Search results for: component prediction

Authors: María Isabel Núñez-Peña, Macarena Suárez Pellicioni

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In the present study, we used event-related potentials (ERP) to address the question of whether high (HMA) and low math-anxious (LMA) individuals differ on a complex addition verification task, which involved both carrying and non-carrying additions. ERPs were recorded while seventeen HMA and seventeen LMA individuals performed the verification task. Groups did not differ in trait anxiety or gender distribution. Participants were presented with two-digit additions and were asked to decide whether the proposed solution was correct or incorrect. Behavioral data showed a significant Carrying x Proposed solution x Group interaction for accuracy, showing that carrying additions were more error prone than non-carrying ones for both groups, although the difference non-carrying minus carrying was larger for the HMA group. As for ERPs, a P2 component larger in HMA individuals than in their LMA peers was found both for carrying and non-carrying additions. The P2 was followed by a sustained negative slow wave at parietal positions. Because the negative slow waves are thought to reflect the updating of working memory, these results give support to the relationship among working memory, math performance and math anxiety.

Keywords: math anxiety, carrying, working memory, P2

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Authors: Noemia Gomes de Mattos de Mesquita, José Eduardo Ferreira de Oliveira, Arimatea Quaresma Ferraz

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Stops to exchange cutting tool, to set up again the tool in a turning operation with CNC or to measure the workpiece dimensions have a direct influence on production. The premature removal of the cutting tool results in high cost of machining since the parcel relating to the cost of the cutting tool increases. On the other hand, the late exchange of cutting tool also increases the cost of production because getting parts out of the preset tolerances may require rework for its use when it does not cause bigger problems such as breaking of cutting tools or the loss of the part. Therefore, the right time to exchange the tool should be well defined when wanted to minimize production costs. When the flank wear is the limiting tool life, the time predetermination that a cutting tool must be used for the machining occurs within the limits of tolerance can be done without difficulty. This paper aims to show how the life of the cutting tool can be calculated taking into account the cutting parameters (cutting speed, feed and depth of cut), workpiece material, power of the machine, the dimensional tolerance of the part, the finishing surface, the geometry of the cutting tool and operating conditions of the machine tool, once known the parameters of Taylor algebraic structure. These parameters were raised for the ABNT 1038 steel machined with cutting tools of hard metal.

Keywords: machining, productions, cutting condition, design, manufacturing, measurement

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Authors: Felora Rafiei, Shahram Shoaei

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The aim of this studies was to evaluate effect of nitroxin, super nitro plus and biophosphorus on yield and yield components of maize (Zea mays) under different levels of chemical fertilizers in the condition of normal and difficiet irrigation. Experiment laid out as split plot factorial based on randomized complete block design with three replications. Main plots includes two irrigation treatments of 70 (I1), 120(I2) mm evaporation from class A pan. Sub plots were biological fertilizer and chemical fertilizer as factorial biological fertilizer consisting of nitroxin: Azospirillium lipoferum, Azospirillium brasilens, Azotobacter chroococcum Azotobacter agilis (108 CFU ml-1) (B1), super nitro plus (Azospirillium spp, + Pseudomonas fluorescence + Bacillus subtilis (108 CFU ml-1) + biological fungicide) (B2), biophosphorus (Pseudomonas spp + Bacillus spp (107 CFU ml-1) (B3), and chemical fertilizer consisting of NPK (C1), N5oP5oK5o (C2) and NoPoKo (C3).The results showed that usage of biological fertilizer have positive effects on chemical fertilizers use efficiency and tolerance to drought stress in maize. Also with use of biological fertilizer can decrease usage of chemical fertilizers.

Keywords: biological fertilizer, chemical fertilizer, yield component, yield, corn

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Authors: Bin Wang, Hengyu Ji, Zhifeng Ye

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Fuel Metering Unit (FMU) in fuel system of an aeroengine sometimes has direct influence on the engine performance, which is neglected for the sake of easy access to mathematical model of the engine in most cases. In order to verify the influence of FMU on an engine model, this paper presents a co-simulation of a stepping motor driven FMU (digital FMU) in a turboshaft aeroengine, using AMESim and MATLAB to obtain the steady and dynamic characteristics of the FMU. For this method, mechanical and hydraulic section of the unit is modeled through AMESim, while the stepping motor is mathematically modeled through MATLAB/Simulink. Combining these two sub-models yields an AMESim/MATLAB co-model of the FMU. A simplified component level model for the turboshaft engine is established and connected with the FMU model. Simulation results on the full model show that the engine model considering FMU characteristics describes the engine more precisely especially in its transition state. An FMU dynamics will cut down the rotation speed of the high pressure shaft and the inlet pressure of the combustor during the step response. The work in this paper reveals the impact of FMU on engine operation characteristics and provides a reference to an engine model for ground tests.

Keywords: fuel metering unit, stepping motor, AMESim/Matlab, full digital simulation

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Authors: Idris Elfeituri

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In the current study, energy and exergy analysis of a 65 MW steam power plant was carried out. This study investigated the effect of variations of overall conductance of the super heater on the performance of an existing steam power plant located in Derna, Libya. The performance of the power plant was estimated by a mathematical modelling which considers the off-design operating conditions of each component. A fully interactive computer program based on the mass, energy and exergy balance equations has been developed. The maximum exergy destruction has been found in the steam generation unit. A 50% reduction in the design value of overall conductance of the super heater has been achieved, which accordingly decreases the amount of the net electrical power that would be generated by at least 13 MW, as well as the overall plant exergy efficiency by at least 6.4%, and at the same time that would cause an increase of the total exergy destruction by at least 14 MW. The achieved results showed that the super heater design and operating conditions play an important role on the thermodynamics performance and the fuel utilization of the power plant. Moreover, these considerations are very useful in the process of the decision that should be taken at the occasions of deciding whether to replace or renovate the super heater of the power plant.

Keywords: Exergy, Super-heater, Fouling; Steam power plant; Off-design., Fouling;, Super-heater, Steam power plant

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Authors: Norsyamimi Hassim, Masturah Markom

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Supercritical fluid extraction (SFE) has been known as a sustainable and safe extraction technique for plant extraction due to the minimal usage of organic solvent. In this study, a scale-up process for the selected herbal plant (Phyllanthus niruri) was investigated by using supercritical carbon dioxide (SC-CO2) with food-grade (ethanol-water) cosolvent. The quantification of excess ethanol content in the final dry extracts was conducted to determine the safety of enriched extracts. The extraction yields obtained by scale-up SFE unit were not much different compared to the predicted extraction yields with an error of 2.92%. For component contents, the scale-up extracts showed comparable quality with laboratory-scale experiments. The final dry extract showed that the excess ethanol content was 1.56% g/g extract. The fish embryo toxicity test (FETT) on the zebrafish embryos showed no toxicity effects by the extract, where the LD50 value was found to be 505.71 µg/mL. Thus, it has been proven that SFE with food-grade cosolvent is a safe extraction technique for the production of bioactive compounds from P. niruri.

Keywords: scale-up, supercritical fluid extraction, enriched extract, toxicity, ethanol content

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Authors: Mina Adel Shokry Fahim, Jūratė Sužiedelytė Visockienė

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With the growing concern over air pollution (AP), it is clear that this has gained more prominence than ever before. The level of consciousness has increased and a sense of knowledge now has to be forwarded as a duty by those enlightened enough to disseminate it to others. This realisation often comes after an understanding of how poor air quality indices (AQI) damage human health. The study focuses on assessing air pollution prediction models specifically for Lithuania, addressing a substantial need for empirical research within the region. Concentrating on Vilnius, it specifically examines particulate matter concentrations 10 micrometers or less in diameter (PM10). Utilizing Gaussian Process Regression (GPR) and Regression Tree Ensemble, and Regression Tree methodologies, predictive forecasting models are validated and tested using hourly data from January 2020 to December 2022. The study explores the classification of AP data into anthropogenic and natural sources, the impact of AP on human health, and its connection to cardiovascular diseases. The study revealed varying levels of accuracy among the models, with GPR achieving the highest accuracy, indicated by an RMSE of 4.14 in validation and 3.89 in testing.

Keywords: air pollution, anthropogenic and natural sources, machine learning, Gaussian process regression, tree ensemble, forecasting models, particulate matter

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Authors: A. Nguyen, K. Nguyen, J. Jackson, E. Manlapig

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With the recent advancement in core imaging systems, a large volume of high resolution drill core images can now be collected rapidly. This paper presents a method for rapid prediction of ore-specific breakage parameters from high resolution mineral classified core images. The aim is to allow for a rapid assessment of the variability in ore hardness within a mineral deposit with reduced amount of physical breakage tests. This method sees its application primarily in project evaluation phase, where proper evaluation of the variability in ore hardness of the orebody normally requires prolong and costly metallurgical test work program. Applying this image-based texture analysis method on mineral classified core images, the ores are classified according to their textural characteristics. A small number of physical tests are performed to produce a dataset used for developing the relationship between texture classes and measured ore hardness. The paper also presents a case study in which this method has been applied on core samples from a copper porphyry deposit to predict the ore-specific breakage A*b parameter, obtained from JKRBT tests.

Keywords: geometallurgy, hyperspectral drill core imaging, process simulation, texture analysis

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Authors: Phil P. Wagner

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There is an overwhelming amount of athlete-centric information available for sport practitioners in this era of tech and big data, but protocols in athletic rehabilitation remain arbitrary. It is a common assumption that the rate at which tissue heals amongst individuals is the same; yielding protocols that are entirely time-based. Progressing athletes through rehab programs that lack individualization can potentially expose athletes to stimuli they are not prepared for or unnecessarily lengthen their recovery period. A 7-year aggregated and anonymous database was used to develop reliable and valid assessments to measure athletic resilience. Each assessment utilizes force plate technology with proprietary protocols and analysis to provide key thresholds for injury risk and recovery. Using a T score to analyze movement qualities, much like the Z score used for bone density from a Dexa scan, specific prescriptions are provided to mitigate the athlete’s inherent injury risk. In addition to obliging to surgical clearance, practitioners must put in place a clearance protocol guided by standardized assessments and achievement in strength thresholds. In order to truly hold individuals accountable (practitioners, athletic trainers, performance coaches, etc.), success in improving pre-defined key performance indicators must be frequently assessed and analyzed.

Keywords: analytics, athlete rehabilitation, athlete resilience, injury prediction, injury prevention

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Authors: B. Paygozar, S.A. Dizaji, A.C. Kandemir

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In this study, the effects of the modified adhesive including different concentrations of Nano-silica are surveyed on the bonding strength of the adhesive scarf joints. The nanoparticles are added in two different concentrations, to an epoxy-based two-component structural adhesive, Araldite 2011, to survey the influences of the nanoparticle weight percentage on the failure load of the joints compared to that of the joints manufactured by the neat adhesive. The effects of being exposure to a moist ambience on the joint strength are also investigated for the joints produced of both neat and modified adhesives. For this purpose, an ageing process was carried out on the joints of both neat and improved kinds with variable immersion periods (20, 40 and 60 days). All the specimens were tested under a quasi-static tensile loading of 2 mm/min speed so as to find the quantities of the failure loads. Outcomes indicate that the failure loads of the joints with modified adhesives are measurably higher than that of the joint with neat adhesive, even while being put for a while under a moist condition. Another result points out that humidity lessens the bonding strength of all the joints of both types as the exposure time increases, which can be attributed to the change in the failure mode.

Keywords: bonding strength, humidity, nano-silica, scarf joint

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Authors: Cosmin-Gabriel Porumb-Ghiurco, Dumitrana Fiț-Iordache, Szőke Árpád

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The literature incorporating geographical or tourist-geographical themes and explicit references to the Carpathian area is extremely abundant. Through this paper, we attempt to “undermine” the traditional, tourist-geographical approaches of the Carpathian Arch by targeting an aspect often regarded as marginal but which, if examined, even only empirically, takes the form of a vast problem with multidisciplinary vocation. Therefore, we propose a more extravagant yet pro-touristic approach to the Romanian Carpathian geo-space. Consequently, the explicit goal of this approach consists precisely in broadening the multidisciplinary, essentially geographic scope of the research, the vision and mental representation of the Carpathian area by advancing a lever that would symbolize a different kind of unification between geography and tourism on a more intimate, subtle, mythological and archetypal level. The spiritual and mercantile dimensions of the tourism field in general and of the local Carpathian tourism can meld harmoniously together in order to create a common territorial reality of referral and favorable perspectives for the consolidation of their symbiotic relationship.

Keywords: tourist image, mythical geography, collective imaginary, spiritual patrimony, Carpathians

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Authors: Aqsa Asharaf

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The current study aims to examine the physical characteristics of charge compact spheres employing anisotropic fluid under f(R, ϕ, X) modified gravity approach, exploring how this theoretical context influences their attributes and behavior. To accomplish our goal, we adopt the Spherically Symmetric (SS) space-time and, additionally, employ a specific Adler-based mode for the metric potential (gtt), which yields a broader class of solutions, Then, by making use of the Karmarkar condition, we successfully derive the other metric potential. A primary component of our current analysis is utilizing the Bardeen geometry as extrinsic space-time to determine the constant parameters of intrinsic space-time. Further, to validate the existence of Bardeen stellar spheres, we debate the behavior of physical properties and parameters such as components of pressure, energy density, anisotropy, parameters of EoS, stability and dynamical equilibrium, energy bounds, mass function, adiabatic index, compactness factor, and surface redshift. Conclusively, all the obtained results show that the system under consideration is physically stable, free from singularity, and viable models.

Keywords: cosmology, GR, Bardeen BH, modified gravities

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Authors: Un-Hwan Park, Jun-Hyeok Heo, In-Sung Lee, Seong-Jin Cho, Tae-Hyeon Oh, Dae-Kyu Park

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Sound absorption coefficient is considered important when designing because noise affects emotion quality of car. It is designed with lots of experiment tunings in the field because it is unreliable to predict it for multi-layer material. In this paper, we present the design of sound absorption for automotive interior material with multiple layers using estimation software of sound absorption coefficient for reverberation chamber. Additionally, we introduce the method for estimation of physical properties required to predict sound absorption coefficient of car interior materials with multiple layers too. It is calculated by inverse algorithm. It is very economical to get information about physical properties without expensive equipment. Correlation test is carried out to ensure reliability for accuracy. The data to be used for the correlation is sound absorption coefficient measured in the reverberation chamber. In this way, it is considered economical and efficient to design automotive interior materials. And design optimization for sound absorption coefficient is also easy to implement when it is designed.

Keywords: sound absorption coefficient, optimization design, inverse algorithm, automotive interior material, multiple layers nonwoven, scaled reverberation chamber, sound impedance tubes

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Authors: Kehinde Adeyeye Adelabu

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Computer applications has completely revolutionized the way of life of people which does not exclude the field of sport education. There are computer technologies which help to enhance teaching in every field of education. Invention of computers has done great to the field of education. This study was therefore carried out to examine the effects and merits of computer operations in Human Kinetics Education and Sports. The study was able to identify the component of computer, uses of computer in Human Kinetics education (sports), computer applications in some branches of human kinetics education. A qualitative research method was employed by the author in gathering experts’ views and used to analyze the effects and merits of computer applications in the field of human kinetics education. No experiment was performed in the cause of carrying out the study. The source of information for the study was text-books, journal, articles, past project reports, internet i.e. Google search engine. Computer has significantly helped to improve Education (Human Kinetic), it has complemented the basic physical fitness testing and gave a more scientific basis to the testing. The use of the software and packages has made cost projections, database applications, inventory control, management of events, word processing, electronic mailing and record keeping easier than the pasts.

Keywords: application, computer operation, education, human kinetics

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Authors: Shivani Saini

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The effect of vertical throughflow on the onset of convection in Rivlin-Ericksen Elastico-Viscous nanofluid with convective boundary condition is investigated. The flow is stimulated with modified Darcy model under the assumption that the nanoparticle volume fraction is not actively managed on the boundaries. The heat conservation equation is formulated by introducing the convective term of nanoparticle flux. A linear stability analysis based upon normal mode is performed, and an approximate solution of eigenvalue problems is obtained using the Galerkin weighted residual method. Investigation of the dependence of the Rayleigh number on various viscous and nanofluid parameter is performed. It is found that through flow and nanofluid parameters hasten the convection while capacity ratio, kinematics viscoelasticity, and Vadasz number do not govern the stationary convection. Using the convective component of nanoparticle flux, critical wave number is the function of nanofluid parameters as well as the throughflow parameter. The obtained solution provides important physical insight into the behavior of this model.

Keywords: Darcy model, nanofluid, porous layer, throughflow

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Authors: Stuti Modi, Aditi Kambli

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This paper addresses the need for intelligent water management and distribution system in smart cities to ensure optimal consumption and distribution of water for drinking and sanitation purposes. Water being a limited resource in cities require an effective system for collection, storage and distribution. In this paper, applications of two mostly widely used particular types of data-driven models, namely artificial neural networks (ANN) and fuzzy logic-based models, to modelling in the water resources management field are considered. The objective of this paper is to review the principles of various types and architectures of neural network and fuzzy adaptive systems and their applications to integrated water resources management. Final goal of the review is to expose and formulate progressive direction of their applicability and further research of the AI-related and data-driven techniques application and to demonstrate applicability of the neural networks, fuzzy systems and other machine learning techniques in the practical issues of the regional water management. Apart from this the paper will deal with water storage, using ANN to find optimum reservoir level and predicting peak daily demands.

Keywords: artificial neural networks, fuzzy systems, peak daily demand prediction, water management and distribution

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Authors: Noor Zainab Habib, Ibrahim Kamaruddin, Madzlan Napiah

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This paper present a part of research conducted to investigate the creep behavior of bituminous concrete mixture prepared with well graded using the dynamic creep test. The samples were prepared from unmodified control mix and Polypropylene modified bituminous mix. Unmodified or control mix was prepared with 80/100 grade bitumen while polypropylene modified mix was prepared using polypropylene PP polymer as modifier, blended with 80/100 Pen bitumen. The concentration of polymer in the blend was kept at 1%, 2%, and 3% by weight of bitumen content. For Dynamic Creep Test, Marshall Specimen were prepared at optimum bitumen content and then tested using IPC Global Universal Testing Machine (UTM), in order to investigate the creep stiffness of both modified and control mix. From the results obtained it was found that 1% and 2% PP modified bituminous mix offer better results in comparison to control and 3% PP modified mix samples. The results verify all the findings of empirical and viscosity test results which indicates that polymer modification induces stiffening effect in the binder. Enhanced viscous component of the binder was considered responsible for this change which eventually enhances the mechanical strength of the modified bituminous mixes.

Keywords: polymer modified bitumen, stiffness, creep, viscosity

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Authors: Masoud Ghermezi

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Studying the sheet metals is one of the most important research areas in the field of metal forming due to their extensive applications in the aerospace industries. A useful method for determining the forming limit of these materials and consequently preventing the rupture of sheet metals during the forming process is the use of the forming limit curve (FLC). In addition to specifying the forming limit, this curve also delineates a boundary for the allowed values of strain in sheet metal forming; these characteristics of the FLC along with its accuracy of computation and wide range of applications have made this curve the basis of research in the present paper. This study presents a new model that not only agrees with the results obtained from the above mentioned theory, but also eliminates its shortcomings. In this theory, like in the M-K theory, a thin sheet with an inhomogeneity as a gradient thickness reduction with a sinusoidal function has been chosen and subjected to two-dimensional stress. Through analytical evaluation, ultimately, a governing differential equation has been obtained. The numerical solution of this equation for the range of positive strains (stretched region) yields the results that agree with the results obtained from M-K theory. Also the solution of this equation for the range of negative strains (tension region) completes the FLC curve. The findings obtained by applying this equation on two alloys with the hardening exponents of 0.4 and 0.24 indicate the validity of the presented equation.

Keywords: sheet metal, metal forming, forming limit curve (FLC), M-K theory

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Authors: Karim Hamidi Machekposhti, Hossein Sedghi, Abdolrasoul Telvari, Hossein Babazadeh

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Floods have huge environmental and economic impact. Therefore, flood prediction is given a lot of attention due to its importance. This study analysed the annual maximum streamflow (discharge) (AMS or AMD) of Karkheh River in Karkheh River Basin for flood predicting using ARIMA model. For this purpose, we use the Box-Jenkins approach, which contains four-stage method model identification, parameter estimation, diagnostic checking and forecasting (predicting). The main tool used in ARIMA modelling was the SAS and SPSS software. Model identification was done by visual inspection on the ACF and PACF. SAS software computed the model parameters using the ML, CLS and ULS methods. The diagnostic checking tests, AIC criterion, RACF graph and RPACF graphs, were used for selected model verification. In this study, the best ARIMA models for Annual Maximum Discharge (AMD) time series was (4,1,1) with their AIC value of 88.87. The RACF and RPACF showed residuals’ independence. To forecast AMD for 10 future years, this model showed the ability of the model to predict floods of the river under study in the Karkheh River Basin. Model accuracy was checked by comparing the predicted and observation series by using coefficient of determination (R²).

Keywords: time series modelling, stochastic processes, ARIMA model, Karkheh river

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Authors: Geraldine Macdonald, Oliver Perra, Nina O’Neill, Laura Neeson, Kathryn Higgins

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Background: Despite improvements in recent years, almost one in six children in Northern Ireland (NI) leaves primary school without achieving the expected level in English and Maths. By early adolescence, this ratio is one in five. In 2010-11, around 9000 pupils in NI had failed to achieve the required standard in literacy and numeracy by the time they left full-time education. This paper reports the findings of an experimental evaluation of a programmed designed to improve educational outcomes of a cohort of children starting primary school in areas of high social disadvantage in Northern Ireland. The intervention: ‘Ready to Learn’ comprised two key components: a literacy-rich After School programme (one hour after school, three days per week), and a range of activities and support to promote the engagement of parents with their children’s learning, in school and at home. The intervention was delivered between September 2010 and August 2013. Study aims and objectives: The primary aim was to assess whether, and to what extent, ‘Ready to Learn’ improved the literacy of socially disadvantaged children entering primary schools compared with children in schools without access to the programme. Secondary aims included assessing the programme’s impact on children’s social, emotional and behavioural regulation, and parents’ engagement with their children’s learning. In total, 505 children (almost all) participated in the baseline assessment for the study, with good retention over seven sweeps of data collection. Study design: The intervention was evaluated by means of a cluster randomized trial, with schools as the unit of randomization and analysis. It included a qualitative component designed to examine process and implementation, and to explore the concept of parental engagement. Sixteen schools participated, with nine randomized to the experimental group. As well as outcome data relating to children, 134 semi-structured interviews were conducted with parents over the three years of the study, together with 88 interviews with school staff. Results: Given the children’s ages, not all measures used were direct measures of reading. Findings point to a positive impact of “Ready to Learn” on children’s reading achievement (comprehension and fluency), as assessed by the York Assessment of Reading Comprehension (YARC) and decoding, assessed using the Word Recognition and Phonic Skills (WRaPS3). Effects were not large, but evidence suggests that it is unusual for an after school programme to clearly to demonstrate effects on reading skills. No differences were found on three other measures of literacy-related skills: British Picture Vocabulary Scale (BPVS-II), Naming Speed and Non-word Reading Tests from the Phonological Assessment Battery (PhAB) or Concepts about Print (CAP) – the last due to an age-related ceiling effect). No differences were found between the two groups on measures of social, emotional and behavioural regulation, and due to low levels of participation, it was not possible directly to assess the contribution of the parent component to children’s outcomes. The qualitative data highlighted conflicting concepts of engagement between parents and school staff. Ready to Learn is a promising intervention that merits further support and evaluation.

Keywords: after-school, education, literacy, parental engagement

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Authors: Jinyan Li, Simon Fong, Raymond Wong, Mohammed Sabah, Fiaidhi Jinan

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Clinical data analysis and forecasting have make great contributions to disease control, prevention and detection. However, such data usually suffer from highly unbalanced samples in class distributions. In this paper, we target at the binary imbalanced dataset, where the positive samples take up only the minority. We investigate two different meta-heuristic algorithms, particle swarm optimization and bat-inspired algorithm, and combine both of them with the synthetic minority over-sampling technique (SMOTE) for processing the datasets. One approach is to process the full dataset as a whole. The other is to split up the dataset and adaptively process it one segment at a time. The experimental results reveal that while the performance improvements obtained by the former methods are not scalable to larger data scales, the later one, which we call Adaptive Swarm Balancing Algorithms, leads to significant efficiency and effectiveness improvements on large datasets. We also find it more consistent with the practice of the typical large imbalanced medical datasets. We further use the meta-heuristic algorithms to optimize two key parameters of SMOTE. Leading to more credible performances of the classifier, and shortening the running time compared with the brute-force method.

Keywords: Imbalanced dataset, meta-heuristic algorithm, SMOTE, big data

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Authors: Sheena K. J., Jyoti Badge, Sayed Mohammed Zeeshan

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A Comparative Study of Exponential and Logistic Population Growth Models in India India is the second most populous city in the world, just behind China, and is going to be in the first place by next year. The Indian population has remarkably at higher rate than the other countries from the past 20 years. There were many scientists and demographers who has formulated various models of population growth in order to study and predict the future population. Some of the models are Fibonacci population growth model, Exponential growth model, Logistic growth model, Lotka-Volterra model, etc. These models have been effective in the past to an extent in predicting the population. However, it is essential to have a detailed comparative study between the population models to come out with a more accurate one. Having said that, this research study helps to analyze and compare the two population models under consideration - exponential and logistic growth models, thereby identifying the most effective one. Using the census data of 2011, the approximate population for 2016 to 2031 are calculated for 20 Indian states using both the models, compared and recorded the data with the actual population. On comparing the results of both models, it is found that logistic population model is more accurate than the exponential model, and using this model, we can predict the future population in a more effective way. This will give an insight to the researchers about the effective models of population and how effective these population models are in predicting the future population.

Keywords: population growth, population models, exponential model, logistic model, fibonacci model, lotka-volterra model, future population prediction, demographers

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Authors: Jairo A. Muñoz, Alexander Komissarov, Alexander Gromov

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In this investigation, a hypoeutectic AlSi11Cu alloy was printed. This alloy was obtained in powder form with an average particle size of 40 µm. Bars 20 mm in diameter and 100 mm in length were printed with the building direction parallel to the bars' longitudinal direction. The microstructural characterization demonstrated an Al matrix surrounded by a Si network forming a coral-like pattern. The microstructure of the alloy showed a heterogeneous behavior with a mixture of columnar and equiaxed grains. Likewise, the texture indicated that the columnar grains were preferentially oriented towards the building direction, while the equiaxed followed a texture dominated by the cube component. On the other hand, the as-printed material strength showed higher values than those obtained in the same alloy using conventional processes such as casting. In addition, strength and ductility differences were found in the printed material, depending on the measurement direction. The highest values were obtained in the radial direction (565 MPa maximum strength and 4.8% elongation to failure). The lowest values corresponded to the transverse direction (508 MPa maximum strength and 3.2 elongation to failure), which corroborate the material anisotropy.

Keywords: additive manufacturing, aluminium alloy, melting pools, tensile test

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Authors: Anurag Jha

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Dharavi is the largest slum in Asia, for which many redevelopment projects have been put forth, to improve the housing conditions of the locals. And yet, these projects are met with much-unexpected resistance from the locals. The research analyses the why and the how of the resistances these projects face and analyses these programs and points out the flaws and benefits of such projects, by predicting its impact on the regulars of Dharavi. The research aims to analyze various aspects of Dharavi, which affect its socio-cultural backdrops, such as its history, and eventual growth into a mega slum. Through various surveys, the research aims to analyze the life of a slum dweller, the street life, and the effect of such settlement on the urban fabric. Various development projects such as Dharavi Museum Movement, are analyzed, and a feasibility and efficiency analysis of the proposals for redevelopment of Dharavi Slums has been theorized. Flaws and benefits of such projects, by predicting its impact on the regulars of Dharavi has been the major approach to the research. Also, prediction the implementation of these projects in another prominent slum area, Anand Nagar, Bhopal, with the use of generated hypothetical model has been done. The research provides a basic framework for a comparative analysis of various redevelopment projects and the effect of implementation of such projects on the general populace. Secondly, it proposes a hypothetical model for feasibility of such projects in certain slum areas.

Keywords: Anand Nagar, Bhopal slums, Dharavi, slum redevelopment programmes

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Authors: Shank Kulkarni, Alireza Tabarraei

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The fantastic properties of polyurea such as flexibility, durability, and chemical resistance have brought it a wide range of application in various industries. Effective prediction of the response of polyurea under different loading and environmental conditions necessitates the development of an accurate constitutive model. Similar to most polymers, the behavior of polyurea depends on both strain and strain rate. Therefore, the constitutive model should be able to capture both these effects on the response of polyurea. To achieve this objective, in this paper, a nonlinear hyper-viscoelastic constitutive model is developed by the superposition of a hyperelastic and a viscoelastic model. The proposed constitutive model can capture the behavior of polyurea under compressive loading conditions at various strain rates. Four parameter Ogden model and Mooney Rivlin model are used to modeling the hyperelastic behavior of polyurea. The viscoelastic behavior is modeled using both a three-parameter standard linear solid (SLS) model and a K-BKZ model. Comparison of the modeling results with experiments shows that Odgen and SLS model can more accurately predict the behavior of polyurea. The material parameters of the model are found by curve fitting of the proposed model to the uniaxial compression test data. The proposed model can closely reproduce the stress-strain behavior of polyurea for strain rates up to 6500 /s.

Keywords: constitutive modelling, ogden model, polyurea, SLS model, uniaxial compression test

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Authors: Chisomo Patrick Kumbuyo, Katsuyuki Shimizu, Hiroshi Yasuda, Yoshinobu Kitamura

Abstract:

This study deals with a way of predicting Malawi rainfall from global sea surface temperature (SST) using a simple multiple regression model. Monthly rainfall data from nine stations in Malawi grouped into two zones on the basis of inter-station rainfall correlations were used in the study. Zone 1 consisted of Karonga and Nkhatabay stations, located in northern Malawi; and Zone 2 consisted of Bolero, located in northern Malawi; Kasungu, Dedza, Salima, located in central Malawi; Mangochi, Makoka and Ngabu stations located in southern Malawi. Links between Malawi rainfall and SST based on statistical correlations were evaluated and significant results selected as predictors for the regression models. The predictors for Zone 1 model were identified from the Atlantic, Indian and Pacific oceans while those for Zone 2 were identified from the Pacific Ocean. The correlation between the fit of predicted and observed rainfall values of the models were satisfactory with r=0.81 and 0.54 for Zone 1 and 2 respectively (significant at less than 99.99%). The results of the models are in agreement with other findings that suggest that SST anomalies in the Atlantic, Indian and Pacific oceans have an influence on the rainfall patterns of Southern Africa.

Keywords: Malawi rainfall, forecast model, predictors, SST

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Authors: Folorunso Omoniyi, Peter Olubambi, Rotimi Sadiku

Abstract:

Thermal barrier coating (TBC) system is used in both aero engines and other gas turbines to offer oxidation protection to superalloy substrate component. In the present work, it shows the ability of a new fabrication technique to develop rapidly new coating composition and microstructure. The compact powders were prepared by Powder Metallurgy method involving powder mixing and the bond coat was synthesized through the application of Spark Plasma Sintering (SPS) at 10500C to produce a fully dense (97%) NiCrAl bulk samples. The influence of sintering temperature on the hardness of NiCrAl, done by Micro Vickers hardness tester, was investigated. And Oxidation test was carried out at 1100oC for 20h, 40h, and 100h. The resulting coat was characterized with optical microscopy, scanning electron microscopy (SEM), energy dispersive x-ray analysis (EDAX) and x-ray diffraction (XRD). Micro XRD analysis after the oxidation test revealed the formation of protective oxides and non-protective oxides.

Keywords: high-temperature oxidation, powder metallurgy, spark plasma sintering, thermal barrier coating

Procedia PDF Downloads 499

Authors: Seyedali Seyedkavoosi, Mohammad Obadat, Seantorrion Boyle

Abstract:

The purpose of this study is to assess the effectiveness of a nontraditional experiential learning strategy in improving the success and interest of mechanical engineering students, using the Kinematics/Dynamics of Machine course as a case study. This upper-division technical course covers a wide range of topics, including mechanism and machine system analysis and synthesis, yet the complexities of ideas like acceleration, motion, and machine component relationships are hard to explain using standard teaching techniques. To solve this problem, a thorough design project was created that gave students hands-on experience developing, manufacturing, and testing their inventions. The main goals of the project were to improve students' grasp of machine design and kinematics, to develop problem-solving and presenting abilities, and to familiarize them with professional software. A questionnaire survey was done to evaluate the effect of this technique on students' performance and interest in mechanical engineering. The outcomes of the study shed light on the usefulness of nontraditional experiential learning approaches in engineering education.

Keywords: experiential learning, nontraditional teaching, hands-on design project, engineering education

Procedia PDF Downloads 89

Authors: Amin Nezarat, Naeime Seifadini

Abstract:

Trip mode selection is a behavioral characteristic of passengers with immense importance for travel demand analysis, transportation planning, and traffic management. Identification of trip mode distribution will allow transportation authorities to adopt appropriate strategies to reduce travel time, traffic and air pollution. The majority of existing trip mode inference models operate based on human selected features and traditional machine learning algorithms. However, human selected features are sensitive to changes in traffic and environmental conditions and susceptible to personal biases, which can make them inefficient. One way to overcome these problems is to use neural networks capable of extracting high-level features from raw input. In this study, the convolutional neural network (CNN) architecture is used to predict the trip mode distribution based on raw GPS trajectory data. The key innovation of this paper is the design of the layout of the input layer of CNN as well as normalization operation, in a way that is not only compatible with the CNN architecture but can also represent the fundamental features of motion including speed, acceleration, jerk, and Bearing rate. The highest prediction accuracy achieved with the proposed configuration for the convolutional neural network with batch normalization is 85.26%.

Keywords: predicting, deep learning, neural network, urban trip

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Authors: Ayhan Ince

Abstract:

In this paper, an analytical simplified method for calculating elasto-plastic stresses strains of notched bodies subject to non-proportional loading paths is discussed. The method was based on the Neuber notch correction, which relates the incremental elastic and elastic-plastic strain energy densities at the notch root and the material constitutive relationship. The validity of the method was presented by comparing computed results of the proposed model against finite element numerical data of notched shaft. The comparison showed that the model estimated notch-root elasto-plastic stresses strains with good accuracy using linear-elastic stresses. The prosed model provides more efficient and simple analysis method preferable to expensive experimental component tests and more complex and time consuming incremental non-linear FE analysis. The model is particularly suitable to perform fatigue life and fatigue damage estimates of notched components subjected to non-proportional loading paths.

Keywords: elasto-plastic, stress-strain, notch analysis, nonprortional loadings, cyclic plasticity, fatigue

Procedia PDF Downloads 457