe the advantages of logistic centers for their users as well as for society as a whole. Method normal costing is used for calculation infrastructure and total costs, method of conversion costing for determine the external costs. We modelling of total society costs for road freight transport and inter modal transport chain (we assumed that most of the traffic is carried by rail) with different loading schemes for condition in the Slovak Republic. Our research has shown that higher utilization of inter modal transport chain do good not only for society, but for companies providing freight services too. Increase in use of inter modal transport chain can bring many benefits to society that do not bring direct immediate financial return. They often bring the multiplier effects, such as greater use of environmentally friendly transport mode and reduce the total society costs.

Keywords: delivery time, economy effectiveness, logistical centers, ecological efficiency, optimization, society

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Authors: Mohamed S. El-Asfoury, Ahmed Abdel-Moneim, Mohamed N. A. Nasr

Abstract:

The current study uses finite element modeling to investigate and analyze a modified form of the from the conventional equal channel multi-angular pressing (ECMAP), using non-equal channels, on the workpiece material plastic deformation. The modified process non-equal channel multi-angular extrusion (NECMAE) is modeled using two-dimensional plane strain finite element model built using the commercial software ABAQUS. The workpiece material used is pure aluminum. The model was first validated by comparing its results to analytical solutions for single-pass equal channel angular extrusion (ECAP), as well as previously published data. After that, the model was used to examine the effects of different % of reductions of the area (for the second stage) on material plastic deformation, corner gap, and required the load. Three levels of reduction in the area were modeled; 10%, 30%, and 50%, and compared to single-pass and double-pass ECAP. Cases with a higher reduction in the area were found to have smaller corner gaps, higher and much uniform plastic deformation, as well as higher required loads. The current results are mainly attributed to the back pressure effects exerted by the second stage, as well as strain hardening effects experienced during the first stage.

Keywords: non-equal channel angular extrusion, multi-pass, sever plastic deformation, back pressure, Finite Element Modelling (FEM)

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Authors: Omil Nady Mahrous Maximous

Abstract:

The construction industry is currently experiencing a shift towards digitisation. This transformation is driven by adopting technologies like Building Information Modelling (BIM), drones, and augmented reality (AR). These advancements are revolutionizing the process of designing, constructing, and operating projects. BIM, for instance, is a new way of communicating and exploiting technology such as software and machinery. It enables the creation of a replica or virtual model of buildings or infrastructure projects. It facilitates simulating construction procedures, identifying issues beforehand, and optimizing designs accordingly. Drones are another tool in this revolution, as they can be utilized for site surveys, inspections, and even deliveries. Moreover, AR technology provides real-time information to workers involved in the project. Implementing these technologies in the construction industry has brought about improvements in efficiency, safety measures, and sustainable practices. BIM helps minimize rework and waste materials, while drones contribute to safety by reducing workers' exposure to areas. Additionally, AR plays a role in worker safety by delivering instructions and guidance during operations. Although the digital transformation within the construction industry is still in its early stages, it holds the potential to reshape project delivery methods entirely. By embracing these technologies, construction companies can boost their profitability while simultaneously reducing their environmental impact and ensuring safer practices.

Keywords: architectural education, construction industry, digital learning environments, immersive learning BIM, digital construction, construction technologies, digital transformation artificial intelligence, collaboration, digital architecture, digital design theory, material selection, space construction

Procedia PDF Downloads 59

Authors: Michael K.O. Ayomoh, Khaled A. Abou-El-Hossein., Sameh F.M. Ghobashy

Abstract:

This paper proposes a numerical modelling scheme for surface roughness prediction. The approach is premised on the use of 3D difference analysis method enhanced with the use of feedback control loop where a set of adaptive weights are generated. The surface roughness values utilized in this paper were adapted from [1]. Their experiments were carried out using S55C high carbon steel. A comparison was further carried out between the proposed technique and those utilized in [1]. The experimental design has three cutting parameters namely: depth of cut, feed rate and cutting speed with twenty-seven experimental sample-space. The simulation trials conducted using Matlab software is of two sub-classes namely: prediction of the surface roughness readings for the non-boundary cutting combinations (NBCC) with the aid of the known surface roughness readings of the boundary cutting combinations (BCC). The following simulation involved the use of the predicted outputs from the NBCC to recover the surface roughness readings for the boundary cutting combinations (BCC). The simulation trial for the NBCC attained a state of total stability in the 7th iteration i.e. a point where the actual and desired roughness readings are equal such that error is minimized to zero by using a set of dynamic weights generated in every following simulation trial. A comparative study among the three methods showed that the proposed difference analysis technique with adaptive weight from feedback control, produced a much accurate output as against the abductive and regression analysis techniques presented in this.

Keywords: Difference Analysis, Surface Roughness; Mesh- Analysis, Feedback control, Adaptive weight, Boundary Element

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Authors: Mariem Saadi, Sabri Kanzari, Adel Zghibi

Abstract:

In semi-arid areas like the Kairouan region, the constant irrigation with saline water and the overuse of groundwater resources, soils and aquifers salinization has become an increasing concern. In this study, a methodology has been developed to evaluate the groundwater contamination risk based on the unsaturated zone hydraulic properties. Two soil profiles with different ranges of salinity, one located in the north of the plain and another one in the south of plain (each 30 m deep) and both characterized by direct recharge of the aquifer were chosen. Simulations were conducted with Hydrus-1D code using measured precipitation data for the period 1998-2003 and calculated evapotranspiration for both chosen profiles. Four combinations of initial conditions of water content and salt concentration were used for the simulation process in order to find the best match between simulated and measured values. The success of the calibration of Hydrus-1D allowed the investigation of some scenarios in order to assess the contamination risk under different natural conditions. The aquifer risk contamination is related to the natural conditions where it increased while facing climate change and temperature increase and decreased in the presence of a clay layer in the unsaturated zone. Hydrus-1D was a useful tool to predict the groundwater level and quality in the case of a direct recharge and in the absence of any information related to the soil layers except for the texture.

Keywords: Hydrus-1D, Kairouan, salinization, semi-arid region, solute transport, unsaturated zone

Procedia PDF Downloads 183

Authors: Mohamed Mohamed, Philip Bonello, Peter Russhard

Abstract:

Blade Tip Timing (BTT) is a technology concerned with the estimation of both frequency and amplitude of rotating blades. A BTT system comprises two main parts: (a) the arrival time measurement system, and (b) the analysis algorithms. Simulators play an important role in the development of the analysis algorithms since they generate blade tip displacement data from the simulated blade vibration under controlled conditions. This enables an assessment of the performance of the different algorithms with respect to their ability to accurately reproduce the original simulated vibration. Such an assessment is usually not possible with real engine data since there is no practical alternative to BTT for blade vibration measurement. Most simulators used in the literature are based on a simple spring-mass-damper model to determine the vibration. In this work, a more realistic experimentally validated simulator based on the Finite Element (FE) model of a bladed disc (blisk) is first presented. It is then used to generate the necessary data for the assessment of different BTT algorithms. The FE modelling is validated using both a hammer test and two firewire cameras for the mode shapes. A number of autoregressive methods, fitting methods and state-of-the-art inverse methods (i.e. Russhard) are compared. All methods are compared with respect to both synchronous and asynchronous excitations with both single and simultaneous frequencies. The study assesses the applicability of each method for different conditions of vibration, amount of sampling data, and testing facilities, according to its performance and efficiency under these conditions.

Keywords: blade tip timing, blisk, finite element, vibration measurement

Procedia PDF Downloads 312