Search results for: predictive modelling

Authors: I. Valdez, J. Perdomo, M. Colindres, N. Castro

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Today, digital servo systems are extensively used in industrial manufacturing processes, robotic applications, vehicles and other areas. In such control systems, control action is provided by digital controllers with different compensation algorithms, which are designed to meet specific requirements for a given application. Due to the constant search for optimization in industrial processes, it is of interest to design digital controllers that offer ease of realization, improved computational efficiency, affordable return rates, and ease of tuning that ultimately improve the performance of the controlled actuators. There is a vast range of options of compensation algorithms that could be used, although in the industry, most controllers used are based on a PID structure. This research article compares different types of digital compensators implemented in a servo system for DC motor position control. PID compensation is evaluated on its two most common architectures: PID position form (1 DOF), and PID speed form (2 DOF). State feedback algorithms are also evaluated, testing two modern control theory techniques: discrete state observer for non-measurable variables tracking, and a linear quadratic method which allows a compromise between the theoretical optimal control and the realization that most closely matches it. The compared control systems’ performance is evaluated through simulations in the Simulink platform, in which it is attempted to model accurately each of the system’s hardware components. The criteria by which the control systems are compared are reference tracking and disturbance rejection. In this investigation, it is considered that the accurate tracking of the reference signal for a position control system is particularly important because of the frequency and the suddenness in which the control signal could change in position control applications, while disturbance rejection is considered essential because the torque applied to the motor shaft due to sudden load changes can be modeled as a disturbance that must be rejected, ensuring reference tracking. Results show that 2 DOF PID controllers exhibit high performance in terms of the benchmarks mentioned, as long as they are properly tuned. As for controllers based on state feedback, due to the nature and the advantage which state space provides for modelling MIMO, it is expected that such controllers evince ease of tuning for disturbance rejection, assuming that the designer of such controllers is experienced. An in-depth multi-dimensional analysis of preliminary research results indicate that state feedback control method is more satisfactory, but PID control method exhibits easier implementation in most control applications.

Keywords: control, DC motor, discrete PID, discrete state feedback

Procedia PDF Downloads 245

Authors: Temitayo Abayomi Ewemoje, Oluwamayowa Oluwafemi Oluwaniyi

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Agriculture and food processing, industry are among the largest industrial sectors that uses large amount of energy. Thus, a larger amount of gases from their fuel combustion technologies is being released into the environment. The choice of input energy supply not only directly having affects the environment, but also poses a threat to human health. The study was therefore designed to assess each unit production processes in order to identify hotspots using life cycle assessments (LCA) approach in South-western Nigeria. Data such as machine power rating, operation duration, inputs and outputs of shea butter materials for unit processes obtained at site were used to modelled Life Cycle Impact Analysis on GaBi6 (Holistic Balancing) software. Four scenarios were drawn for the impact assessments. Material sourcing from Kaiama, Scenarios 1, 3 and Minna Scenarios 2, 4 but different heat supply sources (Liquefied Petroleum Gas ‘LPG’ Scenarios 1, 2 and 10.8 kW Diesel Heater, scenarios 3, 4). Modelling of shea butter production on GaBi6 was for 1kg functional unit of shea butter produced and the Tool for the Reduction and Assessment of Chemical and other Environmental Impacts (TRACI) midpoint assessment was tool used to was analyse the life cycle inventories of the four scenarios. Eight categories in all four Scenarios were observed out of which three impact categories; Global Warming Potential (GWP) (0.613, 0.751, 0.661, 0.799) kg CO2¬-Equiv., Acidification Potential (AP) (0.112, 0.132, 0.129, 0.149) kg H+ moles-Equiv., and Smog (0.044, 0.059, 0.049, 0.063) kg O3-Equiv., categories had the greater impacts on the environment in Scenarios 1-4 respectively. Impacts from transportation activities was also seen to contribute more to these environmental impact categories due to large volume of petrol combusted leading to releases of gases such as CO2, CH4, N2O, SO2, and NOx into the environment during the transportation of raw shea kernel purchased. The ratio of transportation distance from Minna and Kaiama to production site was approximately 3.5. Shea butter unit processes with greater impacts in all categories was the packaging, milling and with the churning processes in ascending order of magnitude was identified as hotspots that may require attention. From the 1kg shea butter functional unit, it was inferred that locating production site at the shortest travelling distance to raw material sourcing and combustion of LPG for heating would reduce all the impact categories assessed on the environment.

Keywords: GaBi6, Life cycle assessment, shea butter production, TRACI

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Authors: Sittampalam Manoharan, Gary Chai, Sanaul Chowdhury, Andrew Golding

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The primary objective of this paper is to present a simplified approach to develop the structural deterioration model using traffic speed deflectometer data for flexible pavements. Maintaining assets to meet functional performance is not economical or sustainable in the long terms, and it would end up needing much more investments for road agencies and extra costs for road users. Performance models have to be included for structural and functional predicting capabilities, in order to assess the needs, and the time frame of those needs. As such structural modelling plays a vital role in the prediction of pavement performance. A structural condition is important for the prediction of remaining life and overall health of a road network and also major influence on the valuation of road pavement. Therefore, the structural deterioration model is a critical input into pavement management system for predicting pavement rehabilitation needs accurately. The Traffic Speed Deflectometer (TSD) is a vehicle-mounted Doppler laser system that is capable of continuously measuring the structural bearing capacity of a pavement whilst moving at traffic speeds. The device’s high accuracy, high speed, and continuous deflection profiles are useful for network-level applications such as predicting road rehabilitations needs and remaining structural service life. The methodology adopted in this model by utilizing time series TSD maximum deflection (D0) data in conjunction with rutting, rutting progression, pavement age, subgrade strength and equivalent standard axle (ESA) data. Then, regression analyses were undertaken to establish a correlation equation of structural deterioration as a function of rutting, pavement age, seal age and equivalent standard axle (ESA). This study developed a simple structural deterioration model which will enable to incorporate available TSD structural data in pavement management system for developing network-level pavement investment strategies. Therefore, the available funding can be used effectively to minimize the whole –of- life cost of the road asset and also improve pavement performance. This study will contribute to narrowing the knowledge gap in structural data usage in network level investment analysis and provide a simple methodology to use structural data effectively in investment decision-making process for road agencies to manage aging road assets.

Keywords: adjusted structural number (SNP), maximum deflection (D0), equant standard axle (ESA), traffic speed deflectometer (TSD)

Procedia PDF Downloads 134

Authors: Nozar Kishi, Babak Kamrani, Filmon Habte

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Natural hazards such as earthquakes and tropical storms, are very frequent and highly destructive in Japan. Japan experiences, every year on average, more than 10 tropical cyclones that come within damaging reach, and earthquakes of moment magnitude 6 or greater. We have developed stochastic catastrophe models to address the risk associated with the entire suite of damaging events in Japan, for use by insurance, reinsurance, NGOs and governmental institutions. KCC’s (Karen Clark and Company) catastrophe models are procedures constituted of four modular segments: 1) stochastic events sets that would represent the statistics of the past events, hazard attenuation functions that could model the local intensity, vulnerability functions that would address the repair need for local buildings exposed to the hazard, and financial module addressing policy conditions that could estimates the losses incurring as result of. The events module is comprised of events (faults or tracks) with different intensities with corresponding probabilities. They are based on the same statistics as observed through the historical catalog. The hazard module delivers the hazard intensity (ground motion or wind speed) at location of each building. The vulnerability module provides library of damage functions that would relate the hazard intensity to repair need as percentage of the replacement value. The financial module reports the expected loss, given the payoff policies and regulations. We have divided Japan into regions with similar typhoon climatology, and earthquake micro-zones, within each the characteristics of events are similar enough for stochastic modeling. For each region, then, a set of stochastic events is developed that results in events with intensities corresponding to annual occurrence probabilities that are of interest to financial communities; such as 0.01, 0.004, etc. The intensities, corresponding to these probabilities (called CE, Characteristics Events) are selected through a superstratified sampling approach that is based on the primary uncertainty. Region specific hazard intensity attenuation functions followed by vulnerability models leads to estimation of repair costs. Extensive economic exposure model addresses all local construction and occupancy types, such as post-linter Shinand Okabe wood, as well as concrete confined in steel, SRC (Steel-Reinforced Concrete), high-rise.

Keywords: typhoon, earthquake, Japan, catastrophe modelling, stochastic modeling, stratified sampling, loss model, ERM

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Authors: Tugbanur Ozen Balaban, Gultekin Tarcan, Unsal Gemici, Mumtaz Colak, I. Hakki Karamanderesi

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Buyuk Menderes Graben is located in the Western Anatolia (Turkey). The graben has become the largest industrial and agricultural area with a total population exceeding 3.000.000. There are two big cities within the study areas from west to east as Aydın and Denizli. The study area is very rich with regard to cold ground waters and thermal waters. Electrical production using geothermal potential has become very popular in the last decades in this area. Buyuk Menderes Graben is a tectonically active extensional region and is undergoing a north–south extensional tectonic regime which commenced at the latest during Early Middle Miocene period. The basement of the study area consists of Menderes massif rocks that are made up of high-to low-grade metamorphics and they are aquifer for both cold ground waters and thermal waters depending on the location. Neogene terrestrial sediments, which are mainly composed by alluvium fan deposits unconformably cover the basement rocks in different facies have very low permeability and locally may act as cap rocks for the geothermal systems. The youngest unit is Quaternary alluvium which is the shallow regional aquifer consists of Holocene alluvial deposits in the study area. All the waters are of meteoric origin and reflect shallow or deep circulation according to the 8O, 2H and 3H contents. Meteoric waters move to deep zones by fractured system and rise to the surface along the faults. Water samples (drilling well, spring and surface waters) and local seawater were collected between 2010 and 2012 years. Geochemical modeling was calculated distribution of the aqueous species and exchange processes by using PHREEQCi speciation code. Geochemical analyses show that cold ground water types are evolving from Ca–Mg–HCO3 to Na–Cl–SO4 and geothermal aquifer waters reflect the water types of Na-Cl-HCO3 in Aydın. Water types of Denizli are Ca-Mg-HCO3 and Ca-Mg-HCO3-SO4. Thermal water types reflect generally Na-HCO3-SO4. The B versus Cl rates increase from east to west with the proportion of seawater introduced into the fresh water aquifers and geothermal reservoirs. Concentrations of some elements (As, B, Fe and Ni) are higher than the tolerance limit of the drinking water standard of Turkey (TS 266) and international drinking water standards (WHO, FAO etc).

Keywords: Buyuk Menderes, isotope chemistry, geochemical modelling, water quality

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Authors: Sina Abadzadesahraei, Stephen Déry, John Rex

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Climate research has repeatedly identified strong associations between anthropogenic emissions of ‘greenhouses gases’ and observed increases of global mean surface air temperature over the past century. Studies have also demonstrated that the degree of warming varies regionally. Canada is not exempt from this situation, and evidence is mounting that climate change is beginning to cause diverse impacts in both environmental and socio-economic spheres of interest. For example, northeastern British Columbia (BC), whose climate is controlled by a combination of maritime, continental and arctic influences, is warming at a greater rate than the remainder of the province. There are indications that these changing conditions are already leading to shifting patterns in the region’s hydrological cycle, and thus its available water resources. Coincident with these changes, northeastern BC is undergoing rapid development for oil and gas extraction: This depends largely on subsurface hydraulic fracturing (‘fracking’), which uses enormous amounts of freshwater. While this industrial activity has made substantial contributions to regional and provincial economies, it is important to ensure that sufficient and sustainable water supplies are available for all those dependent on the resource, including ecological systems. In this turn demands a comprehensive understanding of how water in all its forms interacts with landscapes, the atmosphere, and of the potential impacts of changing climatic conditions on these processes. The aim of this study is therefore to characterize and quantify all components of the water budget in the small watershed of Coles Lake (141.8 km², 100 km north of Fort Nelson, BC), through a combination of field observations and numerical modelling. Baseline information will aid the assessment of the sustainability of current and future plans for freshwater extraction by the oil and gas industry, and will help to maintain the precarious balance between economic and environmental well-being. This project is a perfect example of interdisciplinary research, in that it not only examines the hydrology of the region but also investigates how natural gas operations and growth can affect water resources. Therefore, a fruitful collaboration between academia, government and industry has been established to fulfill the objectives of this research in a meaningful manner. This project aims to provide numerous benefits to BC communities. Further, the outcome and detailed information of this research can be a huge asset to researchers examining the effect of climate change on water resources worldwide.

Keywords: northeastern British Columbia, water resources, climate change, oil and gas extraction

Procedia PDF Downloads 238

Authors: Eunsu Jang, Kang Park

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In developing an armored ground combat vehicle (AGCV), it is a very important step to analyze the vulnerability (or the survivability) of the AGCV against enemy’s attack. In the vulnerability analysis, the penetration equations are usually used to get the penetration depth and check whether a bullet can penetrate the armor of the AGCV, which causes the damage of internal components or crews. The penetration equations are derived from penetration experiments which require long time and great efforts. However, they usually hold only for the specific material of the target and the specific type of the bullet used in experiments. Thus, penetration simulation using ANSYS can be another option to calculate penetration depth. However, it is very important to model the targets and select the input parameters in order to get an accurate penetration depth. This paper performed a sensitivity analysis of input parameters of ANSYS on the accuracy of the calculated penetration depth. Two conflicting objectives need to be achieved in adopting ANSYS in penetration analysis: maximizing the accuracy of calculation and minimizing the calculation time. To maximize the calculation accuracy, the sensitivity analysis of the input parameters for ANSYS was performed and calculated the RMS error with the experimental data. The input parameters include mesh size, boundary condition, material properties, target diameter are tested and selected to minimize the error between the calculated result from simulation and the experiment data from the papers on the penetration equation. To minimize the calculation time, the parameter values obtained from accuracy analysis are adjusted to get optimized overall performance. As result of analysis, the followings were found: 1) As the mesh size gradually decreases from 0.9 mm to 0.5 mm, both the penetration depth and calculation time increase. 2) As diameters of the target decrease from 250mm to 60 mm, both the penetration depth and calculation time decrease. 3) As the yield stress which is one of the material property of the target decreases, the penetration depth increases. 4) The boundary condition with the fixed side surface of the target gives more penetration depth than that with the fixed side and rear surfaces. By using above finding, the input parameters can be tuned to minimize the error between simulation and experiments. By using simulation tool, ANSYS, with delicately tuned input parameters, penetration analysis can be done on computer without actual experiments. The data of penetration experiments are usually hard to get because of security reasons and only published papers provide them in the limited target material. The next step of this research is to generalize this approach to anticipate the penetration depth by interpolating the known penetration experiments. This result may not be accurate enough to be used to replace the penetration experiments, but those simulations can be used in the early stage of the design process of AGCV in modelling and simulation stage.

Keywords: ANSYS, input parameters, penetration depth, sensitivity analysis

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Authors: Sara A. Ben Lashihar

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The heritage building information modelling (HBIM) of the historical masonry buildings has expanded lately to meet the urgent needs for conservation and structural analysis. The masonry structures are unique features for ancient building architectures worldwide that have special cultural, spiritual, and historical significance. However, there is a research gap regarding the reliability of the HBIM modeling process of these structures. The HBIM modeling process of the masonry structures faces significant challenges due to the inherent complexity and uniqueness of their structural systems. Most of these processes are based on tracing the point clouds and rarely follow documents, archival records, or direct observation. The results of these techniques are highly abstracted models where the accuracy does not exceed LOD 200. The masonry assemblages, especially curved elements such as arches, vaults, and domes, are generally modeled with standard BIM components or in-place models, and the brick textures are graphically input. Hence, future investigation is necessary to establish a methodology to generate automatically parametric masonry components. These components are developed algorithmically according to mathematical and geometric accuracy and the validity of the survey data. The main aim of this paper is to provide a comprehensive review of the state of the art of the existing researches and papers that have been conducted on the HBIM modeling of the masonry structural elements and the latest approaches to achieve parametric models that have both the visual fidelity and high geometric accuracy. The paper reviewed more than 800 articles, proceedings papers, and book chapters focused on "HBIM and Masonry" keywords from 2017 to 2021. The studies were downloaded from well-known, trusted bibliographic databases such as Web of Science, Scopus, Dimensions, and Lens. As a starting point, a scientometric analysis was carried out using VOSViewer software. This software extracts the main keywords in these studies to retrieve the relevant works. It also calculates the strength of the relationships between these keywords. Subsequently, an in-depth qualitative review followed the studies with the highest frequency of occurrence and the strongest links with the topic, according to the VOSViewer's results. The qualitative review focused on the latest approaches and the future suggestions proposed in these researches. The findings of this paper can serve as a valuable reference for researchers, and BIM specialists, to make more accurate and reliable HBIM models for historic masonry buildings.

Keywords: HBIM, masonry, structure, modeling, automatic, approach, parametric

Procedia PDF Downloads 144

Authors: Nurkhairul Bariyah Baharun, Afzan Adam, Reena Rahayu Md Zin

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Tumor microenvironment (TME) in breast cancer is mainly composed of cancer cells, immune cells, and stromal cells. The interaction between cancer cells and their microenvironment plays an important role in tumor development, progression, and treatment response. The TME in breast cancer includes tumor-infiltrating lymphocytes (TILs) that are implicated in killing tumor cells. TILs can be found in tumor stroma (sTILs) and within the tumor (iTILs). TILs in triple negative breast cancer (TNBC) have been demonstrated to have prognostic and potentially predictive value. The international Immune-Oncology Biomarker Working Group (TIL-WG) had developed a guideline focus on the assessment of sTILs using hematoxylin and eosin (H&E)-stained slides. According to the guideline, the pathologists use “eye balling” method on the H&E stained- slide for sTILs assessment. This method has low precision, poor interobserver reproducibility, and is time-consuming for a comprehensive evaluation, besides only counted sTILs in their assessment. The TIL-WG has therefore recommended that any algorithm for computational assessment of TILs utilizing the guidelines provided to overcome the limitations of manual assessment, thus providing highly accurate and reliable TILs detection and classification for reproducible and quantitative measurement. This study is carried out to develop a TNBC digital whole slide image (WSI) dataset from H&E-stained slides and IHC (CD4+ and CD8+) stained slides. TNBC cases were retrieved from the database of the Department of Pathology, Hospital Canselor Tuanku Muhriz (HCTM). TNBC cases diagnosed between the year 2010 and 2021 with no history of other cancer and available block tissue were included in the study (n=58). Tissue blocks were sectioned approximately 4 µm for H&E and IHC stain. The H&E staining was performed according to a well-established protocol. Indirect IHC stain was also performed on the tissue sections using protocol from Diagnostic BioSystems PolyVue™ Plus Kit, USA. The slides were stained with rabbit monoclonal, CD8 antibody (SP16) and Rabbit monoclonal, CD4 antibody (EP204). The selected and quality-checked slides were then scanned using a high-resolution whole slide scanner (Pannoramic DESK II DW- slide scanner) to digitalize the tissue image with a pixel resolution of 20x magnification. A manual TILs (sTILs and iTILs) assessment was then carried out by the appointed pathologist (2 pathologists) for manual TILs scoring from the digital WSIs following the guideline developed by TIL-WG 2014, and the result displayed as the percentage of sTILs and iTILs per mm² stromal and tumour area on the tissue. Following this, we aimed to develop an automated digital image scoring framework that incorporates key elements of manual guidelines (including both sTILs and iTILs) using manually annotated data for robust and objective quantification of TILs in TNBC. From the study, we have developed a digital dataset of TNBC H&E and IHC (CD4+ and CD8+) stained slides. We hope that an automated based scoring method can provide quantitative and interpretable TILs scoring, which correlates with the manual pathologist-derived sTILs and iTILs scoring and thus has potential prognostic implications.

Keywords: automated quantification, digital pathology, triple negative breast cancer, tumour infiltrating lymphocytes

Procedia PDF Downloads 92

Authors: Navid Ebrahmi Madiseh, Sina Esfandiarpour-Broujeni, Rahil Razeghi

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Introduction: Quantitative analysis of game-related statistical parameters is widely used to evaluate basketball performance at both individual and team levels. Non-free throw shooting plays a crucial role as the primary scoring method, holding significant importance in the game's technical aspect. It has been explored the predictive value of game-related statistics in relation to various contextual and situational variables. Many similarities and differences also have been found between different age groups and levels of competition. For instance, in the World Basketball Championships after the 2010 rule change, 2-point field goals distinguished winners from losers in women's games but not in men's games, and the impact of successful 3-point field goals on women's games was minimal. The study aimed to identify and compare discriminant shooting-related statistics between winning and losing teams in men’s and women’s FIBA-U19-Basketball-World-Cup-2023 tournaments. Method: Data from 112 observations (2 per game) of 16 teams (for each gender) in the FIBA-U19-Basketball-World-Cup-2023 were selected as samples. The data were obtained from the official FIBA website using Python. Specific information was extracted, organized into a DataFrame, and consisted of twelve variables, including shooting percentages, attempts, and scoring ratio for 3-pointers, mid-range shots, paint shots, and free throws. Made% = scoring type successful attempts/scoring type total attempts¬ (1)Free-throw-pts% (free throw score ratio) = (free throw score/total score) ×100 (2)Mid-pts% (mid-range score ratio) = (mid-range score/total score) ×100 (3) Paint-pts% (paint score ratio) = (Paint score/total score) ×100 (4) 3p_pts% (three-point score ratio) = (three-point score/total score) ×100 (5) Independent t-tests were used to examine significant differences in shooting-related statistical parameters between winning and losing teams for both genders. Statistical significance was p < 0.05. All statistical analyses were completed with SPSS, Version 18. Results: The results showed that 3p-made%, mid-pts%, paint-made%, paint-pts%, mid-attempts, and paint-attempts were significantly different between winners and losers in men (t=-3.465, P<0.05; t=3.681, P<0.05; t=-5.884, P<0.05; t=-3.007, P<0.05; t=2.549, p<0.05; t=-3.921, P<0.05). For women, significant differences between winners and losers were found for 3p-made%, 3p-pts%, paint-made%, and paint-attempt (t=-6.429, P<0.05; t=-1.993, P<0.05; t=-1.993, P<0.05; t=-4.115, P<0.05; t=02.451, P<0.05). Discussion: The research aimed to compare shooting-related statistics between winners and losers in men's and women's teams at the FIBA-U19-Basketball-World-Cup-2023. Results indicated that men's winners excelled in 3p-made%, paint-made%, paint-pts%, paint-attempts, and mid-attempt, consistent with previous studies. This study found that losers in men’s teams had higher mid-pts% than winners, which was inconsistent with previous findings. It has been indicated that winners tend to prioritize statistically efficient shots while forcing the opponent to take mid-range shots. In women's games, significant differences in 3p-made%, 3p-pts%, paint-made%, and paint-attempts were observed, indicating that winners relied on riskier outside scoring strategies. Overall, winners exhibited higher accuracy in paint and 3P shooting than losers, but they also relied more on outside offensive strategies. Additionally, winners acquired a higher ratio of their points from 3P shots, which demonstrates their confidence in their skills and willingness to take risks at this competitive level.

Keywords: gender, losers, shoot-statistic, U19, winners

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Authors: Sagar Saroha, Sawan S. Sinha, Sunil Lakshmipathy

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Reynolds averaged Navier-Stokes (RANS) model is the popular computational tool for prediction of turbulent flows. Being computationally less expensive as compared to direct numerical simulation (DNS), RANS has received wide acceptance in industry and research community as well. However, for high Reynolds number flows, the traditional RANS approach based on the Boussinesq hypothesis is incapacitated to capture all the essential flow characteristics, and thus, its performance is restricted in high Reynolds number flows of practical interest. RANS performance turns out to be inadequate in regimes like flow over curved surfaces, flows with rapid changes in the mean strain rate, duct flows involving secondary streamlines and three-dimensional separated flows. In the recent decade, partially averaged Navier-Stokes (PANS) methodology has gained acceptability among seamless bridging methods of turbulence- placed between DNS and RANS. PANS methodology, being a scale resolving bridging method, is inherently more suitable than RANS for simulating turbulent flows. The superior ability of PANS method has been demonstrated for some cases like swirling flows, high-speed mixing environment, and high Reynolds number turbulent flows. In our work, we intend to evaluate PANS in case of separated turbulent flows past bluff bodies -which is of broad aerodynamic research and industrial application. PANS equations, being derived from base RANS, continue to inherit the inadequacies from the parent RANS model based on linear eddy-viscosity model (LEVM) closure. To enhance PANS’ capabilities for simulating separated flows, the shortcomings of the LEVM closure need to be addressed. Inabilities of the LEVMs have inspired the development of non-linear eddy viscosity models (NLEVM). To explore the potential improvement in PANS performance, in our study we evaluate the PANS behavior in conjugation with NLEVM. Our work can be categorized into three significant steps: (i) Extraction of PANS version of NLEVM from RANS model, (ii) testing the model in the homogeneous turbulence environment and (iii) application and evaluation of the model in the canonical case of separated non-homogeneous flow field (flow past prismatic bodies and bodies of revolution at high Reynolds number). PANS version of NLEVM shall be derived and implemented in OpenFOAM -an open source solver. Homogeneous flows evaluation will comprise the study of the influence of the PANS’ filter-width control parameter on the turbulent stresses; the homogeneous analysis performed over typical velocity fields and asymptotic analysis of Reynolds stress tensor. Non-homogeneous flow case will include the study of mean integrated quantities and various instantaneous flow field features including wake structures. Performance of PANS + NLEVM shall be compared against the LEVM based PANS and LEVM based RANS. This assessment will contribute to significant improvement of the predictive ability of the computational fluid dynamics (CFD) tools in massively separated turbulent flows past bluff bodies.

Keywords: bridging methods of turbulence, high Re-CFD, non-linear PANS, separated turbulent flows

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Authors: Melvin Sethobya, Sithule Xanga, Sechaba Lenong, Lunga Nolakana, Gbenga Adesola

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Mining has been the cornerstone of the South African economy for the last century. Most of the gold mining in South Africa was conducted within the Witwatersrand basin, which contributed to the rapid growth of the city of Johannesburg and capitulated the city to becoming the business and wealth capital of the country. But with gradual depletion of resources, a stoppage in the extraction of underground water from mines and other factors relating to survival of the mining operations over a lengthy period, most of the mines were abandoned and left to pollute the local waterways and groundwater with toxins, heavy metal residue and increased acid mine drainage ensued. The Department of Mineral Resources and Energy commissioned a project whose aim is to monitor, maintain, and mitigate the adverse environmental impacts of polluted water mine water flowing into local streams affecting local ecosystems and livelihoods downstream. As part of mitigation efforts, the diagnosis and monitoring of groundwater or surface water polluted sites has become important. Geophysical surveys, in particular, Resistivity and Magnetics surveys, were selected as some of most suitable techniques for investigation of local ingress points along of one the major streams cutting through the Witwatersrand basin, namely the Blesbokspruit, which is found in the eastern part of the basin. The aim of the surveys was to provide information that could be used to assist in determining possible water loss/ ingress from the Blesbokspriut stream. Modelling of geophysical surveys results offered an in-depth insight into the interaction and pathways of polluted water through mapping of possible ingress channels near the Blesbokspruit. The resistivity - depth profile of the surveyed site exhibit a three(3) layered model with low resistivity values (10 to 200 Ω.m) overburden, which is underlain by a moderate resistivity weathered layer (>300 Ω.m), which sits on a more resistive crystalline bedrock (>500 Ω.m). Two locations of potential ingress channels were mapped across the two traverses at the site. The magnetic survey conducted at the site mapped a major NE-SW trending regional linearment with a strong magnetic signature, which was modeled to depth beyond 100m, with the potential to act as a conduit for dispersion of stream water away from the stream, as it shared a similar orientation with the potential ingress channels as mapped using the resistivity method.

Keywords: eletrictrical resistivity, magnetics survey, blesbokspruit, ingress

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Authors: Mohd Khairul Bazli Mohd Aziz, Fadhilah Yusof, Zulkifli Yusop, Zalina Mohd Daud, Mohammad Afif Kasno

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Recent developed rainfall network design techniques have been discussed and compared by many researchers worldwide due to the demand of acquiring higher levels of accuracy from collected data. In many studies, rain-gauge networks are designed to provide good estimation for areal rainfall and for flood modelling and prediction. In a certain study, even using lumped models for flood forecasting, a proper gauge network can significantly improve the results. Therefore existing rainfall network in Johor must be optimized and redesigned in order to meet the required level of accuracy preset by rainfall data users. The well-known geostatistics method (variance-reduction method) that is combined with simulated annealing was used as an algorithm of optimization in this study to obtain the optimal number and locations of the rain gauges. Rain gauge network structure is not only dependent on the station density; station location also plays an important role in determining whether information is acquired accurately. The existing network of 84 rain gauges in Johor is optimized and redesigned by using rainfall, humidity, solar radiation, temperature and wind speed data during monsoon season (November – February) for the period of 1975 – 2008. Three different semivariogram models which are Spherical, Gaussian and Exponential were used and their performances were also compared in this study. Cross validation technique was applied to compute the errors and the result showed that exponential model is the best semivariogram. It was found that the proposed method was satisfied by a network of 64 rain gauges with the minimum estimated variance and 20 of the existing ones were removed and relocated. An existing network may consist of redundant stations that may make little or no contribution to the network performance for providing quality data. Therefore, two different cases were considered in this study. The first case considered the removed stations that were optimally relocated into new locations to investigate their influence in the calculated estimated variance and the second case explored the possibility to relocate all 84 existing stations into new locations to determine the optimal position. The relocations of the stations in both cases have shown that the new optimal locations have managed to reduce the estimated variance and it has proven that locations played an important role in determining the optimal network.

Keywords: geostatistics, simulated annealing, semivariogram, optimization

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Authors: Antti Lanki, Justiina Halonen, Juuso Punnonen, Emmi Rantavuo

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Marine oil spill response operation requires extensive vessel maneuvering and navigation skills. At-sea oil containment and recovery include both single vessel and multi-vessel operations. Towing long oil containment booms that are several hundreds of meters in length, is a challenge in itself. Boom deployment and towing in multi-vessel configurations is an added challenge that requires precise coordination and control of the vessels. Efficient communication, as a prerequisite for shared situational awareness, is needed in order to execute the response task effectively. To gain and maintain adequate maritime skills, practical training is needed. Field exercises are the most effective way of learning, but especially the related vessel operations are resource-intensive and costly. Field exercises may also be affected by environmental limitations such as high sea-state or other adverse weather conditions. In Finland, the seasonal ice-coverage also limits the training period to summer seasons only. In addition, environmental sensitiveness of the sea area restricts the use of real oil or other target substances. This paper examines, whether maritime simulator training can offer a complementary method to overcome the training challenges related to field exercises. The objective is to assess the efficiency and the learning impact of simulator training, and the specific skills that can be trained most effectively in simulators. This paper provides an overview of learning results from two oil spill response pilot courses, in which maritime navigational bridge simulators were used to train the oil spill response authorities. The simulators were equipped with an oil spill functionality module. The courses were targeted at coastal Fire and Rescue Services responsible for near shore oil spill response in Finland. The competence levels of the participants were surveyed before and after the course in order to measure potential shifts in competencies due to the simulator training. In addition to the quantitative analysis, the efficiency of the simulator training is evaluated qualitatively through feedback from the participants. The results indicate that simulator training is a valid and effective method for developing marine oil spill response competencies that complement traditional field exercises. Simulator training provides a safe environment for assessing various oil containment and recovery tactics. One of the main benefits of the simulator training was found to be the immediate feedback the spill modelling software provides on the oil spill behaviour as a reaction to response measures.

Keywords: maritime training, oil spill response, simulation, vessel manoeuvring

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Authors: Ogemdi Chinwendu Anika, Anna Strzelecka, Yadira Bajón-Fernández, Raffaella Villa

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Anaerobic digestion (AD) has been used since time in memorial to take care of organic wastes in the environment, especially for sewage and wastewater treatments. Recently, the rising demand/need to increase renewable energy from organic matter has caused the AD substrates spectrum to expand and include a wider variety of organic materials such as agricultural residues and farm manure which is annually generated at around 140 billion metric tons globally. The problem, however, is that agricultural wastes are composed of materials that are heterogeneous and too difficult to degrade -particularly lignin, that make up about 0–40% of the total lignocellulose content. This study aimed to evaluate the impact of varying concentrations of lignin on biogas yields and their subsequent response to a commercial yeast-based bioadditive in batch anaerobic digesters. The experiments were carried out in batches for a retention time of 56 days with different lignin concentrations (200 mg, 300 mg, 400 mg, 500 mg, and 600 mg) treated to different conditions to first determine the concentration of the bioadditive that was most optimal for overall process improvement and yields increase. The batch experiments were set up using 130 mL bottles with a working volume of 60mL, maintained at 38°C in an incubator shaker (150rpm). Digestate obtained from a local plant operating at mesophilic conditions was used as the starting inoculum, and commercial kraft lignin was used as feedstock. Biogas measurements were carried out using the displacement method and were corrected to standard temperature and pressure using standard gas equations. Furthermore, the modified Gompertz equation model was used to non-linearly regress the resulting data to estimate gas production potential, production rates, and the duration of lag phases as indicatives of degrees of lignin inhibition. The results showed that lignin had a strong inhibitory effect on the AD process, and the higher the lignin concentration, the more the inhibition. Also, the modelling showed that the rates of gas production were influenced by the concentrations of the lignin substrate added to the system – the higher the lignin concentrations in mg (0, 200, 300, 400, 500, and 600) the lower the respective rate of gas production in ml/gVS.day (3.3, 2.2, 2.3, 1.6, 1.3, and 1.1), although the 300 mg increased by 0.1 ml/gVS.day over that of the 200 mg. The impact of the yeast-based bioaddition on the rate of production was most significant in the 400 mg and 500 mg as the rate was improved by 0.1 ml/gVS.day and 0.2 ml/gVS.day respectively. This indicates that agricultural residues with higher lignin content may be more responsive to inhibition alleviation by yeast-based bioadditive; therefore, further study on its application to the AD of agricultural residues of high lignin content will be the next step in this research.

Keywords: anaerobic digestion, renewable energy, lignin valorisation, biogas

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Authors: Alon Cohen, Jeffrey Kantor, Shalom Levy

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The use of the audit risk model in auditing has faced limitations and difficulties, leading auditors to rely on a conceptual level of its application. The qualitative approach to assessing risks has resulted in different risk assessments, affecting the quality of audits and decision-making on the adoption of CAATTs. This study aims to investigate risk factors impacting the implementation of the audit risk model and propose a complementary risk-based instrument (KRIs) to form substance risk judgments and mitigate against heightened risk of material misstatement (RMM). The study addresses the question of how risk factors impact the implementation of the audit risk model, improve risk judgments, and aid in the adoption of CAATTs. The study uses a three-stage scale development procedure involving a pretest and subsequent study with two independent samples. The pretest involves an exploratory factor analysis, while the subsequent study employs confirmatory factor analysis for construct validation. Additionally, the authors test the ability of the KRIs to predict audit efforts needed to mitigate against heightened RMM. Data was collected through two independent samples involving 767 participants. The collected data was analyzed using exploratory factor analysis and confirmatory factor analysis to assess scale validity and construct validation. The suggested KRIs, comprising two risk components and seventeen risk items, are found to have high predictive power in determining audit efforts needed to reduce RMM. The study validates the suggested KRIs as an effective instrument for risk assessment and decision-making on the adoption of CAATTs. This study contributes to the existing literature by implementing a holistic approach to risk assessment and providing a quantitative expression of assessed risks. It bridges the gap between intuitive risk evaluation and the theoretical domain, clarifying the mechanism of risk assessments. It also helps improve the uniformity and quality of risk assessments, aiding audit standard-setters in issuing updated guidelines on CAATT adoption. A few limitations and recommendations for future research should be mentioned. First, the process of developing the scale was conducted in the Israeli auditing market, which follows the International Standards on Auditing (ISAs). Although ISAs are adopted in European countries, for greater generalization, future studies could focus on other countries that adopt additional or local auditing standards. Second, this study revealed risk factors that have a material impact on the assessed risk. However, there could be additional risk factors that influence the assessment of the RMM. Therefore, future research could investigate other risk segments, such as operational and financial risks, to bring a broader generalizability to our results. Third, although the sample size in this study fits acceptable scale development procedures and enables drawing conclusions from the body of research, future research may develop standardized measures based on larger samples to reduce the generation of equivocal results and suggest an extended risk model.

Keywords: audit risk model, audit efforts, CAATTs adoption, key risk indicators, sustainability

Procedia PDF Downloads 53

Authors: Priscilla Echeverria

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This paper addresses initial teacher formation as a formative space in which pedagogy students develop a pedagogical agency capacity to contribute to social justice, considering ethical, political, and epistemic dimensions. This paper is structured by discussing first the concepts of agency, pedagogical interaction, and social justice from a critical perspective; and continues offering preliminary results on the capacity of pedagogical agency in novice teachers after the analysis of critical incidents as a research methodology. This study is motivated by the concern that responding to the current neoliberal scenario, many initial teacher formation (ITF) programs have reduced the meaning of education to instruction, and pedagogy to methodology, favouring the formation of a technical professional over a reflective or critical one. From this concern, this study proposes that the restitution of the subject is an urgent task in teacher formation, so it is essential to enable him in his capacity for action and advance in eliminating institutionalized oppression insofar as it affects that capacity. Given that oppression takes place in human interaction, through this work, I propose that initial teacher formation develops sensitivity and educates the gaze to identify oppression and take action against it, both in pedagogical interactions -which configure political, ethical, and epistemic subjectivities- as in the hidden and official curriculum. All this from the premise that modelling democratic and dialogical interactions are basic for any program that seeks to contribute to a more just and empowered society. The contribution of this study lies in the fact that it opens a discussion in an area about which we know little: the impact of the type of interactions offered by university teaching at ITF on the capacity of future teachers to be pedagogical agents. For this reason, this study seeks to gather evidence of the result of this formation, analysing the capacity of pedagogical agency of novice teachers, or, in other words, how capable the graduates of secondary pedagogies are in their first pedagogical experiences to act and make decisions putting the formative purposes that they are capable of autonomously defining before technical or bureaucratic issues imposed by the curriculum or the official culture. This discussion is part of my doctoral research, "The importance of developing the capacity for ethical-political-epistemic agency in novice teachers during initial teacher formation to contribute to social justice", which I am currently developing in the Educational Research program of the University of Lancaster, United Kingdom, as a Conicyt fellow for the 2019 cohort.

Keywords: initial teacher formation, pedagogical agency, pedagogical interaction, social justice, hidden curriculum

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Authors: Soheila Sadeghi

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Accurate cost prediction is essential for effective project management and decision-making in the construction industry. This study aims to develop a cost prediction model for construction projects using Machine Learning techniques and Particle Swarm Optimization (PSO). The research utilizes a comprehensive dataset containing project cost estimates, actual costs, resource details, and project performance metrics from a road reconstruction project. The methodology involves data preprocessing, feature selection, and the development of an Artificial Neural Network (ANN) model optimized using PSO. The study investigates the impact of various input features, including cost estimates, resource allocation, and project progress, on the accuracy of cost predictions. The performance of the optimized ANN model is evaluated using metrics such as Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), and R-squared. The results demonstrate the effectiveness of the proposed approach in predicting project costs, outperforming traditional benchmark models. The feature selection process identifies the most influential variables contributing to cost variations, providing valuable insights for project managers. However, this study has several limitations. Firstly, the model's performance may be influenced by the quality and quantity of the dataset used. A larger and more diverse dataset covering different types of construction projects would enhance the model's generalizability. Secondly, the study focuses on a specific optimization technique (PSO) and a single Machine Learning algorithm (ANN). Exploring other optimization methods and comparing the performance of various ML algorithms could provide a more comprehensive understanding of the cost prediction problem. Future research should focus on several key areas. Firstly, expanding the dataset to include a wider range of construction projects, such as residential buildings, commercial complexes, and infrastructure projects, would improve the model's applicability. Secondly, investigating the integration of additional data sources, such as economic indicators, weather data, and supplier information, could enhance the predictive power of the model. Thirdly, exploring the potential of ensemble learning techniques, which combine multiple ML algorithms, may further improve cost prediction accuracy. Additionally, developing user-friendly interfaces and tools to facilitate the adoption of the proposed cost prediction model in real-world construction projects would be a valuable contribution to the industry. The findings of this study have significant implications for construction project management, enabling proactive cost estimation, resource allocation, budget planning, and risk assessment, ultimately leading to improved project performance and cost control. This research contributes to the advancement of cost prediction techniques in the construction industry and highlights the potential of Machine Learning and PSO in addressing this critical challenge. However, further research is needed to address the limitations and explore the identified future research directions to fully realize the potential of ML-based cost prediction models in the construction domain.

Keywords: cost prediction, construction projects, machine learning, artificial neural networks, particle swarm optimization, project management, feature selection, road reconstruction

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Authors: Alex J. Summers, Jasmine P. Devadhasan, Douglas Montgomery, Brittany Fischer, Jian Gu, Frederic Zenhausern

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Immunoassays have been utilized for several applications, including the detection of pathogens. Our laboratory is in the development of a tier 1 biothreat panel utilizing Vertical Flow Assay (VFA) technology for simultaneous detection of pathogens and toxins. One method of manufacturing VFA membranes is with non-contact piezoelectric dispensing, which provides advantages, such as low-volume and rapid dispensing without compromising the structural integrity of antibody or substrate. Challenges of this processinclude premature discontinuation of dispensing and misaligned spotting. Preliminary data revealed the Yp 11C7 mAb (11C7)reagent to exhibit a large angle of failure during printing which may have contributed to variable printing outputs. A Design of Experiment (DOE) was executed using this reagent to investigate the effects of hydrostatic pressure and reagent concentration on microarray printing outputs. A Nano-plotter 2.1 (GeSIM, Germany) was used for printing antibody reagents ontonitrocellulose membrane sheets in a clean room environment. A spotting plan was executed using Spot-Front-End software to dispense volumes of 11C7 reagent (20-50 droplets; 1.5-5 mg/mL) in a 6-test spot array at 50 target membrane locations. Hydrostatic pressure was controlled by raising the Pressure Compensation Vessel (PCV) above or lowering it below our current working level. It was hypothesized that raising or lowering the PCV 6 inches would be sufficient to cause either liquid accumulation at the tip or discontinue droplet formation. After aspirating 11C7 reagent, we tested this hypothesis under stroboscope.75% of the effective raised PCV height and of our hypothesized lowered PCV height were used. Humidity (55%) was maintained using an Airwin BO-CT1 humidifier. The number and quality of membranes was assessed after staining printed membranes with dye. The droplet angle of failure was recorded before and after printing to determine a “stroboscope score” for each run. The DOE set was analyzed using JMP software. Hydrostatic pressure and reagent concentration had a significant effect on the number of membranes output. As hydrostatic pressure was increased by raising the PCV 3.75 inches or decreased by lowering the PCV -4.5 inches, membrane output decreased. However, with the hydrostatic pressure closest to equilibrium, our current working level, membrane output, reached the 50-membrane target. As the reagent concentration increased from 1.5 to 5 mg/mL, the membrane output also increased. Reagent concentration likely effected the number of membrane output due to the associated dispensing volume needed to saturate the membranes. However, only hydrostatic pressure had a significant effect on stroboscope score, which could be due to discontinuation of dispensing, and thus the stroboscope check could not find a droplet to record. Our JMP predictive model had a high degree of agreement with our observed results. The JMP model predicted that dispensing the highest concentration of 11C7 at our current PCV working level would yield the highest number of quality membranes, which correlated with our results. Acknowledgements: This work was supported by the Chemical Biological Technologies Directorate (Contract # HDTRA1-16-C-0026) and the Advanced Technology International (Contract # MCDC-18-04-09-002) from the Department of Defense Chemical and Biological Defense program through the Defense Threat Reduction Agency (DTRA).

Keywords: immunoassay, microarray, design of experiment, piezoelectric dispensing

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Authors: Katherine Maurer

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Background and purpose: Violence that occurs within families is a global social problem. Children who are victims or witness to family violence are at risk for many negative effects both proximally and distally. One of the most disconcerting long-term effects occurs when child victims become adult perpetrators: the intergenerational transmission of family violence (ITFV). Early identification of those children most at risk for ITFV is needed to inform interventions to prevent future family violence perpetration and victimization. Only about 25-30% of child family violence victims become perpetrators of adult family violence (either child abuse, partner abuse, or both). Prior research has primarily been conducted using dichotomous measures of exposure (yes; no) to predict ITFV, given the low incidence rate in community samples. It is often assumed that exposure to greater amounts of violence predicts greater risk of ITFV. However, no previous longitudinal study with a community sample has tested a dose-response model of exposure to physical child abuse and parental physical intimate partner violence (IPV) using count data of frequency and severity of violence to predict adult ITFV. The current study used advanced statistical methods to test if increased childhood exposure would predict greater risk of ITFV. Methods: The study utilized 3 panels of prospective data from a cohort of 15 year olds (N=338) from the Project on Human Development in Chicago Neighborhoods longitudinal study. The data were comprised of a stratified probability sample of seven ethnic/racial categories and three socio-economic status levels. Structural equation modeling was employed to test a hurdle regression model of dose-response to predict ITFV. A version of the Conflict Tactics Scale was used to measure physical violence victimization, witnessing parental IPV and young adult IPV perpetration and victimization. Results: Consistent with previous findings, past 12 months incidence rates severity and frequency of interpersonal violence were highly skewed. While rates of parental and young adult IPV were about 40%, an unusually high rate of physical child abuse (57%) was reported. The vast majority of a number of acts of violence, whether minor or severe, were in the 1-3 range in the past 12 months. Reported frequencies of more than 5 times in the past year were rare, with less than 10% of those reporting more than six acts of minor or severe physical violence. As expected, minor acts of violence were much more common than acts of severe violence. Overall, regression analyses were not significant for the dose-response model of ITFV. Conclusions and implications: The results of the dose-response model were not significant due to a lack of power in the final sample (N=338). Nonetheless, the value of the approach was confirmed for the future research given the bi-modal nature of the distributions which suggest that in the context of both child physical abuse and physical IPV, there are at least two classes when frequency of acts is considered. Taking frequency into account in predictive models may help to better understand the relationship of exposure to ITFV outcomes. Further testing using hurdle regression models is suggested.

Keywords: intergenerational transmission of family violence, physical child abuse, intimate partner violence, structural equation modeling

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Authors: Tetyana Kendzerska, David T. Zhu, Michael Pugliese, Douglas Manuel, Mohsen Sadatsafavi, Marcus Povitz, Therese A. Stukel, Teresa To, Shawn D. Aaron, Sunita Mulpuru, Melanie Chin, Claire E. Kendall, Kednapa Thavorn, Rebecca Robillard, Andrea S. Gershon

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The impact of the COVID-19 pandemic on the management of ambulatory care sensitive conditions (ACSCs) remains unknown. To compare observed and expected (projected based on previous years) trends in all-cause mortality and healthcare use for ACSCs in the first year of the pandemic (March 2020 - March 2021). A population-based study using provincial health administrative data.General adult population (Ontario, Canada). Monthly all-cause mortality, and hospitalizations, emergency department (ED) and outpatient visit rates (per 100,000 people at-risk) for seven combined ACSCs (asthma, COPD, angina, congestive heart failure, hypertension, diabetes, and epilepsy) during the first year were compared with similar periods in previous years (2016-2019) by fitting monthly time series auto-regressive integrated moving-average models. Compared to previous years, all-cause mortality rates increased at the beginning of the pandemic (observed rate in March-May 2020 of 79.98 vs. projected of 71.24 [66.35-76.50]) and then returned to expected in June 2020—except among immigrants and people with mental health conditions where they remained elevated. Hospitalization and ED visit rates for ACSCs remained lower than projected throughout the first year: observed hospitalization rate of 37.29 vs. projected of 52.07 (47.84-56.68); observed ED visit rate of 92.55 vs. projected of 134.72 (124.89-145.33). ACSC outpatient visit rates decreased initially (observed rate of 4,299.57 vs. projected of 5,060.23 [4,712.64-5,433.46]) and then returned to expected in June 2020. Reductions in outpatient visits for ACSCs at the beginning of the pandemic combined with reduced hospital admissions may have been associated with temporally increased mortality—disproportionately experienced by immigrants and those with mental health conditions. The Ottawa Hospital Academic Medical Organization

Keywords: COVID-19, chronic disease, all-cause mortality, hospitalizations, emergency department visits, outpatient visits, modelling, population-based study, asthma, COPD, angina, heart failure, hypertension, diabetes, epilepsy

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Authors: Yagmur Soylu, Emir Ozeren, Erol Esen, Digdem M. Siyez, Ozlem Belkis, Ezgi Burc, Gülce Demirgurz

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The aim of the study is to determine the predictive power of personal growth initiative, socio-demographic variables (such as sex, grade, and working condition) on career adaptability and optimism of bachelor students in Dokuz Eylul University in Turkey. According to career construction theory, career adaptability is viewed as a psychosocial construct, which refers to an individual’s resources for dealing with current and expected tasks, transitions and traumas in their occupational roles. Career optimism is defined as positive results for future career development of individuals in the expectation that it will achieve or to put the emphasis on the positive aspects of the event and feel comfortable about the career planning process. Personal Growth Initiative (PGI) is defined as being proactive about one’s personal development. Additionally, personal growth is defined as the active and intentional engagement in the process of personal. A study conducted on college students revealed that individuals with high self-development orientation make more effort to discover the requirements of the profession and workspaces than individuals with low levels of personal development orientation. University life is a period that social relations and the importance of academic activities are increased, the students make efforts to progress through their career paths and it is also an environment that offers opportunities to students for their self-realization. For these reasons, personal growth initiative is potentially an important variable which has a key role for an individual during the transition phase from university to the working life. Based on the review of the literature, it is expected that individual’s personal growth initiative, sex, grade, and working condition would significantly predict one’s career adaptability. In the relevant literature, it can be seen that there are relatively few studies available on the career adaptability and optimism of university students. Most of the existing studies have been carried out with limited respondents. In this study, the authors aim to conduct a comprehensive research with a large representative sample of bachelor students in Dokuz Eylul University, Izmir, Turkey. By now, personal growth initiative and career development constructs have been predominantly discussed in western contexts where individualistic tendencies are likely to be seen. Thus, the examination of the same relationship within the context of Turkey where collectivistic cultural characteristics can be more observed is expected to offer valuable insights and provide an important contribution to the literature. The participants in this study were comprised of 1500 undergraduate students being included from thirteen faculties in Dokuz Eylul University. Stratified and random sampling methods were adopted for the selection of the participants. The Personal Growth Initiative Scale-II and Career Futures Inventory were used as the major measurement tools. In data analysis stage, several statistical analysis concerning the regression analysis, one-way ANOVA and t-test will be conducted to reveal the relationships of the constructs under investigation. At the end of this project, we will be able to determine the level of career adaptability and optimism of university students at varying degrees so that a fertile ground is likely to be created to carry out several intervention techniques to make a contribution to an emergence of a healthier and more productive youth generation in psycho-social sense.

Keywords: career optimism, career adaptability, personal growth initiative, university students

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Authors: Malla Vijayeta, Y. Vijaya Kumar, N. Ramakrishna Raju, K. Satyanarayana

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Global AEC (architecture, engineering, and construction) industry has been coined as one of the most resistive domains in embracing technology. Although this digital era has been inundated with software tools like CAD, STADD, CANDY, Microsoft Project, Primavera etc. the key stakeholders have been working in siloes and processes remain fragmented. Unlike the yesteryears’ simpler project delivery methods, the current projects are of fast-track, complex, risky, multidisciplinary, stakeholder’s influential, statutorily regulative etc. pose extensive bottlenecks in preventing timely completion of projects. At this juncture, a paradigm shift surfaced in construction industry, and Building Information Modeling, aka BIM, has been a panacea to bolster the multidisciplinary teams’ cooperative and collaborative work leading to productive, sustainable and leaner project outcome. Building information modeling has been integrative, stakeholder engaging and centralized approach in providing a common platform of communication. A common misconception that BIM can be used for building/high rise projects in Indian Construction Industry, while this paper discusses of the implementation of BIM processes/methodologies in water and waste water industry. It elucidates about BIM 4D planning and constructability reviews of a Sewage Treatment Plant in India. Conventional construction planning and logistics management involves a blend of experience coupled with imagination. Even though the excerpts or judgments or lessons learnt gained from veterans might be predictive and helpful, but the uncertainty factor persists. This paper shall delve about the case study of real time implementation of BIM 4D planning protocols for one of the Sewage Treatment Plant of Dravyavati River Rejuvenation Project in India and develops a Time Liner to identify logistics planning and clash detection. With this BIM processes, we shall find that there will be significant reduction of duplication of tasks and reworks. Also another benefit achieved will be better visualization and workarounds during conception stage and enables for early involvement of the stakeholders in the Project Life cycle of Sewage Treatment Plant construction. Moreover, we have also taken an opinion poll of the benefits accrued utilizing BIM processes versus traditional paper based communication like 2D and 3D CAD tools. Thus this paper concludes with BIM framework for Sewage Treatment Plant construction which will achieve optimal construction co-ordination advantages like 4D construction sequencing, interference checking, clash detection checking and resolutions by primary engagement of all key stakeholders thereby identifying potential risks and subsequent creation of risk response strategies. However, certain hiccups like hesitancy in adoption of BIM technology by naïve users and availability of proficient BIM trainers in India poses a phenomenal impediment. Hence the nurture of BIM processes from conception, construction and till commissioning, operation and maintenance along with deconstruction of a project’s life cycle is highly essential for Indian Construction Industry in this digital era.

Keywords: integrated BIM workflow, 4D planning with BIM, building information modeling, clash detection and visualization, constructability reviews, project life cycle

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Authors: Ciara Pienaar, J. W. Odendaal, J. Joubert, J. C. Smit

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Radar cross section (RCS) of dielectric objects play an important role in many applications, such as low observability technology development, drone detection, and monitoring as well as coastal surveillance. Various materials are used to construct the targets of interest such as metal, wood, composite materials, radar absorbent materials, and other dielectrics. Since simulated datasets are increasingly being used to supplement infield measurements, as it is more cost effective and a larger variety of targets can be simulated, it is important to have a high level of confidence in the predicted results. Confidence can be attained through validation. Various computational electromagnetic (CEM) methods are capable of predicting the RCS of dielectric targets. This study will extend previous studies by validating full-wave and asymptotic RCS simulations of dielectric targets with measured data. The paper will provide measured RCS data of a number of canonical dielectric targets exhibiting different material properties. As stated previously, these measurements are used to validate numerous CEM methods. The dielectric properties are accurately characterized to reduce the uncertainties in the simulations. Finally, an analysis of the sensitivity of oblique and normal incidence scattering predictions to material characteristics is also presented. In this paper, the ability of several CEM methods, including method of moments (MoM), and physical optics (PO), to calculate the RCS of dielectrics were validated with measured data. A few dielectrics, exhibiting different material properties, were selected and several canonical targets, such as flat plates and cylinders, were manufactured. The RCS of these dielectric targets were measured in a compact range at the University of Pretoria, South Africa, over a frequency range of 2 to 18 GHz and a 360° azimuth angle sweep. This study also investigated the effect of slight variations in the material properties on the calculated RCS results, by varying the material properties within a realistic tolerance range and comparing the calculated RCS results. Interesting measured and simulated results have been obtained. Large discrepancies were observed between the different methods as well as the measured data. It was also observed that the accuracy of the RCS data of the dielectrics can be frequency and angle dependent. The simulated RCS for some of these materials also exhibit high sensitivity to variations in the material properties. Comparison graphs between the measured and simulation RCS datasets will be presented and the validation thereof will be discussed. Finally, the effect that small tolerances in the material properties have on the calculated RCS results will be shown. Thus the importance of accurate dielectric material properties for validation purposes will be discussed.

Keywords: asymptotic, CEM, dielectric scattering, full-wave, measurements, radar cross section, validation

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Authors: M. Bonello, D. Micallef, S. P. Borg

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Driven by increased comfort standards, but at the same time high energy consciousness, energy-efficient space cooling has become an essential aspect of building design. Its aims are simple, aiming at providing satisfactory thermal comfort for individuals in an interior space using low energy consumption cooling systems. In this context, evaporative cooling is both an energy-efficient and an eco-friendly cooling process. In the past two decades, several academic studies have been performed to determine the resulting thermal comfort produced by an evaporative cooling system, including studies on temperature profiles, air speed profiles, effect of clothing and personnel activity. To the best knowledge of the authors, no studies have yet considered the analysis of relative humidity (RH) profiles in a space cooled using evaporative cooling. Such a study will determine the effect of different humidity levels on a person's thermal comfort and aid in the consequent improvement designs of such future systems. Under this premise, the research objective is to characterise the resulting different RH profiles in a chamber micro-climate using the evaporative cooling system in which the inlet air speed, temperature and humidity content are varied. The chamber shall be modelled using Computational Fluid Dynamics (CFD) in ANSYS Fluent. Relative humidity shall be modelled using a species transport model while the k-ε RNG formulation is the proposed turbulence model that is to be used. The model shall be validated with measurements taken using an identical test chamber in which tests are to be conducted under the different inlet conditions mentioned above, followed by the verification of the model's mesh and time step. The verified and validated model will then be used to simulate other inlet conditions which would be impractical to conduct in the actual chamber. More details of the modelling and experimental approach will be provided in the full paper The main conclusions from this work are two-fold: the micro-climatic relative humidity spatial distribution within the room is important to consider in the context of investigating comfort at occupant level; and the investigation of a human being's thermal comfort (based on Predicted Mean Vote – Predicted Percentage Dissatisfied [PMV-PPD] values) and its variation with different locations of relative humidity values. The study provides the necessary groundwork for investigating the micro-climatic RH conditions of environments cooled using evaporative cooling. Future work may also target the analysis of ways in which evaporative cooling systems may be improved to better the thermal comfort of human beings, specifically relating to the humidity content around a sedentary person.

Keywords: chamber micro-climate, evaporative cooling, relative humidity, thermal comfort

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Authors: Matthew E. Potter, Daniel J. Stewart, Lindsay M. Armstrong, Pier J. A. Sazio, Robert R. Raja

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Rising CO₂ levels in the atmosphere means that CO₂ is a highly desirable feedstock. This requires specific catalysts to be designed to activate this inert molecule, combining a catalytic site tailored for CO₂ transformations with a support that can readily adsorb CO₂. Metal organic frameworks (MOFs) are regularly used as CO₂ sorbents. The organic nature of the linker molecules, connecting the metal nodes, offers many post-synthesis modifications to introduce catalytic active sites into the frameworks. However, the metal nodes may be coordinatively unsaturated, allowing them to bind to organic moieties. Imidazoles have shown promise catalyzing the formation of cyclic carbonates from epoxides with CO₂. Typically, this synthesis route employs toxic reagents such as phosgene, liberating HCl. Therefore an alternative route with CO₂ is highly appealing. In this work we design active sites for CO₂ activation, by tethering substituted-imidazole organocatalytic species to the available Cr3+ metal nodes of a Cr-MIL-101 MOF, for the first time, to create a tailored species for carbon capture utilization applications. Our tailored design strategy combining a CO₂ sorbent, Cr-MIL-101, with an anchored imidazole results in a highly active and selective multifunctional catalyst, achieving turnover frequencies of over 750 hr-1. These findings demonstrate the synergy between the MOF framework and imidazoles for CO₂ utilization applications. Further, the effect of substrate variation has been explored yielding mechanistic insights into this process. Through characterization, we show that the structural and compositional integrity of the Cr-MIL-101 has been preserved on functionalizing the imidazoles. Further, we show the binding of the imidazoles to the Cr3+ metal nodes. This can be seen through our EPR study, where the distortion of the Cr3+ on binding to the imidazole shows the CO₂ binding site is close to the active imidazole. This has a synergistic effect, improving catalytic performance. We believe the combination of MOF support and organocatalyst allows many possibilities to generate new multifunctional catalysts for CO₂ utilisation. In conclusion, we have validated our design procedure, combining a known CO₂ sorbent, with an active imidazole species to create a unique tailored multifunctional catalyst for CO₂ utilization. This species achieves high activity and selectivity for the formation of cyclic carbonates and offers a sustainable alternative to traditional synthesis methods. This work represents a unique design strategy for CO₂ utilization while offering exciting possibilities for further work in characterization, computational modelling, and post-synthesis modification.

Keywords: carbonate, catalysis, MOF, utilisation

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Authors: Michael Mihalicz, Aziz Guergachi

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Background: The science of modelling choice preferences has evolved over centuries into an interdisciplinary field contributing to several branches of Microeconomics and Mathematical Psychology. Early theories in Decision Science rested on the logic of rationality, but as it and related fields matured, descriptive theories emerged capable of explaining systematic violations of rationality through cognitive mechanisms underlying the thought processes that guide human behaviour. Cognitive limitations are not, however, solely responsible for systematic deviations from rationality and many are now exploring the effect of visceral factors as the more dominant drivers. The current study builds on the existing literature by exploring sleep deprivation, thermal comfort, stress, hunger, fear, anger and sadness as moderators to three distinct elements that define individual risk preference under Cumulative Prospect Theory. Methodology: This study is designed to compare the risk preference of participants experiencing an elevated affective or visceral state to those in a neutral state using nonparametric elicitation methods across three domains. Two experiments will be conducted simultaneously using different methodologies. The first will determine visceral states and risk preferences randomly over a two-week period by prompting participants to complete an online survey remotely. In each round of questions, participants will be asked to self-assess their current state using Visual Analogue Scales before answering a series of lottery-style elicitation questions. The second experiment will be conducted in a laboratory setting using psychological primes to induce a desired state. In this experiment, emotional states will be recorded using emotion analytics and used a basis for comparison between the two methods. Significance: The expected results include a series of measurable and systematic effects on the subjective interpretations of gamble attributes and evidence supporting the proposition that a portion of the variability in human choice preferences unaccounted for by cognitive limitations can be explained by interacting visceral states. Significant results will promote awareness about the subconscious effect that emotions and other drive states have on the way people process and interpret information, and can guide more effective decision making by informing decision-makers of the sources and consequences of irrational behaviour.

Keywords: decision making, emotions, prospect theory, visceral factors

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Authors: M. H. Arslan, U. K. Sahin, H. Acikgoz-Tufan, I. Gocek, I. Erdem

Abstract:

Various exterior factors have perpetual effects on textile materials during wear, use and laundering in everyday life. In accordance with their frequency of use, textile materials are required to be laundered at certain intervals. The medium in which the laundering process takes place have inevitable detrimental physical and chemical effects on textile materials caused by the unique parameters of the process inherently existing. Connatural structures of various textile materials result in many different physical, chemical and mechanical characteristics. Because of their specific structures, these materials have different behaviors against several exterior factors. By modeling the behavior of commercial and test textiles as group-wise against laundering process, it is possible to disclose the relation in between these two groups of materials, which will lead to better understanding of their behaviors in terms of similarities and differences against the washing parameters of the laundering. Thus, the goal of the current research is to examine the behavior of two groups of textile materials as commercial textiles and as test textiles towards the main washing machine parameters during laundering process such as temperature, load quantity, mechanical action and level of water amount by concentrating on shrinkage, pilling, sewing defects, collar abrasion, the other defects other than sewing, whitening and overall properties of textiles. In this study, cotton fabrics were preferred as commercial textiles due to the fact that garments made of cotton are the most demanded products in the market by the textile consumers in daily life. Full factorial experimental set-up was used to design the experimental procedure. All profiles always including all of the commercial and the test textiles were laundered for 20 cycles by commercial home laundering machine to investigate the effects of the chosen parameters. For the laundering process, a modified version of ‘‘IEC 60456 Test Method’’ was utilized. The amount of detergent was altered as 0.5% gram per liter depending on varying load quantity levels. Datacolor 650®, EMPA Photographic Standards for Pilling Test and visual examination were utilized to test and characterize the textiles. Furthermore, in the current study the relation in between commercial and test textiles in terms of their performance was deeply investigated by the help of statistical analysis performed by MINITAB® package program modeling their behavior against the parameters of the laundering process. In the experimental work, the behaviors of both groups of textiles towards washing machine parameters were visually and quantitatively assessed in dry state.

Keywords: behavior against washing machine parameters, performance evaluation of textiles, statistical analysis, commercial and test textiles

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Authors: Shaine Mehta, Neelam Parmar, Patrick White, Mark Ashworth

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Patients with a history of substance have a high prevalence of comorbidities, including asthma and chronic obstructive pulmonary disease (COPD). Mortality rates are higher than that of the general population and the link to respiratory disease is reported. Randomised controlled trials (RCTs) support opioid substitution therapy as an effective means for harm reduction. However, whilst a high proportion of patients receiving opioid substitution therapy are smokers, to the author’s best knowledge there have been no studies of respiratory disease and smoking intensity in these patients. A cross sectional prevalence study was conducted using an anonymised patient-level database in primary care, Lambeth DataNet (LDN). We included patients aged 18 years and over who had records of ever having been prescribed methadone in primary care. Patients under 18 years old or prescribed buprenorphine (because of uncertainty about the prescribing indication) were excluded. Demographic, smoking, alcohol and asthma and COPD coding data were extracted. Differences between methadone and non-methadone users were explored with multivariable analysis. LDN contained data on 321, 395 patients ≥ 18 years; 676 (0.16%) had a record of methadone prescription. Patients prescribed methadone were more likely to be male (70.7% vs. 50.4%), older (48.9yrs vs. 41.5yrs) and less likely to be from an ethnic minority group (South Asian 2.1% vs. 7.8%; Black African 8.9% vs. 21.4%). Almost all those prescribed methadone were smokers or ex-smokers (97.3% vs. 40.9%); more were non-alcohol drinkers (41.3% vs. 24.3%). We found a high prevalence of COPD (12.4% vs 1.4%) and asthma (14.2% vs 4.4%). Smoking intensity data shows a high prevalence of ≥ 20 cigarettes per day (21.5% vs. 13.1%). Risk of COPD, adjusted for age, gender, ethnicity and deprivation, was raised in smokers: odds ratio 14.81 (95%CI 11.26, 19.47), and in the methadone group: OR 7.51 (95%CI: 5.78, 9.77). Furthermore, after adjustment for smoking intensity (number of cigarettes/day), the risk was raised in methadone group: OR 4.77 (95%CI: 3.13, 7.28). High burden of respiratory disease compounded by the high rates of smoking is a public health concern. This supports an integrated approach to health in patients treated for opiate dependence, with access to smoking cessation support. Further work may evaluate the current structure and commissioning of substance misuse services, including smoking cessation. Regression modelling highlights that methadone as a ‘risk factor’ was independently associated with COPD prevalence, even after adjustment for smoking intensity. This merits further exploration, as the association may be related to unexplored aspects of smoking (such as the number of years smoked) or may be related to other related exposures, such as smoking heroin or crack cocaine.

Keywords: methadone, respiratory disease, smoking cessation, substance misuse

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Authors: Esmael Makarian, Ayub Elyasi, Fatemeh Saberi, Olusegun Stanley Tomomewo

Abstract:

Rock mechanical investigation is one of the most crucial activities in underground operations, especially in surveys related to hydrocarbon exploration and production, geothermal reservoirs, energy storage, mining, and geotechnics. There is a wide range of traditional methods for driving, collecting, and analyzing rock mechanics data. However, these approaches may not be suitable or work perfectly in some situations, such as fractured zones. Cutting-edge technologies have been provided to solve and optimize the mentioned issues. Internet of Things (IoT), Edge, and Cloud Computing technologies (ECt & CCt, respectively) are among the most widely used and new artificial intelligence methods employed for geomechanical studies. IoT devices act as sensors and cameras for real-time monitoring and mechanical-geological data collection of rocks, such as temperature, movement, pressure, or stress levels. Structural integrity, especially for cap rocks within hydrocarbon systems, and rock mass behavior assessment, to further activities such as enhanced oil recovery (EOR) and underground gas storage (UGS), or to improve safety risk management (SRM) and potential hazards identification (P.H.I), are other benefits from IoT technologies. EC techniques can process, aggregate, and analyze data immediately collected by IoT on a real-time scale, providing detailed insights into the behavior of rocks in various situations (e.g., stress, temperature, and pressure), establishing patterns quickly, and detecting trends. Therefore, this state-of-the-art and useful technology can adopt autonomous systems in rock mechanical surveys, such as drilling and production (in hydrocarbon wells) or excavation (in mining and geotechnics industries). Besides, ECt allows all rock-related operations to be controlled remotely and enables operators to apply changes or make adjustments. It must be mentioned that this feature is very important in environmental goals. More often than not, rock mechanical studies consist of different data, such as laboratory tests, field operations, and indirect information like seismic or well-logging data. CCt provides a useful platform for storing and managing a great deal of volume and different information, which can be very useful in fractured zones. Additionally, CCt supplies powerful tools for predicting, modeling, and simulating rock mechanical information, especially in fractured zones within vast areas. Also, it is a suitable source for sharing extensive information on rock mechanics, such as the direction and size of fractures in a large oil field or mine. The comprehensive review findings demonstrate that digital transformation through integrated IoT, Edge, and Cloud solutions is revolutionizing traditional rock mechanical investigation. These advanced technologies have empowered real-time monitoring, predictive analysis, and data-driven decision-making, culminating in noteworthy enhancements in safety, efficiency, and sustainability. Therefore, by employing IoT, CCt, and ECt, underground operations have experienced a significant boost, allowing for timely and informed actions using real-time data insights. The successful implementation of IoT, CCt, and ECt has led to optimized and safer operations, optimized processes, and environmentally conscious approaches in underground geological endeavors.

Keywords: rock mechanical studies, internet of things, edge computing, cloud computing, underground surveys, geological operations

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