Search results for: two-phase mixture cavitation model

Authors: He Yuhai, Ahmad Ziad Bin Sulaiman

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Tongkat Ali, or Eurycoma longifolia, is a traditional Malay and Orang Asli herb used as aphrodisiac, general tonic, anti-Malaria, and anti-Pyretic. It has been recognized as a cashcrop by Malaysia due to its high value for the pharmaceutical use. In Tongkat Ali, eurycomanone, a quassinoid is usually chosen as a marker phytochemical as it is the most abundant phytochemical. In this research, ultrasound and enzyme were used to enhance the extraction of Eurycomanone from Tongkat Ali. Ultrasonic assisted extraction (USE) enhances extraction by facilitating the swelling and hydration of the plant material, enlarging the plant pores, breaking the plant cell, reducing the plant particle size and creating cavitation bubbles that enhance mass transfer in both the washing and diffusion phase of extraction. Enzyme hydrolyses the cell wall of the plant, loosening the structure of the cell wall, releasing more phytochemicals from the plant cell, enhancing the productivity of the extraction. Possible effects of ultrasound on the activity of the enzyme during the hydrolysis of the cell wall is under the investigation by this research. The extracts was analysed by high performance liquid chromatography for the yields of Eurycomanone. In this whole process, the conventional water extraction was used as a control of comparing the performance of the ultrasound and enzyme assisted extraction.

Keywords: ultrasound, enzymatic, extraction, Eurycoma longifolia

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Authors: Saif Al Ghafri, Thomas Hughes, Armand Karimi, Kumarini Seneviratne, Jordan Oakley, Michael Johns, Eric F. May

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Knowledge of the thermophysical properties of complex mixtures at extreme conditions of pressure and temperature have always been essential to the Liquefied Natural Gas (LNG) industry’s evolution because of the tremendous technical challenges present at all stages in the supply chain from production to liquefaction to transport. Each stage is designed using predictions of the mixture’s properties, such as density, viscosity, surface tension, heat capacity and phase behaviour as a function of temperature, pressure, and composition. Unfortunately, currently available models lead to equipment over-designs of 15% or more. To achieve better designs that work more effectively and/or over a wider range of conditions, new fundamental property data are essential, both to resolve discrepancies in our current predictive capabilities and to extend them to the higher-pressure conditions characteristic of many new gas fields. Furthermore, innovative experimental techniques are required to measure different thermophysical properties at high pressures and over a wide range of temperatures, including near the mixture’s critical points where gas and liquid become indistinguishable and most existing predictive fluid property models used breakdown. In this work, we present a wide range of experimental measurements made for different binary and ternary mixtures relevant to LNG processing, with a particular focus on viscosity, surface tension, heat capacity, bubble-points and density. For this purpose, customized and specialized apparatus were designed and validated over the temperature range (200 to 423) K at pressures to 35 MPa. The mixtures studied were (CH4 + C3H8), (CH4 + C3H8 + CO2) and (CH4 + C3H8 + C7H16); in the last of these the heptane contents was up to 10 mol %. Viscosity was measured using a vibrating wire apparatus, while mixture densities were obtained by means of a high-pressure magnetic-suspension densimeter and an isochoric cell apparatus; the latter was also used to determine bubble-points. Surface tensions were measured using the capillary rise method in a visual cell, which also enabled the location of the mixture critical point to be determined from observations of critical opalescence. Mixture heat capacities were measured using a customised high-pressure differential scanning calorimeter (DSC). The combined standard relative uncertainties were less than 0.3% for density, 2% for viscosity, 3% for heat capacity and 3 % for surface tension. The extensive experimental data gathered in this work were compared with a variety of different advanced engineering models frequently used for predicting thermophysical properties of mixtures relevant to LNG processing. In many cases the discrepancies between the predictions of different engineering models for these mixtures was large, and the high quality data allowed erroneous but often widely-used models to be identified. The data enable the development of new or improved models, to be implemented in process simulation software, so that the fluid properties needed for equipment and process design can be predicted reliably. This in turn will enable reduced capital and operational expenditure by the LNG industry. The current work also aided the community of scientists working to advance theoretical descriptions of fluid properties by allowing to identify deficiencies in theoretical descriptions and calculations.

Keywords: LNG, thermophysical, viscosity, density, surface tension, heat capacity, bubble points, models

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Authors: Magdalena Suśniak, Joanna Karwan-Baczewska

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Microstructure and tribological properties of AlSi5Cu2 matrix composite reinforced with SiC have been studied by microscopic examination and basic tribological properties. Composite material was produced by the mechanical alloying and spark plasma sintering (SPS) technique. The mixture of AlSi5Cu2 chips with 0, 10, 15 wt. % of SiC powder were placed in 250 ml mixing jar and milled 40 hours. To prevent the extreme cold welding the 1 wt. % of stearic acid was added to the powder mixture as a process control agent. Mechanical alloying provide to obtain composites powder with uniform distribution of SiC in matrix. Composite powders were poured into a graphite and a pulsed electric current was passed through powder under vacuum to consolidate material. Processing conditions were: sintering temperature 450°C, uniaxial pressure 32MPa, time of sintering 5 minutes. After SPS process composite samples indicate higher hardness values, lower weight loss, and lower coefficient of friction as compared with the unreinforced alloy. Light microscope micrograph of the worn surfaces and wear debris revealed that in the unreinforced alloy the prominent wear mechanism was the adhesive wear. In the AlSi5Cu2/SiC composites, by increasing of SiC the wear mechanism changed from adhesive and micro-cutting to abrasive and delamination for composite with 20 SiC wt. %. In all the AlSi5Cu2/SiC composites, abrasive wear was the main wear mechanism.

Keywords: aluminum matrix composite, mechanical alloying, spark plasma sintering, AlSi5Cu2/SiC composite

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Authors: Tejush Badal, Sanaa Alwidian

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Class diagrams are useful tools within the Unified Modelling Language (UML) to model and visualize the relationships between, and properties of objects within a system. As a system evolves over time and space (e.g., products), a series of models with several commonalities and variabilities create what is known as a model family. In circumstances where there are several versions of a model, examining each model individually, becomes expensive in terms of computation resources. To avoid performing redundant operations, this paper proposes an approach for representing a family of class diagrams into Union Models to represent model families using a single generic model. The paper aims to analyze and reason about a family of class diagrams using union models as opposed to individual analysis of each member model in the family. The union algorithm provides a holistic view of the model family, where the latter cannot be otherwise obtained from an individual analysis approach, this in turn, enhances the analysis performed in terms of speeding up the time needed to analyze a family of models together as opposed to analyzing individual models, one model at a time.

Keywords: analysis, class diagram, model family, unified modeling language, union model

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Authors: Maryam I. Abdullahi, Suleiman Aliyu, Armaya'u Hamisu Bichi

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The study was conducted at the University Fish Farm, Federal University Dutsinma. The aim of the study was to determine the effects of dietary supplementation of Allium sativum and Zingiber officinale mixture on growth performance, feed utilization and survival of C. gariepinus fingerling reared in tank system. The experimental setup comprised of four treatment (4) groups labeled as T1, T2, T3 and T4, each treatment replicated 3 times with ten (10) fingerlings in each replicate respectively. Treatment 1 contained 0.5% of Zingiber officinale and 0.5% of Allium sativum (ZO-AS: 1.0%), Treatment 2 contained 0.75% Zingiber officinale, and 0.75% garlic (ZO-AS: 1.5%) while T3 contained 1% ginger and 1% Allium sativum (ZO-AS: 2.0%) respectively. The experiment lasted for twelve (12) weeks (84 days). The survival rate ranges from 90% - 100%. With a higher Final Mean Weight (893.10) and Percentage Mean Weight (942.65) as compared to the control group and others. There was no significant difference (p > 0.05) in the FMW (893.10) of the fish fed 1.5g/kg of Garlic and Ginger diets than the control (687.00). The SGR (1.20) of fish-fed Zingiber officinale and Allium sativum fortified diets shows that there is no significant difference between treatments fed 1.5g/kg Zingiber officinale and Allium sativum and the control group. Generally, there was an increased survival rate in the experimental fish-fed Zingiber officinale and Allium sativum-supplemented diets as compared to the control.

Keywords: clarias gariepinus, zingiber officinale, allium sativum, fingerlings

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Authors: Apichit Svang-Ariyaskul, Thanapat Chaireongsirikul, Pawit Tangviroon

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Distillation consumes enormous quantity of energy. This work proposed a process to recover the energy from exit streams during the distillation process of three consecutive columns. There are several novel techniques to recover the heat with the distillation system; however, a complex control system is required. This work proposed a simpler technique by exchanging the heat between streams without interrupting the internal distillation process that might cause a serious control problem. The proposed process is executed by using heat exchanger network with pinch analysis to maximize the process heat recovery. The test model is the distillation of butane, pentane, hexane, and heptanes, which is a common mixture in the petroleum refinery. This proposed process saved the energy consumption for hot and cold utilities of 29 and 27%, which is considered significant. Therefore, the recovery of heat from exit streams from distillation process is proved to be effective for energy saving.

Keywords: distillation, heat exchanger, network pinch analysis, chemical engineering

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Authors: D. Thawinkarn, S. Wongbutlee

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The Social Change Leadership model is strongly aligned with administration’s mission. This research aims to examine the elements of social change leadership, build and develop leadership for social change, and evaluate effectiveness of leadership development model for social change. The research operation has 3 phases: model studies by in-depth interviews and survey research; drafting and creating model which verified by the experts; and trial of model in schools. The results showed that administrators and teachers have the elements of leadership for social change in moderate level. These elements are ranged descending from consciousness of self, common purpose, congruence, collaboration, commitment, citizenship, and controversy with civility. Model of leadership for social change is included the principles, objectives, content, process. Workshop process: Results show that the model of leadership development for social change in administrators and teachers leads to higher score in leadership evaluation prior to administering the operation.

Keywords: leadership, social change model, organization, administrators

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Authors: A. Zonouzi, M. Auli, M. Javanmard Dakheli, M. A. Hejazi

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Microalgae are tiny photosynthetic plants. Nowadays, microalgae are being used as nutrient-dense foods and sources of fine chemicals. They have significant amounts of lipid, carotenoids, vitamins, protein, minerals, chlorophyll, and pigments. Oil extraction from algae is a hotly debated topic currently because introducing an efficient method could decrease the process cost. This can determine the sustainability of algae-based foods. Scientific research works show that solvent extraction using chloroform/methanol (2:1) mixture is one of the efficient methods for oil extraction from algal cells, but both methanol and chloroform are toxic solvents, and therefore, the extracted oil will not be suitable for food application. In this paper, the effect of two food grade solvents (hexane and hexane/ isopropanol) on oil extraction yield from microalgae Dunaliella sp. was investigated and the results were compared with chloroform/methanol (2:1) extraction yield. It was observed that the oil extraction yield using hexane, hexane/isopropanol (3:2) and chloroform/methanol (2:1) mixture were 5.4, 13.93, and 17.5 (% w/w, dry basis), respectively. The fatty acid profile derived from GC illustrated that the palmitic (36.62%), oleic (18.62%), and stearic acids (19.08%) form the main portion of fatty acid composition of microalgae Dunalliela sp. oil. It was concluded that, the addition of isopropanol as polar solvent could increase the extraction yield significantly. Isopropanol solves cell wall phospholipids and enhances the release of intercellular lipids, which improves accessing of hexane to fatty acids.

Keywords: fatty acid profile‎, microalgae‎, oil extraction‎, polar solvent‎

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Authors: A. Lakrim, D. Tahri

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This paper sets out a behavioral macro-model of a Merged PiN and Schottky (MPS) diode based on silicon carbide (SiC). This model holds good for both static and dynamic electrothermal simulations for industrial applications. Its parameters have been worked out from datasheets curves by drawing on the optimization method: Simulated Annealing (SA) for the SiC MPS diodes made available in the industry. The model also adopts the Analog Behavioral Model (ABM) of PSPICE in which it has been implemented. The thermal behavior of the devices was also taken into consideration by making use of Foster’ canonical network as figured out from electro-thermal measurement provided by the manufacturer of the device.

Keywords: SiC MPS diode, electro-thermal, SPICE model, behavioral macro-model

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Authors: Funda Kul, İsmail Gür

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Pension scheme providers have to price mortality risk by accurate mortality forecasting method. There are many mortality-forecasting methods constructed and used in literature. The Lee-Carter model is the first model to consider stochastic improvement trends in life expectancy. It is still precisely used. Mortality forecasting is done by mortality index in the Lee-Carter model. It is assumed that mortality index fits ARIMA time series model. In this paper, we propose and use dynamic normal inverse gaussian distribution to modeling mortality indes in the Lee-Carter model. Using population mortality data for Italy, France, and Turkey, the model is forecasting capability is investigated, and a comparative analysis with other models is ensured by some well-known benchmarking criterions.

Keywords: mortality, forecasting, lee-carter model, normal inverse gaussian distribution

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Authors: Piotr Fiszeder, Marcin Fałdziński, Peter Molnár

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The dynamic conditional correlation model of Engle (2002) is one of the most popular multivariate volatility models. However, this model is based solely on closing prices. It has been documented in the literature that the high and low price of the day can be used in an efficient volatility estimation. We, therefore, suggest a model which incorporates high and low prices into the dynamic conditional correlation framework. Empirical evaluation of this model is conducted on three datasets: currencies, stocks, and commodity exchange-traded funds. The utilisation of realized variances and covariances as proxies for true variances and covariances allows us to reach a strong conclusion that our model outperforms not only the standard dynamic conditional correlation model but also a competing range-based dynamic conditional correlation model.

Keywords: volatility, DCC model, high and low prices, range-based models, covariance forecasting

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Authors: C. Shih, J. R. Wang, H. C. Chang, S. W. Chen, S. C. Chiang, T. Y. Yu

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After the measurement uncertainty recapture (MUR) power uprates, Kuosheng nuclear power plant (NPP) was uprated the power from 2894 MWt to 2943 MWt. For power upgrade, several codes (e.g., TRACE, RELAP5, etc.) were applied to assess the safety of Kuosheng NPP. Hence, the main work of this research is to establish a RELAP5/MOD3.3 model of Kuosheng NPP with SNAP interface. The establishment of RELAP5/SNAP model was referred to the FSAR, training documents, and TRACE model which has been developed and verified before. After completing the model establishment, the startup test scenarios would be applied to the RELAP5/SNAP model. With comparing the startup test data and TRACE analysis results, the applicability of RELAP5/SNAP model would be assessed.

Keywords: RELAP5, TRACE, SNAP, BWR

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Authors: Hoda Ghavamipoor, S. Alireza Hashemi Golpayegani

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An approach to model the customer interaction with e-commerce websites is presented. Considering the service quality level as a predictive feature, we offer an improved method based on the Customer Behavior Model Graph (CBMG), a state-transition graph model. To derive the Quality of Service sensitive-CBMG (QoS-CBMG) model, process-mining techniques is applied to pre-processed website server logs which are categorized as ‘buy’ or ‘visit’. Experimental results on an e-commerce website data confirmed that the proposed method outperforms CBMG based method.

Keywords: customer behavior model, electronic commerce, quality of service, customer behavior model graph, process mining

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Authors: Ishit Sheth, Chandrasekhar Jinendran, Chinmaya Ranjan Sahu

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A fourteen degree of freedom (DOF) ride and handling control mathematical model is developed for a car using generalized boltzmann hamel equation which will create a basis for design of ride and handling controller. Mathematical model developed yield equations of motion for non-holonomic constrained systems in quasi-coordinates. The governing differential equation developed integrates ride and handling control of car. Model-based systems engineering approach is implemented for simulation using matlab/simulink, vehicle’s response in different DOF is examined and later validated using commercial software (ADAMS). This manuscript involves detailed derivation of full car vehicle model which provides response in longitudinal, lateral and yaw motion to demonstrate the advantages of the developed model over the existing dynamic model. The dynamic behaviour of the developed ride and handling model is simulated for different road conditions.

Keywords: Full Vehicle Model, MBSE, Non Holonomic Constraints, Boltzmann Hamel Equation

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Authors: Jolanta Tamošaitienė

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The article focuses on a developed comprehensive model to be used in an agile environment for the risk assessment and selection based on multi-attribute methods. The model is based on a multi-attribute evaluation of risk in construction, and the determination of their optimality criterion values are calculated using complex Multiple Criteria Decision-Making methods. The model may be further applied to risk assessment in an agile construction environment. The attributes of risk in a construction project are selected by applying the risk assessment condition to the construction sector, and the construction process efficiency in the construction industry accounts for the agile environment. The paper presents the comprehensive risk assessment model in an agile construction environment. It provides a background and a description of the proposed model and the developed analysis of the comprehensive risk assessment model in an agile construction environment with the criteria.

Keywords: assessment, environment, agile, model, risk

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Authors: P. G. Siddheshwar, T. N. Sakshath

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In the paper we make linear and non-linear stability analyses of Rayleigh-Bénard convection of a Newtonian nanoliquid in a rotating medium (called as Rayleigh-Bénard-Taylor convection). Rigid-rigid isothermal boundaries are considered for investigation. Khanafer-Vafai-Lightstone single phase model is used for studying instabilities in nanoliquids. Various thermophysical properties of nanoliquid are obtained using phenomenological laws and mixture theory. The eigen boundary value problem is solved for the Rayleigh number using an analytical method by considering trigonometric eigen functions. We observe that the critical nanoliquid Rayleigh number is less than that of the base liquid. Thus the onset of convection is advanced due to the addition of nanoparticles. So, increase in volume fraction leads to advanced onset and thereby increase in heat transport. The amplitudes of convective modes required for estimating the heat transport are determined analytically. The tri-modal standard Lorenz model is derived for the steady state assuming small scale convective motions. The effect of rotation on the onset of convection and on heat transport is investigated and depicted graphically. It is observed that the onset of convection is delayed due to rotation and hence leads to decrease in heat transport. Hence, rotation has a stabilizing effect on the system. This is due to the fact that the energy of the system is used to create the component V. We observe that the amount of heat transport is less in the case of rigid-rigid isothermal boundaries compared to free-free isothermal boundaries.

Keywords: nanoliquid, rigid-rigid, rotation, single phase

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Authors: Guowei Hou, Lixin Yu, Wei Zhuang, Hui Qin, Xue Yang

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Formal verification is proposed to ensure the correctness of the design and make functional verification more efficient. As cache plays a vital role in the design of System on Chip (SoC), and cache with Memory Management Unit (MMU) and cache memory unit makes the state space too large for simulation to verify, then a formal verification is presented for such system design. In the paper, a formal model checking verification flow is suggested and a new cache memory model which is called “exhaustive search model” is proposed. Instead of using large size ram to denote the whole cache memory, exhaustive search model employs just two cache blocks. For cache system contains data cache (Dcache) and instruction cache (Icache), Dcache memory model and Icache memory model are established separately using the same mechanism. At last, the novel model is employed to the verification of a cache which is module of a custom-built SoC system that has been applied in practical, and the result shows that the cache system is verified correctly using the exhaustive search model, and it makes the verification much more manageable and flexible.

Keywords: cache system, formal verification, novel model, system on chip (SoC)

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Authors: Owamah Hilary, O. C. Izinyon

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Many existing biogas kinetic models are difficult to apply to substrates they were not developed for, as they are substrate specific. Biodegradability kinetic (BIK) model and maximum biogas production potential and stability assessment (MBPPSA) model were therefore developed in this study for the anaerobic co-digestion of food waste and maize husk. Biodegradability constant (k) was estimated as 0.11d-1 using the BIK model. The results of maximum biogas production potential (A) obtained using the MBPPSA model corresponded well with the results obtained using the popular but complex modified Gompertz model for digesters B-1, B-2, B-3, B-4, and B-5. The (If) value of MBPPSA model also showed that digesters B-3, B-4, and B-5 were stable, while B-1 and B-2 were unstable. Similar stability observation was also obtained using the modified Gompertz model. The MBPPSA model can therefore be used as alternative model for anaerobic digestion feasibility studies and plant design.

Keywords: biogas, inoculum, model development, stability assessment

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Authors: Yahaya Tajudeen, Joy Okpuzor, Tolu Ajayi

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The cell-rebuilding efficacy of four food plants eating as vegetables and spices in Nigeria was assessed in the lungs of wild rats (Rattus rattus) living in a polluted environment. The plants are roselle (Hibiscus sabdarrifa), moringa (Moringa oleifera), ginger (Zingiber officinale) and ugwu (Telfairia occidentalis). Sixty rats were caught from the vicinity of a cement factory in Sagamu, Southwestern-Nigeria and grouped into 6. The control group was administered distilled water, while the test groups were given ethanolic extracts of roselle, moringa, ginger, ugwu and the mixture of the extracts for 180 days. The histopathology of the rats was conducted before and at the end of 180 days extracts administration. Before administering the extracts, the lungs of the rats showed vascular congestion, severe fibrosis and congested alveolus; all which were also observed in the lungs of control rats at the end of the treatment. However, the lungs of rats that were treated with the extracts of the plants showed moderate, mild or no histological damage compared to the control rats. The extract of the mixture of the plants performed best, followed by ginger, ugwu and roselle, respectively. These findings suggest that the food plants contain phytonutrients and phytochemicals, which repaired damaged cells and tissues in the exposed rats. Consequently, the plants could play a role in ameliorating health effects of environmental pollution.

Keywords: food plants, wild rats, lung, histopathology, fibrosis, cell-rebuilding

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Authors: Chui Ka Shing

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This case study research attempts to examine the use of the Bar Model Method approach in learning and teaching mathematics in a primary school in Hong Kong. The objectives of the study are to find out to what extent (a) the Bar Model Method approach enhances the construction of students’ mathematics concepts, and (b) the school-based mathematics curriculum development with adopting the Bar Model Method approach. This case study illuminates the effectiveness of using the Bar Model Method to solve mathematics problems from Primary 1 to Primary 6. Some effective pedagogies and assessments were developed to strengthen the use of the Bar Model Method across year levels. Suggestions including school-based curriculum development for using Bar Model Method and further study were discussed.

Keywords: bar model method, curriculum development, mathematics education, problem solving

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Authors: M. A. C. S. Sampath Fernando, James M. Curran, Renate Meyer

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Model assessment, in the Bayesian context, involves evaluation of the goodness-of-fit and the comparison of several alternative candidate models for predictive accuracy and improvements. In posterior predictive checks, the data simulated under the fitted model is compared with the actual data. Predictive model accuracy is estimated using information criteria such as the Akaike information criterion (AIC), the Bayesian information criterion (BIC), the Deviance information criterion (DIC), and the Watanabe-Akaike information criterion (WAIC). The goal of an information criterion is to obtain an unbiased measure of out-of-sample prediction error. Since posterior checks use the data twice; once for model estimation and once for testing, a bias correction which penalises the model complexity is incorporated in these criteria. Cross-validation (CV) is another method used for examining out-of-sample prediction accuracy. Leave-one-out cross-validation (LOO-CV) is the most computationally expensive variant among the other CV methods, as it fits as many models as the number of observations. Importance sampling (IS), truncated importance sampling (TIS) and Pareto-smoothed importance sampling (PSIS) are generally used as approximations to the exact LOO-CV and utilise the existing MCMC results avoiding expensive computational issues. The reciprocals of the predictive densities calculated over posterior draws for each observation are treated as the raw importance weights. These are in turn used to calculate the approximate LOO-CV of the observation as a weighted average of posterior densities. In IS-LOO, the raw weights are directly used. In contrast, the larger weights are replaced by their modified truncated weights in calculating TIS-LOO and PSIS-LOO. Although, information criteria and LOO-CV are unable to reflect the goodness-of-fit in absolute sense, the differences can be used to measure the relative performance of the models of interest. However, the use of these measures is only valid under specific circumstances. This study has developed 11 models using normal, log-normal, gamma, and student’s t distributions to improve the PCR stutter prediction with forensic data. These models are comprised of four with profile-wide variances, four with locus specific variances, and three which are two-component mixture models. The mean stutter ratio in each model is modeled as a locus specific simple linear regression against a feature of the alleles under study known as the longest uninterrupted sequence (LUS). The use of AIC, BIC, DIC, and WAIC in model comparison has some practical limitations. Even though, IS-LOO, TIS-LOO, and PSIS-LOO are considered to be approximations of the exact LOO-CV, the study observed some drastic deviations in the results. However, there are some interesting relationships among the logarithms of pointwise predictive densities (lppd) calculated under WAIC and the LOO approximation methods. The estimated overall lppd is a relative measure that reflects the overall goodness-of-fit of the model. Parallel log-likelihood profiles for the models conditional on equal posterior variances in lppds were observed. This study illustrates the limitations of the information criteria in practical model comparison problems. In addition, the relationships among LOO-CV approximation methods and WAIC with their limitations are discussed. Finally, useful recommendations that may help in practical model comparisons with these methods are provided.

Keywords: cross-validation, importance sampling, information criteria, predictive accuracy

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Authors: Irtaza M. Syed, Kaamran Raahemifar

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This paper presents modeling of a Alternating Current (AC) Photovoltaic (PV) module using Matlab/Simulink. The proposed AC-PV module model is simple, realistic, and application oriented. The model is derived on module level as compared to cell level directly from the information provided by the manufacturer data sheet. DC-PV module, MPPT control, BC, VSI and LC filter, all were treated as a single unit. The model accounts for changes in variations of both irradiance and temperature. The AC-PV module proposed model is simulated and the results are compared with the datasheet projected numbers to validate model’s accuracy and effectiveness. Implementation and results demonstrate simplicity and accuracy, as well as reliability of the model.

Keywords: PV modeling, AC PV Module, datasheet, VI curves irradiance, temperature, MPPT, Matlab/Simulink

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Authors: Shelin Jin, Jin Huang, Shiqin Cao, Qiuzhen Jia, Bo Zhang, Zhenyu Sun

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Stripe rust and leaf rust, caused by Puccinia striiformis f.sp. tritici and Puccinia recondita f.sp. tritici are two of the most damaging diseases of wheat in China. In recent years, leaf rust has migrated to some wheat growing areas previously suitable for stripe rust, resulting in a mixture of the two diseases occurring in the same area and at the same time, and seriously damage wheat production in China, Gansu Province. The most effective method of prevention those two diseases are through the use of resistant cultivars. However, many studies have only carried out of resistance of wheat varieties for a single disease; resistance to both diseases is unknown. In order to definite the resistance composition of wheat varieties to these two diseases, 715 wheat varieties/lines from 8 breeding units in Gansu province were collected to test for the resistance to stripe rust and leaf rust at seedling stage in greenhouse and at adult plant stage in field in 2016-2018, respectively. Spore suspensions with the fresh mixture races of CYR32, CYR33, and CYR34 of Puccinia striiformis f.sp. tritici and mixture races of THTP, THTT, TKTT, and THTS of Puccinia recondita f.sp. tritici were used for inoculation separately. The result shows that only 4.74% of the varieties/lines show comprehensive resistance to strip rust and leaf rust at all growth stages, and there are 34 wheat varieties/lines including Tianxuan 67, 2006-1-4-1-4-2-7-2-3-10, 03-139-1-2-2-1-2-1, Qingnong 21, Lenghan 5, 04-203-1-1-1 and so on. In seedling stage, the frequencies of resistant varieties/lines to wheat strip rust and leaf rust were 56.64% and 30.23%. While the materials were susceptible to these diseases were 43.36% and 69.77%. 71 varieties/lines were resistant to those two diseases, accounted for 9.93%. 10 varieties/lines, accounted for 1.4%, were highly resistant (including immune/near immune) to those two diseases. In adult-plant stage, the frequencies of resistant varieties/lines to wheat strip rust and leaf rust were 76.53% and 36.11%. While the materials were susceptible to these diseases were 23.47% and 63.89%. 137 varieties/lines were resistant to those two diseases, accounted for 19.16%. 59 varieties/lines, accounted for 8.25%, were highly resistant (including immune/near immune) to those two diseases. Overall, the 715 varieties /lines had high resistance to wheat strip rust, but poor resistance to leaf rust. This study found out some resistant materials which had better comprehensive resistance to leaf rust and strip rust, also pointed out the resistance characteristics of 715 varieties/lines to those two diseases at the seedling stage and adult-plant stage, which will be of great guiding significance in wheat resistance breeding and comprehensive control those two diseases in China, Gansu Province in the future.

Keywords: Puccinia striiformis f.sp. tritici, Puccinia recondita f.sp. tritici, resistance of variety, wheat

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Authors: Rizwan Latif, Syed Adnan Qasim, Muzaffar Ali

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Fuel direct injection represents one of the key aspects in the development of the diesel engines, the idea of controlling the auto-ignition and the consequent combustion of a liquid spray injected in a reacting atmosphere during a time scale of few milliseconds has been a challenging task for the engine community and pushed forward to a massive research in this field. The quality of the air-fuel mixture defines the combustion efficiency, and therefore the engine efficiency. A droplet interaction in dense as well as thin portion of the spray receives equal importance as other parameters in spray structure. Usually, these are modeled along with breakup process and analyzed alike. In this paper, droplet interaction is modeled and simulated for high torque low speed scenario. Droplet interactions may further be subdivided into droplet collision and coalescence, spray wall impingement, droplets drag, etc. Droplet collisions may occur in almost all spray applications, but especially in diesel like conditions such as high pressure sprays as utilized in combustion engines. These collisions have a strong influence on the mean droplet size and its spatial distribution and can, therefore, affect sub-processes of spray combustion such as mass, momentum and energy transfer between gas and droplets. Similarly, for high-pressure injection systems spray wall impingement is an inherent sub-process of mixture formation. However, its influence on combustion is in-explicit.

Keywords: droplet collision, coalescence, low speed, diesel fuel

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Authors: Pham Van Nha, Le Cam Binh

Abstract:

Particle swarm optimization (PSO) is a population-based stochastic optimization algorithm. PSO was inspired by the natural behavior of birds and fish in migration and foraging for food. PSO is considered as a multidisciplinary optimization model that can be applied in various optimization problems. PSO’s ideas are simple and easy to understand but PSO is only applied in simple model problems. We think that in order to expand the applicability of PSO in complex problems, PSO should be described more explicitly in the form of a mathematical model. In this paper, we represent PSO in a mathematical model and apply in the multivariate data classification. First, PSOs general mathematical model (MPSO) is analyzed as a universal optimization model. Then, Model of Optimal Centroids (MOC) is proposed for the multivariate data classification. Experiments were conducted on some benchmark data sets to prove the effectiveness of MOC compared with several proposed schemes.

Keywords: analysis of optimization, artificial intelligence based optimization, optimization for learning and data analysis, global optimization

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Authors: Anmar Dulaimi, Hassan Al Nageim, Felicite Ruddock, Linda Seton

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Cold bituminous asphalt mixture (CBEM) provide a sustainable, cost effective and energy efficiency alternative to traditional hot mixtures. However, these mixtures have a comparatively low initial strength and as it is considered as evolutionary materials, mainly in the early life where the initial cohesion is low and builds up slowly. On the other hand, asphalt concrete is, by far, the most common mixtures in use as binder course and base in road pavement in the UK having a continuous grade offer a good aggregate interlock results in this material having very good load-spreading properties as well as a high resistance to permanent deformation. This study aims at developing a novel fast curing cold asphalt concrete binder course mixtures by using Ordinary Portland Cement (OPC) as a replacement to conventional mineral filler (0%-100%) while new by-product material (LJMU-A2) was used as a supplementary cementitious material. With this purpose, cold asphalt concrete binder course mixtures with cationic emulsions were studied by means of stiffness modulus whereas water sensitivity was approved by assessing the stiffness modulus ratio before and after sample conditioning. The results indicate that a substantial enhancement in the stiffness modulus and a considerable improvement of water sensitivity resistance by adding of LJMU-A2 to the cold asphalt mixtures as a supplementary cementitious material. Moreover, the addition of LJMU-A2 to those mixtures leads to stiffness modulus after 2- day curing comparable to those obtained with Portland cement after 7-day curing.

Keywords: cold mix asphalt, binder course, cement, stiffness modulus, water sensitivity

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Authors: Catherine Maware, Olufemi Adetunji

Abstract:

The paper is aimed at developing a model to measure the impact of Lean manufacturing deployment on organizational performance. The model will help industry practitioners to assess the impact of implementing Lean constructs on organizational performance. It will also harmonize the measurement models of Lean performance with the house of Lean that seems to have become the industry standard. The sheer number of measurement models for impact assessment of Lean implementation makes it difficult for new adopters to select an appropriate assessment model or deployment methodology. A literature review is conducted to classify the Lean performance model. Pareto analysis is used to select the Lean constructs for the development of the model. The model is further formalized through the use of Structural Equation Modeling (SEM) in defining the underlying latent structure of a Lean system. An impact assessment measurement model developed can be used to measure Lean performance and can be adopted by different industries.

Keywords: impact measurement model, lean bundles, lean manufacturing, organizational performance

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Authors: Shreya Srivastava, Sagnik Dey

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Aerosol direct radiative forcing (ADRF) refers to the alteration of the Earth's energy balance from the scattering and absorption of solar radiation by aerosol particles. India experiences substantial ADRF due to high aerosol loading from various sources. These aerosols' radiative impact depends on their physical characteristics (such as size, shape, and composition) and atmospheric distribution. Quantifying ADRF is crucial for understanding aerosols’ impact on the regional climate and the Earth's radiative budget. In this study, we have taken radiation data from Clouds and the Earth’s Radiant Energy System (CERES, spatial resolution=1ox1o) for 22 years (2000-2021) over the Indian subcontinent. Except for a few locations, the short-wave DARF exhibits aerosol cooling at the TOA (values ranging from +2.5 W/m2 to -22.5W/m2). Cooling due to aerosols is more pronounced in the absence of clouds. Being an aerosol hotspot, higher negative ADRF is observed over the Indo-Gangetic Plain (IGP). Aerosol Forcing Efficiency (AFE) shows a decreasing seasonal trend in winter (DJF) over the entire study region while an increasing trend over IGP and western south India during the post-monsoon season (SON) in clear-sky conditions. Analysing atmospheric heating and AOD trends, we found that only the aerosol loading is not governing the change in atmospheric heating but also the aerosol composition and/or their vertical profile. We used a Multi-angle Imaging Spectro-Radiometer (MISR) Level-2 Version 23 aerosol products to look into aerosol composition. MISR incorporates 74 aerosol mixtures in its retrieval algorithm based on size, shape, and absorbing properties. This aerosol mixture information was used for analysing long-term changes in aerosol composition and dominating aerosol species corresponding to the aerosol forcing value. Further, ADRF derived from this method is compared with around 35 studies across India, where a plane parallel Radiative transfer model was used, and the model inputs were taken from the OPAC (Optical Properties of Aerosols and Clouds) utilizing only limited aerosol parameter measurements. The result shows a large overestimation of TOA warming by the latter (i.e., Model-based method).

Keywords: aerosol radiative forcing (ARF), aerosol composition, MISR, CERES, SBDART

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Authors: Beata Kaczmarek-Szczepańska, Lidia Zasada

Abstract:

Marine collagens such as fish skin, bone, cartilage, and scales, including both marine vertebrates and invertebrates sources, are more bioavailable compared to bovine or porcine collagen and have a higher absorption capability and more rapid bloodstream circulation due to their low molecular weight and small particle size. Fish skin may be used as a source of bioactive compounds. The advantage is that fish skin is a by-product of the food industry. The subject of the study is a lyophilizate consisting of a mixture of compounds from the group of glycosaminoglycans and collagen obtained as a result of processing fish skins. Bioactive compounds may find biomedical use in the production of dressing materials for wounds or in tissue engineering for the production of scaffolds for cells. Collagen and glycosaminoglycans were isolated from Salmo salar skin. The final mixture was obtained by the freeze-drying method. In the obtained lyophilizate, the content of amino acids was studied as well as the presence of polysaccharides. The studies showed the presence of glycine, proline, and hydroxyproline, which are the main amino acids of collagen. The HPLC analysis showed the presence of glucose which is a product of polysaccharides hydrolyzation and then reduction of glucuronic acid. It may be assumed that the lyophilizate contains both collagen and polysaccharide, which is probably hyaluronic acid. Acknowledgment: This work was carried out as a result of research project no. TANGO-V-A/0020/2021 financed by the National Centre for Research and Development.

Keywords: collagen, glycosaminoglycans, bioactive compounds, fish skin

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Authors: Shalini Menon, K. Girish Kumar

Abstract:

Norepinephrine (NE) is one of the naturally occurring catecholamines which act both as a neurotransmitter and a hormone. Catecholamine levels are used for the diagnosis and regulation of phaeochromocytoma, a neuroendocrine tumor of the adrenal medulla. The development of simple, rapid and cost-effective sensors for NE still remains a great challenge. Herein, a dual-channel sensor has been developed for the determination of NE. A mixture of AgNO₃, NaOH, NH₃.H₂O and cetrimonium bromide in appropriate concentrations was taken as the working solution. To the thoroughly vortexed mixture, an appropriate volume of NE solution was added. After a particular time, the fluorescence and absorbance were measured. Fluorescence measurements were made by exciting at a wavelength of 400 nm. A dual-channel optical sensor has been developed for the colorimetric as well as the fluorimetric determination of NE. Metal enhanced fluorescence property of nanoparticles forms the basis of the fluorimetric detection of this assay, whereas the appearance of brown color in the presence of NE leads to colorimetric detection. Wide linear ranges and sub-micromolar detection limits were obtained using both the techniques. Moreover, the colorimetric approach was applied for the determination of NE in synthetic blood serum and the results obtained were compared with the classic high-performance liquid chromatography (HPLC) method. Recoveries between 97% and 104% were obtained using the proposed method. Based on five replicate measurements, relative standard deviation (RSD) for NE determination in the examined synthetic blood serum was found to be 2.3%. This indicates the reliability of the proposed sensor for real sample analysis.

Keywords: norepinephrine, colorimetry, fluorescence, silver nanoparticles

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