Search results for: Philips mathematical model

Authors: Panwasn Mahalawalert

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The objective of this study was to meta-evaluation of Master Degree theses in Science Program of Evaluation Methodology at Srinakharinwirot University, published during 2008-2011. This study was summative meta-evaluation that evaluated all theses of Master Degree in Science Program of Evaluation Methodology. Data were collected using the theses characteristics recording form and the evaluation meta-evaluation checklist. The collected data were analyzed by two parts: 1) Quantitative data were analyzed by descriptive statistics presented in frequency, percentages, mean, and standard deviation and 2) Qualitative data were analyzed by content analysis. The results of this study were found the theses characteristics was results revealed that most of theses were published in 2011. The largest group of theses researcher were female and were from the government office. The evaluation model of all theses were Decision-Oriented Evaluation Model. The objective of all theses were evaluate the project or curriculum. The most sampling technique were used the multistage random sampling technique. The most tool were used to gathering the data were questionnaires. All of the theses were analysed by descriptive statistics. The meta-evaluation results revealed that most of theses had fair on Utility Standards and Feasibility Standards, good on Propriety Standards and Accuracy Standards.

Keywords: meta-evaluation, evaluation, master degree theses, Srinakharinwirot University

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Authors: Mayowa Saheed Sanusi A, Musiliu Olushola Sunmonua, Abdulquadri Alakab Owolabi Raheema, Adeyemi Ikimot Adejokea

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The development of healthy cookies for health-conscious consumers cannot be overemphasized in the present global health crisis. This study was aimed to evaluate and model the influence of ripeness levels of papaya puree (unripe, ripe and overripe), oven temperature (130°C, 150°C and 170°C) and oven rack speed (stationary, 10 and 20 rpm) on physicochemical properties of papaya-based cookies using Response Surface Methodology (RSM). The physicochemical properties (baking time, cookies mass, cookies thickness, spread ratio, proximate composition, Calcium, Vitamin C and Total Phenolic Content) were determined using standard procedures. The data obtained were statistically analysed at p≤0.05 using ANOVA. The polynomial regression model of response surface methodology was used to model the physicochemical properties. The adequacy of the models was determined using the coefficient of determination (R²) and the response optimizer of RSM was used to determine the optimum physicochemical properties for the papaya-based cookies. Cookies produced from overripe papaya puree were observed to have the shortest baking time; ripe papaya puree favors cookies spread ratio, while the unripe papaya puree gives cookies with the highest mass and thickness. The highest crude protein content, fiber content, calcium content, Vitamin C and Total Phenolic Content (TPC) were observed in papaya based-cookies produced from overripe puree. The models for baking time, cookies mass, cookies thickness, spread ratio, moisture content, crude protein and TPC were significant, with R2 ranging from 0.73 – 0.95. The optimum condition for producing papaya based-cookies with desirable physicochemical properties was obtained at 149°C oven temperature, 17 rpm oven rack speed and with the use of overripe papaya puree. The Information on the use of puree from unripe, ripe and overripe papaya can help to increase the use of underutilized unripe or overripe papaya and also serve as a strategic means of obtaining a fat substitute to produce new products with lower production cost and health benefit.

Keywords: papaya based-cookies, modeling, response surface methodology, physicochemical properties

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Authors: C. Fernandez-Plaza, I. Abad, E. Diaz, I. Diaz

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Births occurring before the 37th week of gestation are considered preterm births. A threat of preterm is defined as the beginning of regular uterine contractions, dilation and cervical effacement between 23 and 36 gestation weeks. To author's best knowledge, the factors that determine the beginning of the birth are not completely defined yet. In particular, the incidence of sleep habits on preterm births is weekly studied. The aim of this study is to develop a model to predict the factors affecting premature delivery on pregnancy, based on the above potential risk factors, including those derived from sleep habits and light exposure at night (introduced as 12 variables obtained by a telephone survey using two questionnaires previously used by other authors). Thus, three groups of variables were included in the study (maternal, fetal and sleep habits). The study was approved by Research Ethics Committee of the Principado of Asturias (Spain). An observational, retrospective and descriptive study was performed with 481 births between January 1, 2015 and May 10, 2016 in the University Central Hospital of Asturias (Spain). A statistical analysis using SPSS was carried out to compare qualitative and quantitative variables between preterm and term delivery. Chi-square test qualitative variable and t-test for quantitative variables were applied. Statistically significant differences (p < 0.05) between preterm vs. term births were found for primiparity, multi-parity, kind of conception, place of residence or premature rupture of membranes and interruption during nights. In addition to the statistical analysis, machine learning methods to look for a prediction model were tested. In particular, tree based models were applied as the trade-off between performance and interpretability is especially suitable for this study. C5.0, recursive partitioning, random forest and tree bag models were analysed using caret R-package. Cross validation with 10-folds and parameter tuning to optimize the methods were applied. In addition, different noise reduction methods were applied to the initial data using NoiseFiltersR package. The best performance was obtained by C5.0 method with Accuracy 0.91, Sensitivity 0.93, Specificity 0.89 and Precision 0.91. Some well known preterm birth factors were identified: Cervix Dilation, maternal BMI, Premature rupture of membranes or nuchal translucency analysis in the first trimester. The model also identifies other new factors related to sleep habits such as light through window, bedtime on working days, usage of electronic devices before sleeping from Mondays to Fridays or change of sleeping habits reflected in the number of hours, in the depth of sleep or in the lighting of the room. IF dilation < = 2.95 AND usage of electronic devices before sleeping from Mondays to Friday = YES and change of sleeping habits = YES, then preterm is one of the predicting rules obtained by C5.0. In this work a model for predicting preterm births is developed. It is based on machine learning together with noise reduction techniques. The method maximizing the performance is the one selected. This model shows the influence of variables related to sleep habits in preterm prediction.

Keywords: machine learning, noise reduction, preterm birth, sleep habit

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Authors: Stephen Eyije Abechi, Casimir Emmanuel Gimba, Zaharaddeen Nasiru Garba, Sani Shamsudeen, David Ebuka Authur

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The mechanisms of corrosion inhibition of mild steel in acid medium using Acalypha chamaedrifolia leaves extract as potential green inhibitor were investigated. Gravimetric (weight loss) technique was used for the corrosion studies. Mild steel coupons of 2cm × 1cm × 0.27 cm dimensions were exposed for varying durations of between 24 to 120 hours, in 1M HCl medium containing a varying concentrations of the leaves extract (0.25g/L, - 1.25g/L). The results show that corrosion rates dropped from a value of 0.49 mgcm-2hr-1 for the uninhibited medium to a value of 0.15 mgcm-2hr-1 for the inhibited medium of 1M HCl in 0.25 g/l of the extract. Values of corrosion inhibition efficiencies of 70.38-85.11% were observed as the concentration of the inhibitor were increased from 0.25g/L, - 1.25g/L. Corrosion Inhibition was found to increase with increase in immersion time and temperature. The magnitude of the Ea indicates that the interaction between the metal surface and the inhibitor was chemisorptions. The Adsorption process fit into the Langmuir isotherm model with a correlation coefficient of 0.97. Evidence from molecular dynamics model shows that Methyl stearate (Line 5) and (3Z, 13Z)-2-methyloctadeca-3,13-dien-1-ol (line 11) were found to have the highest binding energy of -197.69 ± 3.12 and-194.56 ± 10.04 in kcal/mol respectively. The binding energy of these compounds indicates that they would be a very good corrosion inhibitor for mild steel and other Fe related materials.

Keywords: binding energy, corrosion, inhibitor, Langmuir isotherm, mild steel.

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Authors: Kimberly Samaha

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The Bio-Hub Ecosystem model was developed to address a critical area of concern within the global energy market regarding biomass as a feedstock for power plants. Yet the lack of an economically-viable business model for bioenergy facilities has resulted in the continuation of idled and decommissioned plants. This study analyzed data and submittals to the Born Global Maine Innovation Challenge. The Innovation Challenge was a global innovation challenge to identify process innovations that could address a ‘whole-tree’ approach of maximizing the products, byproducts, energy value and process slip-streams into a circular zero-waste design. Participating companies were at various stages of developing bioproducts and included biofuels, lignin-based products, carbon capture platforms and biochar used as both a filtration medium and as a soil amendment product. This case study shows the QCA (Qualitative Comparative Analysis) methodology of the prequalification process and the resulting techno-economic model that was developed for the maximizing profitability of the Bio-Hub Ecosystem through continuous expansion of system waste streams into valuable process inputs for co-hosts. A full site plan for the integration of co-hosts (biorefinery, land-based shrimp and salmon aquaculture farms, a tomato green-house and a hops farm) at an operating forestry-based biomass to energy plant in West Enfield, Maine USA. This model and process for evaluating the profitability not only proposes models for integration of forestry, aquaculture and agriculture in cradle-to-cradle linkages of what have typically been linear systems, but the proposal also allows for the early measurement of the circularity and impact of resource use and investment risk mitigation, for these systems. In this particular study, profitability is assessed at two levels CAPEX (Capital Expenditures) and in OPEX (Operating Expenditures). Given that these projects start with repurposing facilities where the industrial level infrastructure is already built, permitted and interconnected to the grid, the addition of co-hosts first realizes a dramatic reduction in permitting, development times and costs. In addition, using the biomass energy plant’s waste streams such as heat, hot water, CO₂ and fly ash as valuable inputs to their operations and a significant decrease in the OPEX costs, increasing overall profitability to each of the co-hosts bottom line. This case study utilizes a proprietary techno-economic model to demonstrate how utilizing waste streams of a biomass energy plant and/or biorefinery, results in significant reduction in OPEX for both the biomass plants and the agriculture and aquaculture co-hosts. Economically viable Bio-Hubs with favorable environmental and community impacts may prove critical in garnering local and federal government support for pilot programs and more wide-scale adoption, especially for those living in severely economically depressed rural areas where aging industrial sites have been shuttered and local economies devastated.

Keywords: bio-economy, biomass energy, financing, zero-waste

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Authors: Tharsinithevy Kirupananthan, Thivahary Geretharan

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Since creation of agricultural enterprises going to reflect the micro and macro level development of Sri Lanka, it is vey important to study the entrepreneurial trends of Agricultural Undergraduates. Likert scale scoring method was used to assess the responses of involvement, Role model effect, aware of demands, confidence and willingness. 37.8% were strongly agreed to do full time business. The average score for to do agriculture businesses were between agree and strongly agree. The average scores for role model effects were less than agree. Average score for aware of needs of society was less than agree. 75.7% of them were able to identify the demands of the society. The demands identified were human capital, self sufficient domestic production, safe and nutritional foods. The confidence of having enough skills score was less than agree. 64.1% of them were owned special skills to carry out entrepreneurial activities. Such skills were possession of different human capitals management skills. The willingness responses scores were more than agree. 61.5% of them were discussed their business plan. Their dream plans were development of new food products, Quality planting materials, harmless method of cultivation and floricultural industry. Those were supported by government policies and other related organizations.

Keywords: agricultural undergraduates, entrepreneurial trends, likert scale Sri Lanka

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Authors: A. Chowdhury, P. Egodawatta, J. M. McGree, A. Goonetilleke

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Hydrologic models are increasingly used as tools to predict stormwater quantity and quality from urban catchments. However, due to a range of practical issues, most models produce gross errors in simulating complex hydraulic and hydrologic systems. Difficulty in finding a robust approach for model calibration is one of the main issues. Though automatic calibration techniques are available, they are rarely used in common commercial hydraulic and hydrologic modelling software e.g. MIKE URBAN. This is partly due to the need for a large number of parameters and large datasets in the calibration process. To overcome this practical issue, a framework for automatic calibration of a hydrologic model was developed in R platform and presented in this paper. The model was developed based on the time-area conceptualization. Four calibration parameters, including initial loss, reduction factor, time of concentration and time-lag were considered as the primary set of parameters. Using these parameters, automatic calibration was performed using Approximate Bayesian Computation (ABC). ABC is a simulation-based technique for performing Bayesian inference when the likelihood is intractable or computationally expensive to compute. To test the performance and usefulness, the technique was used to simulate three small catchments in Gold Coast. For comparison, simulation outcomes from the same three catchments using commercial modelling software, MIKE URBAN were used. The graphical comparison shows strong agreement of MIKE URBAN result within the upper and lower 95% credible intervals of posterior predictions as obtained via ABC. Statistical validation for posterior predictions of runoff result using coefficient of determination (CD), root mean square error (RMSE) and maximum error (ME) was found reasonable for three study catchments. The main benefit of using ABC over MIKE URBAN is that ABC provides a posterior distribution for runoff flow prediction, and therefore associated uncertainty in predictions can be obtained. In contrast, MIKE URBAN just provides a point estimate. Based on the results of the analysis, it appears as though ABC the developed framework performs well for automatic calibration.

Keywords: automatic calibration framework, approximate bayesian computation, hydrologic and hydraulic modelling, MIKE URBAN software, R platform

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Authors: Leila Najeh Bel'Kiry

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Artificial intelligence (AI) brought about many language robots, with ChatGPT being the most sophisticated thanks to its human-like linguistic capabilities. This aspect raises the idea of using ChatGPT in learning foreign languages. Starting from the premise that positions ChatGPT as a mediator between the language and the leaner, functioning as a “ghost teacher" offering a peaceful and secure learning space, this study aims to explore the attitudes of Tunisian students of English towards ChatGPT as a “Foreign Language Teacher” . Forty-five students, in their third year of fundamental English at Tunisian universities and high institutes, completed a Likert scale questionnaire consisting of thirty-two items and covering various aspects of language (phonology, morphology, syntax, semantics, and pragmatics). A scale ranging from 'Strongly Disagree,' 'Disagree,' 'Undecided,' 'Agree,' to 'Strongly Agree.' is used to assess the attitudes of the participants towards the integration of ChaGPTin learning a foreign language. Results indicate generally positive attitudes towards the reliance on ChatGPT in learning foreign languages, particularly some compounds of language like syntax, phonology, and morphology. However, learners show insecurity towards ChatGPT when it comes to pragmatics and semantics, where the artificial model may fail when dealing with deeper contextual and nuanced language levels.

Keywords: artificial language model, attitudes, foreign language learning, ChatGPT, linguistic capabilities, Tunisian English language learners

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Authors: Slim Namouchi, Bruno Vallet, Imed Riadh Farah

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3D urban models provide powerful tools for decision making, urban planning, and smart city services. The accuracy of this 3D based systems is directly related to the quality of these models. Since manual large-scale modeling, such as cities or countries is highly time intensive and very expensive process, a fully automatic 3D building generation is needed. However, 3D modeling process result depends on the input data, the proprieties of the captured objects, and the required characteristics of the reconstructed 3D model. Nowadays, producing 3D real-world model is no longer a problem. Remotely sensed data had experienced a remarkable increase in the recent years, especially data acquired using unmanned aerial vehicles (UAV). While the scanning techniques are developing, the captured data amount and the resolution are getting bigger and more precise. This paper presents a literature review, which aims to identify different methods of automatic 3D buildings extractions either from LiDAR or the combination of LiDAR and satellite or aerial images. Then, we present open source technologies, and data models (e.g., CityGML, PostGIS, Cesiumjs) used to integrate these models in geospatial base layers for smart city services.

Keywords: CityGML, LiDAR, remote sensing, SIG, Smart City, 3D urban modeling

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Authors: Salim Al Jadidi, Shian Gao, Shivananda Moolya

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Computational Fluid Dynamic (CFD) technique coupled with Sub-Grid-Scale (SGS) model is used to study the flow behavior of heavy oil-water-air flow in a horizontal pipe by adapting ANSYS Fluent CFD software. The technique suitable for the transport of water-lubricated heavy viscous oil in a horizontal pipe is the Core Annular flow (CAF) technique. The present study focuses on the numerical study of CAF adapting Large Eddy Simulations (LES). The basic objective of the present study is to gain a basic knowledge of the flow behavior of heavy oil using turbulent CAF through a conventional horizontal pipe. This work also focuses on the success and applicability of LES. The simulation of heavy oil-water-air three-phase flow and two-phase flow of heavy oil–water in a conventional horizontal pipe is performed using ANSYS Fluent 16.2 software. The influence of three-phase heavy oil-water air flow in a selected pipe is affected by gravity. It is also observed from the result that the air phase and the variation in the temperature impact the behavior of the annular stream and pressure drop. Some results obtained during the study are validated with the results gained from part of the literature experiments and simulations, and the results show reasonably good agreement between the studies.

Keywords: computational fluid dynamics, gravity, heavy viscous oil, three-phase flow

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Authors: Tarandeep Kaur

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Generation Y and Z nursing students have a much higher need for technology-based stimulation than previous generations, as they may find traditional methods of education boring and disinterested. These generations prefer experiential learning and the use of advanced technology for enhanced learning. Therefore, nursing educators must acquire knowledge to make better use of technology and technological tools for instruction. Millennials and generation are digital natives, optimistic, assertive, want engagement, instant feedback, and collaborative approach. The integration of technology and the efficacy of its use can be challenging for nursing educators. The SAMR (substitution, augmentation, modification, and redefinition) model designed and developed by Dr. Ruben Puentedura can help nursing educators to engage their students in different levels of technology integration for effective learning. Nursing educators should understand that technology use in the classroom must be purposeful. The influx of technology in nursing education is ever-changing; therefore, nursing educators have to constantly enhance and develop technical skills to keep up with the emerging technology in the schools as well as hospitals. In the Saskatchewan Collaborative Bachelor of Nursing (SCBSCN) program at Saskatchewan polytechnic, we use technology at various levels using the SAMR model in our program, including low and high-fidelity simulation labs. We are also exploring futuristic options of using virtual reality and gaming in our classrooms as an innovative way to motivate, increase critical thinking, create active learning, provide immediate feedback, improve student retention and create collaboration.

Keywords: generations, nursing, SAMR, technology

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Authors: M. N. A. Abdullah, Pritha Roy, R. R. Shil, D. R. Sarker

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Alpha-nucleus interaction is obscured because it produces enhanced cross-sections at large scattering angles known as anomaly in large angle scattering (ALAS). ALAS is prominent in the elastic scattering of α-particles as well as in non-elastic processes involving α-particles for incident energies up to 50 MeV and for targets of mass A ≤ 50. The Woods-Saxon type of optical model potential fails to describe the processes in a consistent manner. Folded potential is a good candidate and often used to construct the potential which is derived from the microscopic as well as semi-microscopic folding calculations. The present work reports the analyses of the elastic scattering of α-particles from ²⁴Mg and ²⁸Si at Eα=22-100 MeV and 14.4-120 MeV incident energies respectively in terms of the modified single-folded (MSF) potential. To derive the MSF potential, we take the view that the nucleons in the target nuclei ²⁴Mg and ²⁸Si are primarily in α-like clusters and the rest of the time in unclustered nucleonic configuration. The MSF potential, found in this study, does not need any renormalization over the whole range of incident α energies, and the renormalization factor has been found to be exactly 1 for both the targets. The best-fit parameters yield 4Aα = 21 and AN = 3 for α-²⁴Mg potential, and 4Aα = 26 and AN = 2 for α-²⁸Si potential in time-average pictures. The root-mean-square radii of both ²⁴Mg and ²⁸Si are also deduced, and the results obtained from this work agree well with the outcomes of other studies.

Keywords: elastic scattering, optical model, folded potential, renormalization

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Authors: A. Luft, S. Bremen, N. Balc

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The task of flexibility planning and design, just like factory planning, for example, is to create the long-term systemic framework that constitutes the restriction for short-term operational management. This is a strategic challenge since, due to the decision defect character of the underlying flexibility problem, multiple types of flexibility need to be considered over the course of various scenarios, production programs, and production system configurations. In this context, an evaluation model has been developed that integrates both conventional and additive resources on a basic task level and allows the quantification of flexibility enhancement in terms of mix and volume flexibility, complexity reduction, and machine capacity. The model helps companies to decide in early decision-making processes about the potential gains of implementing additive manufacturing technologies on a strategic level. For companies, it is essential to consider both additive and conventional manufacturing beyond pure unit costs. It is necessary to achieve an integrative view of manufacturing that incorporates both additive and conventional manufacturing resources and quantifies their potential with regard to flexibility and manufacturing complexity. This also requires a structured process for the strategic production systems design that spans the design of various scenarios and allows for multi-dimensional and comparative analysis. A respective guideline for the planning of additive resources on a strategic level is being laid out in this paper.

Keywords: additive manufacturing, production system design, flexibility enhancement, strategic guideline

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Authors: Fitri Nugraheni, Adwitya Bhaskara, N. Faried Hanafi

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Coastal is one area that can be a place to live. Various buildings can be built in the area around the beach. Many Indonesians use beaches as housing and work, but we know that coastal areas are identical to tsunami and wind. Costs incurred due to permanent damage caused by tsunamis and wind disasters in Indonesia can be minimized by replacing permanent buildings into semi-permanent buildings. Semi-permanent buildings can be realized by using cold-formed steel as a building. Thus, the purpose of this research is to provide efficient semi-permanent building recommendations for residents around the coast. The research is done by first designing the building model by using sketch-up software, then the validation phase is done in consultation with the expert consultant of cold form steel structure. Based on the results of the interview there are several revisions on several sides of the building by adding some bracing rods on the roof, walls and floor frame. The result of this research is recommendation of semi-permanent building model, where the nature of the building; easy to disassemble and install (knockdown), tsunami-friendly (continue the tsunami load), cost and time efficient (using cold-formed-steel and prefabricated GRC), zero waste, does not require many workers (less labor). The recommended building design concept also keeps the architecture side in mind thus it remains a comfortable occupancy for the residents.

Keywords: construction method, cold-formed steel, efficiency, semi-permanent building, tsunami

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Authors: Alasdair Stanton

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What makes for a good explanation? Twenty years after Wendt’s important treatment of constitution and causation, non-causal explanations (sometimes referred to as ‘understanding’, or ‘descriptive inference’) have become, if not mainstream, at least accepted within International Relations. This article proceeds in two parts: firstly, it examines closely Wendt’s constitutional claims, and while it agrees there is a difference between causal and constitutional, rejects the view that constitutional explanations lack temporality. In fact, this author concludes that a constitutional argument is only possible if it relies upon a more foundational, causal argument. Secondly, through theoretical analysis of the constitutional argument, this research seeks to delineate temporal and non-temporal ways of explaining within International Relations. This article concludes that while the constitutional explanation, like other logical arguments, including comparative, and counter-factual, are not truly non-causal explanations, they are not bound as tightly to the ‘real world’ as temporal arguments such as cause-effect, process tracing, or even interpretivist accounts. However, like mathematical models, non-temporal arguments should aim for empirical testability as well as internal consistency. This work aims to give clear theoretical grounding to those authors using non-temporal arguments, but also to encourage them, and their positivist critics, to engage in thoroughgoing empirical tests.

Keywords: causal explanation, constitutional understanding, empirical, temporality

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Authors: Bao Liu, Maarten Vanierschot, Frank Buysschaert

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The present work examines the wake dynamics of a rim-driven thruster (RDT) with Computational Fluid Dynamics (CFD). Unsteady Reynolds-averaged Navier-Stokes (URANS) equations were solved in the commercial solver ANSYS Fluent in combination with the SST k-ω turbulence model. The application of the moving reference frame (MRF) and sliding mesh (SM) approach to handling the rotational movement of the propeller were compared in the transient simulations. Validation and verification of the numerical model was performed to ensure numerical accuracy. Two representative scenarios were considered, i.e., the bollard condition (J=0) and a very light loading condition(J=0.7), respectively. From the results, it’s confirmed that compared to the SM method, the MRF method is not suitable for resolving the unsteady flow features as it only gives the general mean flow but smooths out lots of characteristic details in the flow field. By evaluating the simulation results with the SM technique, the instantaneous wake flow field under both conditions is presented and analyzed, most notably the helical vortex structure. It’s observed from the results that the tip vortices, blade shed vortices, and hub vortices are present in the wake flow field and convect downstream in a highly non-linear way. The shear layer vortices shedding from the duct displayed a strong interaction with the distorted tip vortices in an irregularmanner.

Keywords: computational fluid dynamics, rim-driven thruster, sliding mesh, wake dynamics

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Authors: Anton James

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This study explored the contribution of parenting styles in the Maternal Perception of Compliance Model (MPCM). This model explores maternal expectations to illustrate the formation of maternal perception of severity of noncompliance in adolescent children. The methodology consisted of three stages: In the first stage, a focus group was held, and the data was analysed to fine-tune the interview schedule. In the second stage, a single interview was held, and the interview schedule was further modified. The third and the final stage consisted of interviewing six mothers who had adolescent children. They were chosen with ‘maximum variation’ approach to represent three tiered socioeconomic statuses, and Asian, white and black ethnicities. The data was thematically analysed in a hybrid fashion: inductive coding and deductive assignment of codes into discrete parenting styles. The study found: a) parenting styles are not always discrete and sometimes it can be mixed. b) The parenting styles are influenced by culture, socioeconomic status, transgenerational knowledge, academic knowledge, observational knowledge, self-reflective knowledge, and parental anxiety. c) The parenting style functioned a mediating mechanism where it attempted to converge discrepancies between parental expectations of compliance with maternal perception of severity of noncompliance. The findings of parenting styles were discussed in relation to MPCM.

Keywords: compliance, expectation, parenting styles, perception

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Authors: H. Jung, N. Kim, B. Kang, J. Choe

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History matching is a crucial procedure for predicting reservoir performances and making future decisions. However, it is difficult due to uncertainties of initial reservoir models. Therefore, it is important to have reliable initial models for successful history matching of highly heterogeneous reservoirs such as channel reservoirs. In this paper, we proposed a novel scheme for regenerating geological models using support vector machine (SVM) and principal component analysis (PCA). First, we perform PCA for figuring out main geological characteristics of models. Through the procedure, permeability values of each model are transformed to new parameters by principal components, which have eigenvalues of large magnitude. Secondly, the parameters are projected into two-dimensional plane by multi-dimensional scaling (MDS) based on Euclidean distances. Finally, we train an SVM classifier using 20% models which show the most similar or dissimilar well oil production rates (WOPR) with the true values (10% for each). Then, the other 80% models are classified by trained SVM. We select models on side of low WOPR errors. One hundred channel reservoir models are initially generated by single normal equation simulation. By repeating the classification process, we can select models which have similar geological trend with the true reservoir model. The average field of the selected models is utilized as a probability map for regeneration. Newly generated models can preserve correct channel features and exclude wrong geological properties maintaining suitable uncertainty ranges. History matching with the initial models cannot provide trustworthy results. It fails to find out correct geological features of the true model. However, history matching with the regenerated ensemble offers reliable characterization results by figuring out proper channel trend. Furthermore, it gives dependable prediction of future performances with reduced uncertainties. We propose a novel classification scheme which integrates PCA, MDS, and SVM for regenerating reservoir models. The scheme can easily sort out reliable models which have similar channel trend with the reference in lowered dimension space.

Keywords: history matching, principal component analysis, reservoir modelling, support vector machine

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Authors: Tanja Ecken, Laura Fricke, Anika Wehling, Maren M. Michaelsen, Tobias Esch

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Studies and applied experiences evidence severe and traumatic accidents not only require physical rehabilitation and recovery but also necessitate a psychological adaption and reorganization to the changed living conditions. Neurobiological models underpinning the experience of happiness and satisfaction postulate life shocks to potentially enhance the experience of happiness and life satisfaction, i.e., posttraumatic growth (PTG). This present study aims to provide an in-depth understanding of the underlying psychological processes of PTG and to outline its consequences on subjective happiness and life satisfaction. To explore the aforementioned, Esch’s ABC Model was used as guidance for the development of a questionnaire assessing changes in happiness and life satisfaction and for a schematic model postulating the development of PTG in the context of paraplegia. Two-stage qualitative interview procedures explored participants’ experiences of paraplegia. Specifically, narrative, semi-structured interviews (N=28) focused on the time before and after the accident, the availability of supportive resources, and potential changes in the perception of happiness and life satisfaction. Qualitative analysis (Grounded Theory) indicated an initial phase of reorganization was followed by a gradual psychological adaption to novel, albeit reduced, opportunities in life. Participants reportedly experienced a ‘compelled’ slowing down and elements of mindfulness, subsequently instilling a sense of gratitude and joy in relation to life’s presumed trivialities. Despite physical limitations and difficulties, participants reported an enhanced ability to relate to oneself and others and a reduction of perceived everyday nuisances. Concluding, PTG can be experienced in response to severe, traumatic life events and has the potential to enrich the lives of affected persons in numerous, unexpected and yet challenging ways. PTG appears to be a spectrum comprised of an interplay of internal and external resources underpinned by neurobiological processes. Participants experienced PTG irrelevant of age, gender, marital status, income or level of education.

Keywords: post traumatic growth, happiness, life satisfaction, traumatic life events, paraplegia, ABC model, trauma

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Authors: Mohammad Heidari

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In this paper a method for high strength steel is proposed of residual stresses in autofrettaged tubes by combination of artificial neural networks is presented. Many different thick walled cylinders that were subjected to different conditions were studied. At first, the residual stress is calculated by analytical solution. Then by changing of the parameters that influenced in residual stresses such as percentage of autofrettage, internal pressure, wall ratio of cylinder, material property of cylinder, bauschinger and hardening effect factor, a neural network is created. These parameters are the input of network. The output of network is residual stress. Numerical data, employed for training the network and capabilities of the model in predicting the residual stress has been verified. The output obtained from neural network model is compared with numerical results, and the amount of relative error has been calculated. Based on this verification error, it is shown that the radial basis function of neural network has the average error of 2.75% in predicting residual stress of thick wall cylinder. Further analysis of residual stress of thick wall cylinder under different input conditions has been investigated and comparison results of modeling with numerical considerations shows a good agreement, which also proves the feasibility and effectiveness of the adopted approach.

Keywords: thick walled cylinder, residual stress, radial basis, artificial neural network

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Authors: Mohammad Hossein Mohammadi Sanjani, Ashknaz Oraee, Arian Amirnia, Atena Taheri, Mohammadreza Arabi, Mahmud Fotuhi-Firuzabad

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Ferroresonance effects cause overvoltage in medium voltage transformers and isolators used in electrical networks. Ferroresonance effects are nonlinear and occur between the network capacitor and the nonlinear inductance of the voltage transformer during saturation. This phenomenon is unwanted for transformers since it causes overheating, introduction of high dynamic forces in primary coils, and rise of voltage in primary coils for the voltage transformer. Furthermore, it results in electrical and thermal failure of the transformer. Expansion of distribution lines, design of the transformer in smaller sizes, and the increase of harmonics in distribution networks result in an increase of ferroresonance. There is limited literature available to improve the effects of ferroresonance; therefore, optimizing its effects for voltage transformers is of great importance. In this study, comprehensive modeling of a medium voltage block-type voltage transformer is performed. In addition, a recent model is proposed to improve the performance of voltage transformers during the occurrence of ferroresonance using damping oscillations. Also, transformer design optimization is presented in this study to show further improvements in the performance of the voltage transformer. The recently proposed model is experimentally tested and verified on a medium voltage transformer in the laboratory, and simulation results show a large reduction of the effects of ferroresonance.

Keywords: optimization, voltage transformer, ferroresonance, modeling, damper

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Authors: G. C. Tikkiwal, Mukesh Upadhyay

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During the surveillance operations at war or peace time, the Radar operator gets a scatter of targets over the screen. This may be a tracked vehicle like tank vis-à-vis T72, BMP etc, or it may be a wheeled vehicle like ALS, TATRA, 2.5Tonne, Shaktiman or moving the army, moving convoys etc. The radar operator selects one of the promising targets into single target tracking (STT) mode. Once the target is locked, the operator gets a typical audible signal into his headphones. With reference to the gained experience and training over the time, the operator then identifies the random target. But this process is cumbersome and is solely dependent on the skills of the operator, thus may lead to misclassification of the object. In this paper, we present a technique using mathematical and statistical methods like fast fourier transformation (FFT) and principal component analysis (PCA) to identify the random objects. The process of classification is based on transforming the audible signature of target into music octave-notes. The whole methodology is then automated by developing suitable software. This automation increases the efficiency of identification of the random target by reducing the chances of misclassification. This whole study is based on live data.

Keywords: radar target, FFT, principal component analysis, eigenvector, octave-notes, DSP

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Authors: Sijie Chen, Xiaofang Chen, Juan Wang, Yingying Zhang, Yu Hong, Wanyu Zhuang, Xinxin Huang, Ping Ou, Longsheng Huang

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Purpose: Autistic symptom improvement can be observed in children treated with acupuncture, but the mechanism is still being explored. In the present study, we used scalp acupuncture to treat autism rat model, and then their improvement in the abnormal behaviors and specific mechanisms behind were revealed by detecting animal behaviors, analyzing the RNA sequencing of the prefrontal cortex(PFC), and observing the ultrastructure of PFC neurons under the transmission electron microscope. Methods: On gestational day 12.5, Wistar rats were given valproic acid (VPA) by intraperitoneal injection, and their offspring were considered to be reliable rat models of autism. They were randomized to VPA or VPA-acupuncture group (n=8). Offspring of Wistar pregnant rats that were simultaneously injected with saline were randomly selected as the wild-type group (WT). VPA_acupuncture group rats received acupuncture intervention at 23 days of age for 4 weeks, and the other two groups followed without intervention. After the intervention, all experimental rats underwent behavioral tests. Immediately afterward, they were euthanized by cervical dislocation, and their prefrontal cortex was isolated for RNA sequencing and transmission electron microscopy. Results: The main results are as follows: 1. Animal behavioural tests: VPA group rats showed more anxiety-like behaviour and repetitive, stereotyped behaviour than WT group rats. While VPA group rats showed less spatial exploration ability, activity level, social interaction, and social novelty preference than WT group rats. It was gratifying to observe that acupuncture indeed improved these abnormal behaviors of autism rat model. 2. RNA-sequencing: The three groups of rats differed in the expression and enrichment pathways of multiple genes related to synaptic function, neural signal transduction, and circadian rhythm regulation. Our experiments indicated that acupuncture can alleviate the major symptoms of ASD by improving these neurological abnormalities. 3. Under the transmission electron microscopy, several lysosomes and mitochondrial structural abnormalities were observed in the prefrontal neurons of VPA group rats, which were manifested as atrophy of the mitochondrial membran, blurring or disappearance of the mitochondrial cristae, and even vacuolization. Moreover, the number of synapses and synaptic vesicles was relatively small. Conversely, the mitochondrial structure of rats in the WT group and VPA_acupuncture was normal, and the number of synapses and synaptic vesicles was relatively large. Conclusion: Acupuncture effectively improved the abnormal behaviors of autism rat model and the ultrastructure of the PFC neurons, which might worked by improving their abnormal synaptic function, synaptic plasticity and promoting neuronal signal transduction.

Keywords: autism spectrum disorder, acupuncture, animal behavior, RNA sequencing, transmission electron microscope

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Authors: Gabriella Fardhiyanti, Victor Wee

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Air connectivity is the crucial factors to boost a region economics growth. It will open the accessibility to support regional competitiveness and helps to achieve ASEAN (Association of Southeast Asian Nations) integration in term of economic integration, business investment, promote intra-regional trade, and creates the sense of belongingness among ASEAN people in the region. An increasing number of air connectivity and transportation will be benefiting the region because air transportation is a vital hub for ASEAN. The aim of this paper is to address the importance of air connectivity in promoting ASEAN Integration, by focusing on the ASEAN vision for a more integrated region. The assessment uses based on the Netscan Air connectivity model based on the flight destination and airport connectivity index, further analysis present that air connectivity significantly influence ASEAN tourism sector. Follow by the implications of open skies policy for the liberation of the aviation industry and the growth of low cost-carriers (LCCs) in the region. This paper provides recommendation and strategy for overcoming the challenges faced by ASEAN to boost ASEAN tourism integration successfully. The findings can assist in guiding policy and industry stakeholders in the future decision relating to air liberalization and more integrated system in the region.

Keywords: air connectivity, ASEAN integration, low-cost carries, NetScan connectivity model, open skies policy

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Authors: Ellen Nhedzi Gozo

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Unavailability of adequate hydro-meteorological data has always limited the analysis and understanding of hydrological behaviour of several dam catchments including Mazowe Dam in Zimbabwe. The problem of insufficient data for Mazowe Dam catchment analysis was solved by extracting catchment characteristics and aerial hydro-meteorological data from ASTER, LANDSAT, Shuttle Radar Topographic Mission SRTM remote sensing (RS) images using ILWIS, ArcGIS and ERDAS Imagine geographic information systems (GIS) software. Available observed hydrological as well as meteorological data complemented the use of the remotely sensed information. Ground truth land cover was mapped using a Garmin Etrex global positioning system (GPS) system. This information was then used to validate land cover classification detail that was obtained from remote sensing images. A bathymetry survey was conducted using a SONAR system connected to GPS. Hydrological modelling using the HBV model was then performed to simulate the hydrological process of the catchment in an effort to verify the reliability of the derived parameters. The model output shows a high Nash-Sutcliffe Coefficient that is close to 1 indicating that the parameters derived from remote sensing and GIS can be applied with confidence in the analysis of Mazowe Dam catchment.

Keywords: geographic information systems, hydrological modelling, remote sensing, water resources management

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Authors: A. Dėdelė, A. Miškinytė

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The assessment of air pollution exposure in different microenvironments is important for better understanding the relationship between health effects caused by air pollution. The recent researches revealed that the level of air pollution in transport microenvironment contributes considerably to the total exposure of air pollution. The aim of the study was to determine air pollution of nitrogen dioxide and to assess the exposure of NO2 dependence on the chosen commuting mode using a global positioning system (GPS). The same travel destination was chosen and 30 rides in three different commuting modes: cycling, walking, and public transport were made. Every different mean of transport is associated with different route. GPS device and travel diary data were used to track all routes of different commuting modes. Air pollution of nitrogen dioxide was determined using the ADMS-Urban dispersion model. The average annual concentration of nitrogen dioxide was modeled for 2011 year in Kaunas city. The geographical information systems were used to visualize the travel routes, to create maps indicating the route of different commuting modes and to combine modelled nitrogen dioxide data. The results showed that there is a significant difference between the selected commuting mode and the exposure of nitrogen dioxide. The concentrations in the microenvironments were 22.4 μg/m3, 21.4 μg/m3, and 25.9 μg/m3 for cycling, walking and public transport respectively. Of all the modes of commuting, the highest average exposure of nitrogen dioxide was found travelling by public transport, while the lowest average concentration of NO2 was determined by walking.

Keywords: nitrogen dioxide, dispersion model, commuting mode, GPS

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Authors: Kimberly Samaha

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In order to attract new types of investors into the emerging Bio-Economy, a new set of metrics and measurement system is needed to better quantify the environmental, social and economic impacts of circular zero-waste design. The Bio-Hub Ecosystem model was developed to address a critical area of concern within the global energy market regarding the use of biomass as a feedstock for power plants. Lack of an economically-viable business model for bioenergy facilities has resulted in the continuation of idled and decommissioned plants. In particular, the forestry-based plants which have been an invaluable outlet for woody biomass surplus, forest health improvement, timber production enhancement, and especially reduction of wildfire risk. This study looked at repurposing existing biomass-energy plants into Circular Zero-Waste Bio-Hub Ecosystems. A Bio-Hub model that first targets a ‘whole-tree’ approach and then looks at the circular economics of co-hosting diverse industries (wood processing, aquaculture, agriculture) in the vicinity of the Biomass Power Plants facilities. It proposes not only models for integration of forestry, aquaculture, and agriculture in cradle-to-cradle linkages of what have typically been linear systems, but the proposal also allows for the early measurement of the circularity and impact of resource use and investment risk mitigation, for these systems. Typically, life cycle analyses measure environmental impacts of different industrial production stages and are not integrated with indicators of material use circularity. This concept paper proposes the further development of a new set of metrics that would illustrate not only the typical life-cycle analysis (LCA), which shows the reduction in greenhouse gas (GHG) emissions, but also the zero-waste circularity measures of mass balance of the full value chain of the raw material and energy content/caloric value. These new measures quantify key impacts in making hyper-efficient use of natural resources and eliminating waste to landfills. The project utilized traditional LCA using the GREET model where the standalone biomass energy plant case was contrasted with the integration of a jet-fuel biorefinery. The methodology was then expanded to include combinations of co-hosts that optimize the life cycle of woody biomass from tree to energy, CO₂, heat and wood ash both from an energy/caloric value and for mass balance to include reuse of waste streams which are typically landfilled. The major findings of both a formal LCA study resulted in the masterplan for the first Bio-Hub to be built in West Enfield, Maine. Bioenergy facilities are currently at a critical juncture where they have an opportunity to be repurposed into efficient, profitable and socially responsible investments, or be idled and scrapped. If proven as a model, the expedited roll-out of these innovative scenarios can set a new standard for circular zero-waste projects that advance the critical transition from the current ‘take-make-dispose’ paradigm inherent in the energy, forestry and food industries to a more sustainable bio-economy paradigm where waste streams become valuable inputs, supporting local and rural communities in simple, sustainable ways.

Keywords: bio-economy, biomass energy, financing, metrics

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Authors: Mohsen Torabi, Nader Karimi, Kaili Zhang

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This work aims to provide a comprehensive study on the heat transfer and entropy generation rates of a horizontal channel partially filled with a porous medium which experiences internal heat generation or consumption due to exothermic or endothermic chemical reaction. The focus has been given to the local thermal non-equilibrium (LTNE) model. The LTNE approach helps us to deliver more accurate data regarding temperature distribution within the system and accordingly to provide more accurate Nusselt number and entropy generation rates. Darcy-Brinkman model is used for the momentum equations, and constant heat flux is assumed for boundary conditions for both upper and lower surfaces. Analytical solutions have been provided for both velocity and temperature fields. By incorporating the investigated velocity and temperature formulas into the provided fundamental equations for the entropy generation, both local and total entropy generation rates are plotted for a number of cases. Bifurcation phenomena regarding temperature distribution and interface heat flux ratio are observed. It has been found that the exothermicity or endothermicity characteristic of the channel does have a considerable impact on the temperature fields and entropy generation rates.

Keywords: entropy generation, exothermicity or endothermicity, forced convection, local thermal non-equilibrium, analytical modelling

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Authors: Allyson Dale, Max Hlywa

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The Canadian public expects the highest moral standards from Canadian Armed Forces (CAF) members and Department of National Defence (DND) employees. The Chief, Professional Conduct and Culture (CPCC) stood up in April 2021 with the mission of ensuring that the defence culture and members’ conduct are aligned with the ethical principles and values that the organization aspires towards. The Defence Ethics Program (DEP), which stood up in 1997, is a values-based ethics program for individuals and organizations within the DND/CAF and now falls under CPCC. The DEP is divided into five key functional areas, including policy, communications, collaboration, training and education, and advice and guidance. The main focus of the DEP is to foster an ethical culture within defence so that members and organizations perform to the highest ethical standards. The measurement of organizational ethics is often complex and challenging. In order to monitor whether the DEP is achieving its intended outcomes, a performance measurement framework (PMF) was developed using the Director General Military Personnel Research and Analysis (DGMPRA) PMF development process. This evidence-based process is based on subject-matter expertise from the defence team. The goal of this presentation is to describe each stage of the DGMPRA PMF development process and to present and discuss the products of the DEP PMF (e.g., logic model). Specifically, first, a strategic framework was developed to provide a high-level overview of the strategic objectives, mission, and vision of the DEP. Next, Key Performance Questions were created based on the objectives in the strategic framework. A logic model detailing the activities, outputs (what is produced by the program activities), and intended outcomes of the program were developed to demonstrate how the program works. Finally, Key Performance Indicators were developed based on both the intended outcomes in the logic model and the Key Performance Questions in order to monitor program effectiveness. The Key Performance Indicators measure aspects of organizational ethics such as ethical conduct and decision-making, DEP collaborations, and knowledge and awareness of the Defence Ethics Code while leveraging ethics-related items from multiple DGMPRA surveys where appropriate.

Keywords: defence ethics, ethical culture, organizational performance, performance measurement framework

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Authors: Sevelina Ndlovu

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Financial Technology (fintech) advancement is recognised as one of the most transformational innovations in the financial industry. Fintech has given rise to internet-only digital banking, a novel financial technology advancement, and innovation that allows banking services through internet applications with no need for physical branches. This technology is becoming a new banking normal among consumers for its ubiquitous and real-time access advantages. There is evident switching and migration from traditional banking towards these fintech facilities, which could possibly pose a systemic risk if not properly understood and monitored. Fintech advancement has also brought about the emergence and escalation of financial technology consumption themes such as trust, security, perceived risk, and sustainability within the banking industry, themes scarcely covered in existing theoretic literature. To that end, the objective of this research is to investigate factors that determine fintech adoption and propose an integrated adoption model. This study aims to establish what the significant drivers of adoption are and develop a conceptual model that integrates technological, behavioral, and environmental constructs by extending the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2). It proposes integrating constructs that influence financial consumption themes such as trust, perceived risk, security, financial incentives, micro-investing opportunities, and environmental consciousness to determine the impact of these factors on the adoption and intention to use digital banking apps. The main advantage of this conceptual model is the consolidation of a greater number of predictor variables that can provide a fuller explanation of the consumer's adoption of digital banking Apps. Moderating variables of age, gender, and income are incorporated. To the best of author’s knowledge, this study is the first that extends the UTAUT2 model with this combination of constructs to investigate user’s intention to adopt internet-only digital banking apps in the UK context. By investigating factors that are not included in the existing theories but are highly pertinent to the adoption of internet-only banking services, this research adds to existing knowledge and extends the generalisability of the UTAUT2 in a financial services adoption context. This is something that fills a gap in knowledge, as highlighted to needing further research on UTAUT2 after reviewing the theory in 2016 from its original version of 2003. To achieve the objectives of this study, this research assumes a quantitative research approach to empirically test the hypotheses derived from existing literature and pilot studies to give statistical support to generalise the research findings for further possible applications in theory and practice. This research is explanatory or casual in nature and uses cross-section primary data collected through a survey method. Convenient and purposive sampling using structured self-administered online questionnaires is used for data collection. The proposed model is tested using Structural Equation Modelling (SEM), and the analysis of primary data collected through an online survey is processed using Smart PLS software with a sample size of 386 digital bank users. The results are expected to establish if there are significant relationships between the dependent and independent variables and establish what the most influencing factors are.

Keywords: banking applications, digital banking, financial technology, technology adoption, UTAUT2

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