Search results for: vector error correction model (VECM)

Authors: İsmail Seçer, Taştan Seçer

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In this study, the effect of the group counseling on the victimhood perceptions of the primary school 7th and 8th grade students who are determined to be the subject of peer victimization and their dealing way with it was analyzed. The research model is Solomon Four Group Experimental Model. In this model, there are four groups that were determined with random sampling. Two of the groups have been used as experimental group and the other two have been used as control group. Solomon model is defined as real experimental model. In real experimental models, there are multiple groups consisting of subject which have similar characteristics, and selection of the subjects is done with random sampling. For this purpose, 230 students from Kültür Kurumu Primary School in Erzurum were asked to fill Adolescent Peer Victim Form. 100 students whose victim scores were higher and who were determined to be the subject of bullying were talked face to face and informed about the current study, and they were asked if they were willing to participate or not. As a result of these interviews, 60 students were determined to participate in the experimental study and four group consisting of 15 people were created with simple random sampling method. After the groups had been formed, experimental and control group were determined with casting lots. After determining experimental and control groups, an 11-session group counseling activity which was prepared by the researcher according to the literature was applied. The purpose of applying group counseling is to change the ineffective dealing ways with bullying and their victimhood perceptions. Each session was planned to be 75 minutes and applied as planned. In the control groups, counseling activities in the primary school counseling curricula was applied for 11 weeks. As a result of the study, physical, emotional and verbal victimhood perceptions of the participants in the experimental groups were decreased significantly compared to pre-experimental situations and to those in control group. Besides, it was determined that this change observed in the victimhood perceptions of the experimental group occurred independently from the effect of variables such as gender, age and academic success. The first evidence of the study related to the dealing ways is that the scores of the participants in the experimental group related to the ineffective dealing ways such as despair and avoidance is decreased significantly compared to the pre-experimental situation and to those in control group. The second evidence related to the dealing ways is that the scores of the participants in the experimental group related to effective dealing ways such as seeking for help, consulting social support, resistance and optimism is increased significantly compared to the pre-experimental situation and to those in control group. According to the evidence obtained through the study, it can be said that group counseling is an effective approach to change the victimhood perceptions of the individuals who are the subject of bullying and their dealing strategies with it.

Keywords: bullying, perception of victimization, coping strategies, ancova analysis

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Authors: L. Q. Yuan, J. Yang, A. Siddiqui

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A new regression uncertainty analysis methodology was applied to determine the uncertainties of the critical heat flux (CHF) power correlation for an advanced 43-element bundle design, which was developed by Canadian Nuclear Laboratories (CNL) to achieve improved economics, resource utilization and energy sustainability. The new methodology is considered more appropriate than the traditional methodology in the assessment of the experimental uncertainty associated with regressions. The methodology was first assessed using both the Monte Carlo Method (MCM) and the Taylor Series Method (TSM) for a simple linear regression model, and then extended successfully to a non-linear CHF power regression model (CHF power as a function of inlet temperature, outlet pressure and mass flow rate). The regression uncertainty assessed by MCM agrees well with that by TSM. An equation to evaluate the CHF power regression uncertainty was developed and expressed as a function of independent variables that determine the CHF power.

Keywords: CHF experiment, CHF correlation, regression uncertainty, Monte Carlo Method, Taylor Series Method

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Authors: Kalu Uka Orji, Nasiman Sapari, Khamaruzaman W. Yusof

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Exposure of galena (PbS), tealite (PbSnS2), and other associated minerals during mining activities release lead (Pb) and other heavy metals into the mining water through oxidation and dissolution. Heavy metal pollution has become an environmental challenge. Lead, for instance, can cause toxic effects to human health, including brain damage. Ex-mining pond water was reported to contain lead as high as 69.46 mg/L. Conventional treatment does not easily remove lead from water. A promising and emerging treatment technology for lead removal is the application of the electrocoagulation (EC) process. However, some of the problems associated with EC are systematic reactor design, selection of maximum EC operating parameters, scale-up, among others. This study investigated an EC process for the removal of lead from synthetic ex-mining pond water using a batch reactor and Fe electrodes. The effects of various operating parameters on lead removal efficiency were examined. The results obtained indicated that the maximum removal efficiency of 98.6% was achieved at an initial PH of 9, the current density of 15mA/cm2, electrode spacing of 0.3cm, treatment time of 60 minutes, Liquid Motion of Magnetic Stirring (LM-MS), and electrode arrangement = BP-S. The above experimental data were further modeled and optimized using a 2-Level 4-Factor Full Factorial design, a Response Surface Methodology (RSM). The four factors optimized were the current density, electrode spacing, electrode arrangements, and Liquid Motion Driving Mode (LM). Based on the regression model and the analysis of variance (ANOVA) at 0.01%, the results showed that an increase in current density and LM-MS increased the removal efficiency while the reverse was the case for electrode spacing. The model predicted the optimal lead removal efficiency of 99.962% with an electrode spacing of 0.38 cm alongside others. Applying the predicted parameters, the lead removal efficiency of 100% was actualized. The electrode and energy consumptions were 0.192kg/m3 and 2.56 kWh/m3 respectively. Meanwhile, the adsorption kinetic studies indicated that the overall lead adsorption system belongs to the pseudo-second-order kinetic model. The adsorption dynamics were also random, spontaneous, and endothermic. The higher temperature of the process enhances adsorption capacity. Furthermore, the adsorption isotherm fitted the Freundlish model more than the Langmuir model; describing the adsorption on a heterogeneous surface and showed good adsorption efficiency by the Fe electrodes. Adsorption of Pb2+ onto the Fe electrodes was a complex reaction, involving more than one mechanism. The overall results proved that EC is an efficient technique for lead removal from synthetic mining pond water. The findings of this study would have application in the scale-up of EC reactor and in the design of water treatment plants for feed-water sources that contain lead using the electrocoagulation method.

Keywords: ex-mining water, electrocoagulation, lead, adsorption kinetics

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Authors: Leonardo Alfredo Mendoza, Cristian Munoz, Marco Aurelio Pacheco, Manoela Kohler, Evelyn Batista, Rodrigo Moura

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Natural Language Processing (NLP) techniques are increasingly more powerful to be able to interpret the feelings and reactions of a person to a product or service. Sentiment analysis has become a fundamental tool for this interpretation but has few applications in languages other than English. This paper presents a classification of sentiment analysis in Portuguese with a base of comments from social networks in Portuguese. A word embedding's representation was used with a 50-Dimension GloVe pre-trained model, generated through a corpus completely in Portuguese. To generate this classification, the bidirectional long short-term memory and bidirectional Gated Recurrent Unit (GRU) models are used, reaching results of 99.1%.

Keywords: natural processing language, sentiment analysis, bidirectional long short-term memory, BI-LSTM, gated recurrent unit, GRU

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Authors: Wenqing Fan, Yixuan Cheng, Wei Huang

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The diversity and complexity of modern IT systems make it almost impossible for internal teams to find vulnerabilities in all software before the software is officially released. The emergence of threat intelligence and vulnerability reporting policy has greatly reduced the burden on software vendors and organizations to find vulnerabilities. However, to prove the existence of the reported vulnerability, it is necessary but difficult for security incident response team to build a deliberated vulnerable environment from the vulnerability report with limited and incomplete information. This paper presents a structured, standardized, machine-oriented vulnerability intelligence format, that can be used to automate the orchestration of Deliberated Vulnerable Environment (DVE). This paper highlights the important role of software configuration and proof of vulnerable specifications in vulnerability intelligence, and proposes a triad model, which is called DIR (Dependency Configuration, Installation Configuration, Runtime Configuration), to define software configuration. Finally, this paper has also implemented a prototype system to demonstrate that the orchestration of DVE can be automated with the intelligence.

Keywords: DIR triad model, DVE, vulnerability intelligence, vulnerability recurrence

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Authors: Abdusalam Sharf

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In the oil and gas industries, one of the most important issues in drilling wells is understanding the behavior of a flow through an annulus gap in a vertical position, whose outer wall is stationary whilst the inner wall rotates. The main emphasis is placed on a comparison of experimental and computational investigations into the effects of the rotation speed of the inner pipe on the axial velocity profiles. The computational investigations were carried out by employing CFD software, and Gambit and Fluent. Three turbulence models were used: standard, RNG with enhanced wall treatment, and SST model. The profiles of the axial velocity had investigated at different rotation speeds of the inner pipe with three different volumetric flow rates. The comparison results showed that the calculations satisfactorily predict the qualitative features of the axial and swirl velocity profiles and the RNG model performs the best results.

Keywords: computational fluid dynamics (CFD), SST k−ω shear-stress transport (k−ω mode variant), RNG k–ε renormalisation group (k−ε mode variant), y+ dimensionless distance from wall

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Authors: Hong Bae Kim, Chang Ho Hur

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Many governments have tried to reduce CO₂ emissions which are believed to be the main cause for global warming. The deployment of electric automobiles is regarded as an effective way to reduce CO₂ emissions. The Korean government has planned to deploy about 200,000 electric automobiles. The policy for the deployment of electric automobiles aims at not only decreasing gasoline consumption but also increasing electricity production. However, if an electricity consuming regions is not consistent with an electricity producing region, the policy generates environmental problems between regions. Hence, this paper has established the energy multi-region input-output model to specifically analyze the impacts of the deployment of electric automobiles on regional energy consumption and CO₂ emissions. Finally, the paper suggests policy directions regarding the deployment of electric automobiles.

Keywords: electric automobiles, CO2 emissions, regional imbalances in electricity production and consumption, energy multi-region input-output model

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Authors: Sang Kompiang Wirawan, Pandu Prabowo Jati, I Wayan Warmada

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Klaten Indonesian natural zeolite can be used as powder or pellet adsorbent. Pellet adsorbent has been made from activated natural zeolite powder by a conventional pressing method. Starch and formaldehyde were added as binder to strengthen the construction of zeolite pellet. To increase the absorptivity and its capacity, natural zeolite was activated first chemically and thermally. This research examined adsorption process of water from Isopropyl Alcohol (IPA)-water system using zeolite adsorbent pellet from natural zeolite powder which has been activated with H2SO4 0.1 M and 0.3 M. Adsorbent was pelleted by pressing apparatus at certain pressure to make specification in 1.96 cm diameter, 0.68 cm thickness which the natural zeolite powder (-80 mesh). The system of isopropyl-alcohol water contained 80% isopropyl-alcohol. Adsorption process was held in close-loop continuous apparatus which the zeolite pellet was put inside a column and the solution of IPA-water was circulated at certain flow. Concentration changing was examined thoroughly at a certain time. This adsorption process included mass transfer from bulk liquid into film layer and from film layer into the solid particle. Analysis of rate constant was using first order isotherm model that simulated with MATLAB. Besides using first order isotherm, intra-particle diffusion model was proposed by using pore diffusion model. The study shows that adsorbent activated by H2SO4 0.1 M has good absorptivity with mass transfer constant at 0.1286 min-1.

Keywords: intra-particle diffusion, fractional attainment, first order isotherm, zeolite

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Authors: Yufeng Li, Yinan Ma, Jing Wu, Chengnian Long

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Infrared object detection aims at separating small and dim target from clutter background and its capabilities extend beyond the limits of visible light, making it invaluable in a wide range of applications such as improving safety, security, efficiency, and functionality. However, existing methods are usually sensitive to the noise of the input infrared image, leading to a decrease in target detection accuracy and an increase in the false alarm rate in high-noise environments. To address this issue, an infrared small target detection algorithm called YOLO-IR is proposed in this paper to improve the robustness to high infrared noise. To address the problem that high noise significantly reduces the clarity and reliability of target features in infrared images, we design a soft-threshold coordinate attention mechanism to improve the model’s ability to extract target features and its robustness to noise. Since the noise may overwhelm the local details of the target, resulting in the loss of small target features during depth down-sampling, we propose a deep and shallow feature fusion neck to improve the detection accuracy. In addition, because the generalized Intersection over Union (IoU)-based loss functions may be sensitive to noise and lead to unstable training in high-noise environments, we introduce a Wasserstein-distance based loss function to improve the training of the model. The experimental results show that YOLO-IR achieves a 5.0% improvement in recall and a 6.6% improvement in F1-score over existing state-of-art model.

Keywords: infrared small target detection, high noise, robustness, soft-threshold coordinate attention, feature fusion

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Authors: Pakhapoom Sarapat, James M. Hill, Duangkamon Baowan

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Carbon nanotori provide several properties such as high tensile strength and heat resistance. They are promised to be ideal structures for encapsulation, and their encapsulation ability can be determined by the interaction energy between the carbon nanotori and the encapsulated nanostructures. Such interaction energy is evaluated using Lennard-Jones potential and continuum approximation. Here, four problems relating to toroidal molecules are determined in order to find the most stable configuration. Firstly, the interaction energy between a carbon nanotorus and an atom is examined. The second problem relates to the energy of a fullerene encapsulated inside a carbon nanotorus. Next, the interaction energy between two symmetrically situated and parallel nanotori is considered. Finally, the classical mechanics is applied to model the interaction energy between the toroidal structure of cyclodextrin and the spherical DNA molecules. These mathematical models might be exploited to study a number of promising devices for future developments in bio and nanotechnology.

Keywords: carbon nanotori, continuum approximation, interaction energy, Lennard-Jones potential, nanotechnology

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Authors: Sonia Ben Hamza, Sabra Habli, Nejla Mahjoub Said, Hervé Bournot, Georges Le Palec

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The distribution characteristics of pollutants released at different vertical inlet positions of an open channel are investigated with a three-dimensional numerical model. Pollutants are injected from time-dependent sources in a turbulent free surface flow. Numerical computations were carried out using ANSYS Fluent which is based on the finite volume approach. The air/water interface was modeled with the volume of the fluid method (VOF). By focusing on investigating the influences of flow on pollutants, it is found that pollutant released from the bottom position of the channel takes more time to disperse in the longitudinal direction of the flow in comparison with the case of pollutant released near the free surface. On the other hand, the pollutant released from the bottom position generates a vertical dispersion with decreased amplitude. These findings may assist in cost-effective scientific countermeasures to be taken for accident or planned pollutant discharged into a river.

Keywords: numerical simulation, pollutant release, turbulent free surface flow, VOF model

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Authors: Fadi Al Khatib, Raouf Mbarki, Malek Adouni

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In various sport and recreational activities, the patellofemoral joint undergoes large forces and moments while accommodating the significant knee joint movement. In doing so, this joint is commonly the source of anterior knee pain related to instability in normal patellar tracking and excessive pressure syndrome. One well-observed explanation of the instability of the normal patellar tracking is the patellofemoral ligaments and patellar tendon damage. Improved knowledge of the damage mechanism mediating ligaments and tendon injuries can be a great help not only in rehabilitation and prevention procedures but also in the design of better reconstruction systems in the management of knee joint disorders. This damage mechanism, specifically due to excessive mechanical loading, has been linked to the micro level of the fibred structure precisely to the tropocollagen molecules and their connection density. We argue defining a clear frame starting from the bottom (micro level) to up (macro level) in the hierarchies of the soft tissue may elucidate the essential underpinning on the state of the ligaments damage. To do so, in this study a multiscale fibril reinforced hyper elastoplastic Finite Element model that accounts for the synergy between molecular and continuum syntheses was developed to determine the short-term stresses/strains patellofemoral ligaments and tendon response. The plasticity of the proposed model is associated only with the uniaxial deformation of the collagen fibril. The yield strength of the fibril is a function of the cross-link density between tropocollagen molecules, defined here by a density function. This function obtained through a Coarse-graining procedure linking nanoscale collagen features and the tissue level materials properties using molecular dynamics simulations. The hierarchies of the soft tissues were implemented using the rule of mixtures. Thereafter, the model was calibrated using a statistical calibration procedure. The model then implemented into a real structure of patellofemoral ligaments and patellar tendon (OpenKnee) and simulated under realistic loading conditions. With the calibrated material parameters the calculated axial stress lies well with the experimental measurement with a coefficient of determination (R2) equal to 0.91 and 0.92 for the patellofemoral ligaments and the patellar tendon respectively. The ‘best’ prediction of the yielding strength and strain as compared with the reported experimental data yielded when the cross-link density between the tropocollagen molecule of the fibril equal to 5.5 ± 0.5 (patellofemoral ligaments) and 12 (patellar tendon). Damage initiation of the patellofemoral ligaments was located at the femoral insertions while the damage of the patellar tendon happened in the middle of the structure. These predicted finding showed a meaningful correlation between the cross-link density of the tropocollagen molecules and the stiffness of the connective tissues of the extensor mechanism. Also, damage initiation and propagation were documented with this model, which were in satisfactory agreement with earlier observation. To the best of our knowledge, this is the first attempt to model ligaments from the bottom up, predicted depending to the tropocollagen cross-link density. This approach appears more meaningful towards a realistic simulation of a damaging process or repair attempt compared with certain published studies.

Keywords: tropocollagen, multiscale model, fibrils, knee ligaments

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Authors: Fabienne Fel, Eric Griette

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Reshoring, whether concerning back-reshoring or near-reshoring, is a quite recent phenomenon. Despite the economic and political interest of this topic, academic research questioning determinants of reshoring remains rare. Our paper aims at contributing to fill this gap. In order to better understand the reasons for reshoring, we conducted a study among 280 French firms during spring 2016, three-quarters of which sourced, or source, in China. 105 firms in the sample have reshored all or part of their Chinese production or supply in recent years, and we aimed to establish a typology of the motives that drove them to this decision. We asked our respondents about the history of their Chinese supplies, their current reshoring strategies, and their motivations. Statistical analysis was performed with SPSS 22 and SPAD 8. Our results show that change in commercial and financial terms with China is the first motive explaining the current reshoring movement from this country (it applies to 54% of our respondents). A change in corporate strategy is the second motive (30% of our respondents); the reshoring decision follows a change in companies’ strategies (upgrading, implementation of a CSR policy, or a 'lean management' strategy). The third motive (14% of our sample) is a mere correction of the initial offshoring decision, considered as a mistake (under-estimation of hidden costs, non-quality and non-responsiveness problems). Some authors emphasize that developing a short supply chain, involving geographic proximity between design and production, gives a competitive advantage to companies wishing to offer innovative products. Admittedly 40% of our respondents indicate that this motive could have played a part in their decision to reshore, but this reason was not enough for any of them and is not an intrinsic motive leading to leaving Chinese suppliers. Having questioned our respondents about the importance given to various problems leading them to reshore, we then performed a Principal Components Analysis (PCA), associated with an Ascending Hierarchical Classification (AHC), based on Ward criterion, so as to point out more specific motivations. Three main classes of companies should be distinguished: -The 'Cost Killers' (23% of the sample), which reshore their supplies from China only because of higher procurement costs and so as to find lower costs elsewhere. -The 'Realists' (50% of the sample), giving equal weight or importance to increasing procurement costs in China and to the quality of their supplies (to a large extend). Companies being part of this class tend to take advantage of this changing environment to change their procurement strategy, seeking suppliers offering better quality and responsiveness. - The 'Voluntarists' (26% of the sample), which choose to reshore their Chinese supplies regardless of higher Chinese costs, to obtain better quality and greater responsiveness. We emphasize that if the main driver for reshoring from China is indeed higher local costs, it is should not be regarded as an exclusive motivation; 77% of the companies in the sample, are also seeking, sometimes exclusively, more reactive suppliers, liable to quality, respect for the environment and intellectual property.

Keywords: China, procurement, reshoring, strategy, supplies

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Authors: Bhavna Malik

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The study is build on a theoretical framework that links characteristics of job, key attitudes and intention to leave, why faculty may be disengaging from institutional service. The literature indicates that job characteristics, key attitudes and intention to leave are very important for effective organizational functioning. In general, the literature showed that some job characteristics might be the antecedents of job satisfaction and the aggregate variable job scope was positively associated with organizational commitment, and these key attitudes predicted intention to leave negatively. The present study attempted to propose a new integrative model of the relationships among job characteristics, key attitudes, and intention to leave. The main purpose of the present study is to examine the effects of job characteristics on intention to leave. While examining the role of job characteristics, the mediating roles of key attitudes were taken into account in order to better understand how job characteristics affect the exhibition of intention to leave. The secondary purpose is to investigate the effects of job characteristics on key attitudes, and the effects of key attitudes on intention to leave. Job characteristics of remuneration, resource for professional activities, career opportunities were positively associated with the work attitude of job satisfaction. The aggregate job scope was positively associated with the work attitude of organizational commitment although no single job characteristic was significantly associated with organizational commitment. Commitment, however, did not significantly affect time spent on institutional service. Two job characteristics—time spent on research and time spent on teaching—were negatively associated with this behavior. In general, the literature showed that some job characteristics might be the antecedents of job satisfaction and the aggregate variable job scope was positively associated with organizational commitment, and these key attiudes predicted intention to leave negatively. In turn, job satisfaction and organizational commitment were negatively associated with the intention to leave. In addition to these, organizational commitment was negatively associated with the intention to leave. However, no significant direct association was found between job characteristics and intention to leave.

Keywords: Job Characteristics Model, job satisfaction, organizational commitment, intention to leave

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Authors: Praveen Chandramenon, Andrew Gascoyne, Fideline Tchuenbou-Magaia

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Aquaponics offers a simple conclusive solution to the food and environmental crisis of the world. This approach combines the idea of Aquaculture (growing fish) to Hydroponics (growing vegetables and plants in a soilless method). Smart Aquaponics explores the use of smart technology including artificial intelligence and IoT, to assist farmers with better decision making and online monitoring and control of the system. Identification of different growth stages of Swiss Chard plants and predicting its harvest time is found to be important in Aquaponic yield management. This paper brings out the comparative analysis of a standard Aquaponics with a Vermiponics (Aquaponics with worms), which was grown in the controlled environment, by implementing IoT and deep learning-based growth stage segregation and harvest time prediction of Swiss Chards before and after applying an optimal freshwater replenishment. Data collection, Growth stage classification and Harvest Time prediction has been performed with and without water replenishment. The paper discusses the experimental design, IoT and sensor communication with architecture, data collection process, image segmentation, various regression and classification models and error estimation used in the project. The paper concludes with the results comparison, including best models that performs growth stage segregation and harvest time prediction of the Aquaponic and Vermiponic testbed with and without freshwater replenishment.

Keywords: aquaponics, deep learning, internet of things, vermiponics

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Authors: José Leandro Melgar Néris, Claudinéia Brazil, Luciane Teresa Salvi, Isabel Cristina Damin

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The impact the climate change is not recent, the main variable in the hydrological cycle is the sequence and shortage of a drought, which has a significant impact on the socioeconomic, agricultural and environmental spheres. This study aims to characterize and quantify, based on precipitation climatic projections, the rainy and dry events in the region of the Uruguay River Basin, through the Standardized Precipitation Index (SPI). The database is the image that is part of the Intercomparison of Model Models, Phase 5 (CMIP5), which provides condition prediction models, organized according to the Representative Routes of Concentration (CPR). Compared to the normal set of climates in the Uruguay River Watershed through precipitation projections, seasonal precipitation increases for all proposed scenarios, with a low climate trend. From the data of this research, the idea is that this article can be used to support research and the responsible bodies can use it as a subsidy for mitigation measures in other hydrographic basins.

Keywords: climate change, climatic model, dry events, precipitation projections

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Authors: Damien Kunjal, Faeezah Peerbhai

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Despite the increasing popularity of exchange-traded funds (ETFs), ETF investment choices may not always be rational. Excess trading volume, misevaluations of securities, and excess return volatility present in financial markets can be attributed to the influence of the overconfidence bias. Whilst previous research has explored the overconfidence bias in stock markets; this study focuses on trading in ETF markets. Therefore, the objective of this study is to investigate the presence of investor overconfidence in the South African ETF market. Using vector autoregressive models, the lead-lag relationship between market turnover and the market return is examined for the market of South African ETFs tracking domestic benchmarks and for the market of South African ETFs tracking international benchmarks over the period November 2000 till August 2019. Consistent with the overconfidence hypothesis, a positive relationship between current market turnover and lagged market return is found for both markets, even after controlling for market volatility and cross-sectional dispersion. This relationship holds for both market and individual ETF turnover suggesting that investors are overconfident when trading in South African ETFs tracking domestic benchmarks and South African ETFs tracking international benchmarks since trading activity depends on past market returns. Additionally, using the global recession as a structural break, this study finds that investor overconfidence is more pronounced after the global recession suggesting that investors perceive ETFs as risk-reducing assets due to their diversification benefits. Overall, the results of this study indicate that the overconfidence bias has a significant influence on ETF investment choices, therefore, suggesting that the South African ETF market is inefficient since investors’ decisions are based on their biases. As a result, the effect of investor overconfidence can account for the difference between the fair value of ETFs and its current market price. This finding has implications for policymakers whose responsibility is to promote the efficiency of the South African ETF market as well as ETF investors and traders who trade in the South African ETF market.

Keywords: exchange-traded fund, market return, market turnover, overconfidence, trading activity

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Authors: Sidique Gawusu, Xiaobing Zhang

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Turbulence models play a significant role in all computational fluid dynamics based modelling approaches. There is, however, no general turbulence model suitable for all flow scenarios. Therefore, a successful numerical modelling approach is only achievable if a more appropriate closure model is used. This paper evaluates different turbulence models in numerical modelling of oil-water flow within the Eulerian-Eulerian approach. A comparison among the obtained numerical results and published benchmark data showed reasonable agreement. The domain was meshed using structured mesh, and grid test was performed to ascertain grid independence. The evaluation of the models was made through analysis of velocity and pressure profiles across the domain. The models were tested for their suitability to accurately obtain a scalable and precise numerical experience. As a result, it is found that all the models except Standard-ω provide comparable results. The study also revealed new insights on flow in porous media, specifically oil reservoirs.

Keywords: turbulence modelling, simulation, multi-phase flows, water-flooding, heavy oil

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Authors: Anatoliy Kharkhurin

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Modifications that the prefix ‘trans-‘ refers to start within a person. This presentation focuses on the transpersonal that goes beyond the individual (trans-personal) to encompass wider aspects of humanities, specifically peak experience as a culminating stage of the creative act. It proposes a model according to which the peak experience results from a harmonious vibration of four spheres, which transcend an individual’s capacities and bring one to a qualitatively different level of experience. Each sphere represents an aspect of creative activity: superconscious, intellectual, emotive and active. Each sphere corresponds to one of four creative functions: authenticity, novelty, aesthetics, and utility, respectively. The creative act starts in the superconscious sphere: the supreme pleasure of Creation is reflected in creative pleasure, which is realized in creative will. These three instances serve as a source of force axes, which penetrate other spheres, and in place of infiltration establish restrictive, expansive, and integrative principles, respectively; the latter balances the other two and ensures a harmonious vibration within a sphere. This Hegelian-like triad is realized within each sphere in the form of creative capacities. The intellectual sphere nurtures capacities to invent and to elaborate, which are integrated by capacity to conceptualize. The emotive sphere nurtures satiation and restrictive capacities integrated by capacity to balance. The active sphere nurtures goal orientation and stabilization capacities integrated by capacity for self-expression. All four spheres vibrate within each other – the superconscious sphere being in the core of the structure followed by intellectual, emotive, and active spheres, respectively – thereby reflecting the path of creative production. If the spheres vibrate in-phase, their amplitudes amplify the creative energy; if in antiphase – the amplitudes reduce the creative energy. Thus, creative act is perceived as continuum with perfectly harmonious vibration within and between the spheres on one side and perfectly disharmonious vibration on the other.

Keywords: creativity, model, transpersonal, peak experience

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Authors: Maryam Karimi, Rouzbeh Nazari

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Introduction: Understanding thermal distribution in the micro-urban climate has now been necessary for urban planners or designers due to the impact of complex micro-scale features of Urban Heat Island (UHI) on the built environment and public health. Hence, understanding the interrelation between urban components and thermal pattern can assist planners in the proper addition of vegetation to build-environment, which can minimize the UHI impact. To characterize the need for urban green infrastructure (UGI) through better urban planning, this study proposes the use of RayMan model to measure the impact of air quality and increased temperature based on urban morphology in the selected metropolitan cities. This project will measure the impact of build environment for urban and regional planning using human biometeorological evaluations (Tmrt). Methods: We utilized the RayMan model to estimate the Tmrt in an urban environment incorporating location and height of buildings and trees as a supplemental tool in urban planning and street design. The estimated Tmrt value will be compared with existing surface and air temperature data to find the actual temperature felt by pedestrians. Results: Our current results suggest a strong relationship between sky-view factor (SVF) and increased surface temperature in megacities based on current urban morphology. Conclusion: This study will help with Quantifying the impacts of the built environment and surface properties on surrounding temperature, identifying priority urban neighborhoods by analyzing Tmrt and air quality data at the pedestrian level, and characterizing the need for urban green infrastructure cooling potential.

Keywords: built environment, urban planning, urban cooling, extreme heat

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Authors: Shayan Mohajer Hamidi

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Federated Learning (FL) has emerged as a promising paradigm for training machine learning models on distributed data without the need for centralized data aggregation. In the realm of wireless communications, FL has the potential to leverage the vast amounts of data generated by wireless devices to improve model performance and enable intelligent applications. However, the fairness aspect of FL in wireless communications remains largely unexplored. This abstract presents an idea for fair federated learning in wireless communications, addressing the challenges of imbalanced data distribution, privacy preservation, and resource allocation. Firstly, the proposed approach aims to tackle the issue of imbalanced data distribution in wireless networks. In typical FL scenarios, the distribution of data across wireless devices can be highly skewed, resulting in unfair model updates. To address this, we propose a weighted aggregation strategy that assigns higher importance to devices with fewer samples during the aggregation process. By incorporating fairness-aware weighting mechanisms, the proposed approach ensures that each participating device's contribution is proportional to its data distribution, thereby mitigating the impact of data imbalance on model performance. Secondly, privacy preservation is a critical concern in federated learning, especially in wireless communications where sensitive user data is involved. The proposed approach incorporates privacy-enhancing techniques, such as differential privacy, to protect user privacy during the model training process. By adding carefully calibrated noise to the gradient updates, the proposed approach ensures that the privacy of individual devices is preserved without compromising the overall model accuracy. Moreover, the approach considers the heterogeneity of devices in terms of computational capabilities and energy constraints, allowing devices to adaptively adjust the level of privacy preservation to strike a balance between privacy and utility. Thirdly, efficient resource allocation is crucial for federated learning in wireless communications, as devices operate under limited bandwidth, energy, and computational resources. The proposed approach leverages optimization techniques to allocate resources effectively among the participating devices, considering factors such as data quality, network conditions, and device capabilities. By intelligently distributing the computational load, communication bandwidth, and energy consumption, the proposed approach minimizes resource wastage and ensures a fair and efficient FL process in wireless networks. To evaluate the performance of the proposed fair federated learning approach, extensive simulations and experiments will be conducted. The experiments will involve a diverse set of wireless devices, ranging from smartphones to Internet of Things (IoT) devices, operating in various scenarios with different data distributions and network conditions. The evaluation metrics will include model accuracy, fairness measures, privacy preservation, and resource utilization. The expected outcomes of this research include improved model performance, fair allocation of resources, enhanced privacy preservation, and a better understanding of the challenges and solutions for fair federated learning in wireless communications. The proposed approach has the potential to revolutionize wireless communication systems by enabling intelligent applications while addressing fairness concerns and preserving user privacy.

Keywords: federated learning, wireless communications, fairness, imbalanced data, privacy preservation, resource allocation, differential privacy, optimization

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Authors: Muhammed Ashiq Villanthenkodath, Shreya Pal

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Purpose: This study scrutinizes the impact of economic globalization on ecological footprint while endogenizing economic growth and energy consumption from 1990 to 2018 in India. Design/methodology/approach: The standard unit root test has been employed for time series analysis to unveil the integration order. Then, the cointegration was confirmed using autoregressive distributed lag (ARDL) analysis. Further, the study executed the dynamic ARDL simulation model to estimate long-run and short-run results along with simulation and robotic prediction. Findings: The cointegration analysis confirms the existence of a long-run association among variables. Further, economic globalization reduces the ecological footprint in the long run. Similarly, energy consumption decreases the ecological footprint. In contrast, economic growth spurs the ecological footprint in India. Originality/value: This study contributes to the literature in many ways. First, unlike studies that employ CO2 emissions and globalization nexus, this study employs ecological footprint for measuring environmental quality; since it is the broader measure of environmental quality, it can offer a wide range of climate change mitigation policies for India. Second, the study executes a multivariate framework with updated series from 1990 to 2018 in India to explore the link between EF, economic globalization, energy consumption, and economic growth. Third, the dynamic autoregressive distributed lag (ARDL) model has been used to explore the short and long-run association between the series. Finally, to our limited knowledge, this is the first study that uses economic globalization in the EF function of India amid facing a trade-off between sustainable economic growth and the environment in the era of globalization.

Keywords: economic globalization, ecological footprint, India, dynamic ARDL simulation model

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Authors: Mohd Asrul Affendi Bin Abdullah

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Sample size calculation is especially important for zero inflated models because a large sample size is required to detect a significant effect with this model. This paper verify how to present percentage of power approximation for categorical and then extended to zero inflated models. Wald test was chosen to determine power sample size of AIDS death rate because it is frequently used due to its approachability and its natural for several major recent contribution in sample size calculation for this test. Power calculation can be conducted when covariates are used in the modeling ‘excessing zero’ data and assist categorical covariate. Analysis of AIDS death rate study is used for this paper. Aims of this study to determine the power of sample size (N = 945) categorical death rate based on parameter estimate in the simulation of the study.

Keywords: power sample size, Wald test, standardize rate, ZINBDR

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Authors: Armansyah, I. P. Almanar, M. Saiful Bahari Shaari, M. Shamil Jaffarullah

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Finite element approach have been used via three-dimensional models by using Altair Hyper Work, a commercially available software, to describe heat gradients along the welding zones (axially and coronaly) in Friction Stir Welding (FSW). Transient thermal finite element analyses are performed in AA 6061-T6 Aluminum Alloy to obtain temperature distribution in the welded aluminum plates during welding operation. Heat input from tool shoulder and tool pin are considered in the model. A moving heat source with a heat distribution simulating the heat generated by frictions between tool shoulder and work piece is used in the analysis. The developed model was then used to show the effect of various input parameters such as total rate of welding speed and rotational speed on temperature distribution in the work piece.

Keywords: Frictions Stir Welding (FSW), temperature distribution, Finite Element Method (FEM), altair hyperwork

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Authors: Md. S. Ansari, S. S. Motsa

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In this paper, an analysis has been made on the flow of non-Newtonian viscoelastic nanofluid over a linearly stretching sheet under the influence of uniform magnetic field. Heat transfer characteristics is analyzed taking into the effect of nonlinear radiation and non-uniform heat source/sink. Transport equations contain the simultaneous effects of Brownian motion and thermophoretic diffusion of nanoparticles. The relevant partial differential equations are non-dimensionalized and transformed into ordinary differential equations by using appropriate similarity transformations. The transformed, highly nonlinear, ordinary differential equations are solved by spectral local linearisation method. The numerical convergence, error and stability analysis of iteration schemes are presented. The effects of different controlling parameters, namely, radiation, space and temperature-dependent heat source/sink, Brownian motion, thermophoresis, viscoelastic, Lewis number and the magnetic force parameter on the flow field, heat transfer characteristics and nanoparticles concentration are examined. The present investigation has many industrial and engineering applications in the fields of coatings and suspensions, cooling of metallic plates, oils and grease, paper production, coal water or coal–oil slurries, heat exchangers’ technology, and materials’ processing and exploiting.

Keywords: magnetic field, nonlinear radiation, non-uniform heat source/sink, similar solution, spectral local linearisation method, Rosseland diffusion approximation

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Authors: Alaba M. Dare, Idris A. Ayinde, Adebayo M. Shittu, Sam O. Sam-Wobo

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Households' source of water is one of the core development indicators recently gaining pre-eminence in Nigeria. This study examined rural households' sources of water, Willingness to Pay (WTP) and factors influencing mean WTP. A cross-sectional survey which involved the use of questionnaire was used. A dichotomous choice (DC) with follow up was used as elicitation method. A multi-stage random sampling technique was used to select 437 rural households. Descriptive statistics and Tobit model were used for data estimation. The result revealed that about 70% fetched from unimproved water sources. Most (74.4%) respondents showed WTP for improved water sources. Age (p < 0.01), sex (p < 0.01), education (p < 0.01), occupation (p < 0.01), income (p < 0.01), price of water (P < 0.01), quantity of water (p < 0.01), household size (p < 0.01) and distance (p < 0.01) to existing water sources significantly influenced rural households' WTP for these services. The inference from this study showed that rural dweller sources of water is highly primitive and deplorable. Governments and stakeholders should prioritize the provision of rural water at an affordable price by rural dwellers.

Keywords: households, source of water, willingness to pay (WTP), tobit model

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Authors: Adil Mustafa, Ahmet Erten, Alper Kiraz, Melikhan Tanyeri

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Work presented here is based on a novel experimental technique used to hydrodynamically trap oil microdroplets inside a microfluidic chip at the junction of microchannels known as stagnation point. Hydrodynamic trapping has been recently used to trap and manipulate a number of particles starting from microbeads to DNA and single cells. Benzyl Benzoate (BB) is used as droplet material. The microdroplets are trapped individually at stagnation point and their dissolution was observed. Experiments are performed for two concentrations (10mM or 10µM) of AOT surfactant (Docusate Sodium Salt) and two flow rates for each case. Moreover, experimental data is compared with Zhang-Yang-Mao (ZYM) model which studies dissolution of liquid microdroplets in the presence of a host fluid experiencing extensional creeping flow. Industrial processes like polymer blending systems in which heat or mass transport occurs experience extensional flow and an insight into these phenomena is of significant importance to many industrial processes. The experimental technique exploited here gives an insight into the dissolution of liquid microdroplets under extensional flow regime. The comparison of our experimental results with ZYM model reveals that dissolution of microdroplets at lower surfactant concentration (10µM) fits the ZYM model at saturation concentration (Cs) value reported in literature (Cs = 15×10⁻³Kg\m³) while for higher surfactant concentration (10mM) which is also above the critical micelle concentration (CMC) of surfactant (5mM) the data fits ZYM model at (Cs = 45×10⁻³Kg\m³) which is 3X times the value reported in literature. The difference in Cs value from the literature shows enhancement in dissolution rate of sparingly soluble BB microdroplets at surfactant concentrations higher than CMC. Enhancement in the dissolution of sparingly soluble materials is of great importance in pharmaceutical industry. Enhancement in the dissolution of sparingly soluble drugs is a key research area for drug design industry. The experimental method is also advantageous because it is robust and has no mechanical contact with droplets under study are freely suspended in the fluid as compared existing methods used for testing dissolution of drugs. The experiments also give an insight into CMC measurement for surfactants.

Keywords: extensional flow, hydrodynamic trapping, Zhang-Yang-Mao, CMC

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Authors: Sawsan Eissa, Omnia Kabbany

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The coastline of Togo has been historically suffering from erosion for decades, which requires a solution to help control and reduce the erosion to allow for the development of the coastal area. A morpho-dynamic model using X-beach software was developed for the Western 14 Km of the Togolese coast. The model was coupled with the hydrodynamic module of DELFT 3D, flow, and the Wave module, SWAN. The data used as input included a recent bathymetric survey, a recent shoreline topographic survey, aerial photographs, ERA 5 water level and wave data, and recent test results of seabed samples. A number of scenarios were modeled: do nothing scenario, groynes, detached breakwaters system with different crest levels and alignments. The findings showed that groynes is not expected to be effective for protection against erosion, and that the best option is a system of detached breakwater, partially emerged-partially submerged couples with periodical maintenance.

Keywords: hydrodynamics, morphology, Togo, Delft3D, SWAN, XBeach, coastal erosion, detached breakwaters

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Authors: Khin Fai Chen, Jee-Hou Ho, Eng Hwa Yap

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An acoustic micro-energy harvester (AMEH) is developed to convert wasted acoustical energy into useful electrical energy. AMEH is mathematically modeled using lumped element modelling (LEM) and Euler-Bernoulli beam (EBB) modelling. An experiment is designed to validate the mathematical model and assess the feasibility of AMEH. Comparison of theoretical and experimental data on critical parameter value such as Mm, Cms, dm and Ceb showed the variances are within 1% to 6%, which is reasonably acceptable. Hence, AMEH mathematical model is validated. Then, AMEH undergoes bandwidth tuning for performance optimization for further experimental work. The AMEH successfully produces 0.9 V⁄(m⁄s^2) and 1.79 μW⁄(m^2⁄s^4) at 60Hz and 400kΩ resistive load which only show variances about 7% compared to theoretical data. By integrating a capacitive load of 200µF, the discharge cycle time of AMEH is 1.8s and the usable energy bandwidth is available as low as 0.25g. At 1g and 60Hz resonance frequency, the averaged power output is about 2.2mW which fulfilled a range of wireless sensors and communication peripherals power requirements. Finally, the design for AMEH is assessed, validated and deemed as a feasible design.

Keywords: piezoelectric, acoustic, energy harvester

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Authors: Zuliani Mahmood, Thirumulu Ponnuraj Kannan, Yean Yean Chan, Salahddin A. Al-Hudhairy

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Caries is the most common childhood disease which develops due to disturbances in the physiological equilibrium in the dental plaque resulting in demineralization of tooth structures. Plaque and dentine samples were collected from three different tooth surfaces representing caries progression (intact, over carious lesion and dentine) in children with early childhood caries (ECC, n=36). In caries free (CF) children, plaque samples were collected from sound tooth surfaces at baseline and after one year (n=12). The genomic DNA was extracted from all samples and subjected to 16S rRNA PCR amplification. The end products were cloned into pCR®2.1-TOPO® Vector. Five randomly selected positive clones collected from each surface were sent for sequencing. Identification of the bacterial clones was performed using BLAST against GenBank database. In the ECC group, the frequency of Lactobacillus sp. detected was significantly higher in the dentine surface (p = 0.031) than over the cavitated lesion. The highest frequency of bacteria detected in the intact surfaces was Fusobacterium nucleatum subsp. polymorphum (33.3%) while Streptococcus mutans was detected over the carious lesions and dentine surfaces at a frequency of 33.3% and 52.7% respectively. Fusobacterium nucleatum subsp. polymorphum was also found to be highest in the CF group (41.6%). Follow up at the end of one year showed that the frequency of Corynebacterium matruchotii detected was highest in those who remained caries free (16.6%), while Porphyromonas catoniae was highest in those who developed caries (25%). In conclusion, Streptococcus mutans and Porphyromonas catoniae are strongly associated with caries progression, while Lactobacillus sp. is restricted to deep carious lesions. Fusobacterium nucleatum subsp. polymorphum and Corynebacterium matruchotii may play a role in sustaining the healthy equilibrium in the dental plaque. These identified bacteria show promise as potential biomarkers in diagnosis which could help in the management of dental caries in children.

Keywords: early childhood caries, genotypic identification, oral bacteria, 16S rRNA

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