Search results for: capability maturity model integration

Authors: S. Boukais, A. Nekmouche, N. Khelil, A. Kezmane

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The first intent of this study is to develop a finite element model that can predict correctly the behavior of the reinforced concrete column. Second aim is to use the finite element model to investigate and evaluate the effect of the strengthening method by jacketing of the reinforced concrete column, by considering different interface contact between the old and the new concrete. Four models were evaluated, one by considering perfect contact, the other three models by using friction coefficient of 0.1, 0.3 and 0.5. The simulation was carried out by using Abaqus software. The obtained results show that the jacketing reinforcement led to significant increase of the global performance of the behavior of the simulated reinforced concrete column.

Keywords: strengthening, jacketing, rienforced concrete column, Abaqus, simulation

Procedia PDF Downloads 132

Authors: André Jesus, Yanjie Zhu, Irwanda Laory

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Structural health monitoring is one of the most promising technologies concerning aversion of structural risk and economic savings. Analysts often have to deal with a considerable variety of uncertainties that arise during a monitoring process. Namely the widespread application of numerical models (model-based) is accompanied by a widespread concern about quantifying the uncertainties prevailing in their use. Some of these uncertainties are related with the deterministic nature of the model (code uncertainty) others with the variability of its inputs (parameter uncertainty) and the discrepancy between a model/experiment (systematic uncertainty). The actual process always exhibits a random behaviour (observation error) even when conditions are set identically (residual variation). Bayesian inference assumes that parameters of a model are random variables with an associated PDF, which can be inferred from experimental data. However in many Bayesian methods the determination of systematic uncertainty can be problematic. In this work systematic uncertainty is associated with a discrepancy function. The numerical model and discrepancy function are approximated by Gaussian processes (surrogate model). Finally, to avoid the computational burden of a fully Bayesian approach the parameters that characterise the Gaussian processes were estimated in a four stage process (modular Bayesian approach). The proposed methodology has been successfully applied on fields such as geoscience, biomedics, particle physics but never on the SHM context. This approach considerably reduces the computational burden; although the extent of the considered uncertainties is lower (second order effects are neglected). To successfully identify the considered uncertainties this formulation was extended to consider multiple responses. The efficiency of the algorithm has been tested on a small scale aluminium bridge structure, subjected to a thermal expansion due to infrared heaters. Comparison of its performance with responses measured at different points of the structure and associated degrees of identifiability is also carried out. A numerical FEM model of the structure was developed and the stiffness from its supports is considered as a parameter to calibrate. Results show that the modular Bayesian approach performed best when responses of the same type had the lowest spatial correlation. Based on previous literature, using different types of responses (strain, acceleration, and displacement) should also improve the identifiability problem. Uncertainties due to parametric variability, observation error, residual variability, code variability and systematic uncertainty were all recovered. For this example the algorithm performance was stable and considerably quicker than Bayesian methods that account for the full extent of uncertainties. Future research with real-life examples is required to fully access the advantages and limitations of the proposed methodology.

Keywords: bayesian, calibration, numerical model, system identification, systematic uncertainty, Gaussian process

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Authors: Saheed Olakunle Sanusi, Israel Ajibade Adedeji

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The study analysed the effect of microfinance on the profit level of small and medium scale enterprises in Lagos. The data for the study were obtained by simple random sampling, and total of one hundred and fifty (150) small and medium scale enterprises (SMEs) were sampled for the study. Seventy-five (75) each are microfinance users and non-users. Data were analysed using descriptive statistics, logit model, t-test and ordinary least square (OLS) regression. The mean profit of the enterprises using microfinance is ₦16.8m, while for the non-users of microfinance is ₦5.9m. The mean profit of microfinance users is statistically different from the non-users. The result of the logit model specified for the determinant of access to microfinance showed that three of specified variables- educational status of the enterprise head, credit utilisation and volume of business investment are significant at P < 0.01. Enterprises with many years of experience, highly educated enterprise heads and high volume of business investment have more potential access to microfinance. The OLS regression model indicated that three parameters namely number of school years, the volume of business investment and (dummy) participation in microfinance were found to be significant at P < 0.05. These variables are therefore significant determinants of impacts of microfinance on profit level in the study area. The study, therefore, concludes and recommends that to improve the status of small and medium scale enterprises for an increase in profit, the full benefit of access to microfinance can be enhanced through investment in social infrastructure and human capital development. Also, concerted efforts should be made to encouraged non-users of microfinance among SMEs to use it in order to boost their profit.

Keywords: credit utilisation, logit model, microfinance, small and medium enterprises

Procedia PDF Downloads 189

Authors: Rakesh Namdeti

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Toxic dyes found in industrial effluent must be treated before being disposed of due to their harmful impact on human health and aquatic life. Thus, Musa acuminata (Banana Leaves) was employed in the role of a biosorbent in this work to get rid of methylene blue derived from a synthetic solution. The effects of five process parameters, such as temperature, pH, biosorbent dosage, and initial methylene blue concentration, using a central composite design (CCD), and the percentage of dye clearance were investigated. The response was modelled using a quadratic model based on the CCD. The analysis of variance revealed the most influential element on experimental design response (ANOVA). The temperature of 44.30C, pH of 7.1, biosorbent dose of 0.3 g, starting methylene blue concentration of 48.4 mg/L, and 84.26 percent dye removal were the best conditions for Musa acuminata (Banana leave powder). At these ideal conditions, the experimental percentage of biosorption was 76.93. The link between the estimated results of the developed ANN model and the experimental results defined the success of ANN modeling. As a result, the study's experimental results were found to be quite close to the model's predicted outcomes.

Keywords: Musa acuminata, central composite design, methylene blue, artificial neural network

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Authors: Weiyao Zhu, Qian Qi, Ming Yue, Dongxu Ma

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Due to the nano-micro pore structures and the massive multi-stage multi-cluster hydraulic fracturing in shale gas reservoirs, the multi-scale seepage flows are much more complicated than in most other conventional reservoirs, and are crucial for the economic development of shale gas. In this study, a new multi-scale non-linear flow model was established and simplified, based on different diffusion and slip correction coefficients. Due to the fact that different flow laws existed between the fracture network and matrix zone, a three-zone composite model was proposed. Then, according to the conformal transformation combined with the law of equivalent percolation resistance, the productivity equation of a horizontal fractured well, with consideration given to diffusion, slip, desorption, and absorption, was built. Also, an analytic solution was derived, and the interference of the multi-cluster fractures was analyzed. The results indicated that the diffusion of the shale gas was mainly in the transition and Fick diffusion regions. The matrix permeability was found to be influenced by slippage and diffusion, which was determined by the pore pressure and diameter according to the Knudsen number. It was determined that, with the increased half-lengths of the fracture clusters, flow conductivity of the fractures, and permeability of the fracture network, the productivity of the fractured well also increased. Meanwhile, with the increased number of fractures, the distance between the fractures decreased, and the productivity slowly increased due to the mutual interference of the fractures. In regard to the fractured horizontal wells, the free gas was found to majorly contribute to the productivity, while the contribution of the desorption increased with the increased pressure differences.

Keywords: multi-scale, fracture network, composite model, productivity

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Authors: Nurudeen Oluwasola Lasisi

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Newcastle disease is a highly contagious disease of birds caused by a para-myxo virus. In this paper, we presented Novel quarantine-adjusted incident and linear incident of Newcastle disease model equations. We considered the dynamics of transmission and control of Newcastle disease. The existence and uniqueness of the solutions were obtained. The existence of disease-free points was shown, and the model threshold parameter was examined using the next-generation operator method. The sensitivity analysis was carried out in order to identify the most sensitive parameters of the disease transmission. This revealed that as parameters β,ω, and ᴧ increase while keeping other parameters constant, the effective reproduction number R_ev increases. This implies that the parameters increase the endemicity of the infection of individuals. More so, when the parameters μ,ε,γ,δ_1, and α increase, while keeping other parameters constant, the effective reproduction number R_ev decreases. This implies the parameters decrease the endemicity of the infection as they have negative indices. Analytical results were numerically verified by the Differential Transformation Method (DTM) and quantitative views of the model equations were showcased. We established that as contact rate (β) increases, the effective reproduction number R_ev increases, as the effectiveness of drug usage increases, the R_ev decreases and as the quarantined individual decreases, the R_ev decreases. The results of the simulations showed that the infected individual increases when the susceptible person approaches zero, also the vaccination individual increases when the infected individual decreases and simultaneously increases the recovery individual.

Keywords: disease-free equilibrium, effective reproduction number, endemicity, Newcastle disease model, numerical, Sensitivity analysis

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Authors: Leili Esmaeilani, Jafar Ghaisari, Mohsen Ahmadian

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Hammerstein–Wiener model is a block-oriented model where a linear dynamic system is surrounded by two static nonlinearities at its input and output and could be used to model various processes. This paper contains an optimization approach method for analysing the problem of Hammerstein–Wiener systems identification. The method relies on reformulate the identification problem; solve it as constraint quadratic problem and analysing its solutions. During the formulation of the problem, effects of adding noise to both input and output signals of nonlinear blocks and disturbance to linear block, in the emerged equations are discussed. Additionally, the possible parametric form of matrix operations to reduce the equation size is presented. To analyse the possible solutions to the mentioned system of equations, a method to reduce the difference between the number of equations and number of unknown variables by formulate and importing existing knowledge about nonlinear functions is presented. Obtained equations are applied to an instance H–W system to validate the results and illustrate the proposed method.

Keywords: identification, Hammerstein-Wiener, optimization, quantization

Procedia PDF Downloads 247

Authors: Shrawan Baghel, Helen Cathcart, Biall J. O'Reilly

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Amorphous drug formulations have great potential to enhance solubility and thus bioavailability of BCS class II drugs. However, the higher free energy and molecular mobility of the amorphous form lowers the activation energy barrier for crystallization and thermodynamically drives it towards the crystalline state which makes them unstable. Accurate determination of the crystallization tendency/kinetics is the key to the successful design and development of such systems. In this study, dipyridamole (DPM) and cinnarizine (CNZ) has been selected as model compounds. Thermodynamic fragility (m_T) is measured from the heat capacity change at the glass transition temperature (Tg) whereas dynamic fragility (m_D) is evaluated using methods based on extrapolation of configurational entropy to zero 〖(m〗_(D_CE )), and heating rate dependence of Tg 〖(m〗_(D_Tg)). The mean relaxation time of amorphous drugs was calculated from Vogel-Tammann-Fulcher (VTF) equation. Furthermore, the correlation between fragility and glass forming ability (GFA) of model drugs has been established and the relevance of these parameters to crystallization of amorphous drugs is also assessed. Moreover, the crystallization kinetics of model drugs under isothermal conditions has been studied using Johnson-Mehl-Avrami (JMA) approach to determine the Avrami constant ‘n’ which provides an insight into the mechanism of crystallization. To further probe into the crystallization mechanism, the non-isothermal crystallization kinetics of model systems was also analysed by statistically fitting the crystallization data to 15 different kinetic models and the relevance of model-free kinetic approach has been established. In addition, the crystallization mechanism for DPM and CNZ at each extent of transformation has been predicted. The calculated fragility, glass forming ability (GFA) and crystallization kinetics is found to be in good correlation with the stability prediction of amorphous solid dispersions. Thus, this research work involves a multidisciplinary approach to establish fragility, GFA and crystallization kinetics as stability predictors for amorphous drug formulations.

Keywords: amorphous, fragility, glass forming ability, molecular mobility, mean relaxation time, crystallization kinetics, stability

Procedia PDF Downloads 339

Authors: Ahmed Kayad Abdourazak, Abderafi Souad, Zejli Driss, Idriss Abdoulkader Ibrahim

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In this paper Artificial Neural Network (ANN) is used to predict the solar irradiation in Djibouti for the first Time that is useful to the integration of Concentrating Solar Power (CSP) and sites selections for new or future solar plants as part of solar energy development. An ANN algorithm was developed to establish a forward/reverse correspondence between the latitude, longitude, altitude and monthly solar irradiation. For this purpose the German Aerospace Centre (DLR) data of eight Djibouti sites were used as training and testing in a standard three layers network with the back propagation algorithm of Lavenber-Marquardt. Results have shown a very good agreement for the solar irradiation prediction in Djibouti and proves that the proposed approach can be well used as an efficient tool for prediction of solar irradiation by providing so helpful information concerning sites selection, design and planning of solar plants.

Keywords: artificial neural network, solar irradiation, concentrated solar power, Lavenberg-Marquardt

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Authors: Najla Kamergi

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In a world context of increasing interest in environmental issues, this paper investigates the effect of agri-environmental regulations heterogeneity on the volume of crop commodities’ exports using a theoretically justified gravity model of Anderson and van Wincoop (2003) for the 2003–2013 period. Our findings show that the difference in exporter and importer environmental regulations is more relevant to agricultural trade than trade agreements. In fact, the environmental gap between the two partners is decreasing slightly but significantly crop commodities’ exports according to our results. We also note that the sector of fruit and vegetables is more sensitive to this determinant, unlike cereals that remain relatively less affected. Furthermore, high-income countries have more tendency to trade with countries characterized by similar environmental stringency. Further results show that the BRICS are clearly importing from developed countries where the environmental difference is relatively important. It is likely that emerging countries are witnessing a growing demand for high-quality and “green” crop commodities captured by high-income exporters. Surprisingly, our results suggest that low and middle-income countries with the same level of environmental stringency are more likely to trade crop commodities.

Keywords: agricultural trade, environment, gravity model, food crops, agri-environmental efficiency, DEA

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Authors: Vilma Deltuvaitė

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Comparisons of financial development across countries are central to answering many of the questions on factors leading to economic development. For this reason this study analyzes the implications of financial system’s development on country’s economic development. The aim of the article: to analyze the impact of financial system’s development on economic development. The following research methods were used: systemic, logical and comparative analysis of scientific literature, analysis of statistical data, time series model (Autoregressive Distributed Lag (ARDL) Model). The empirical results suggest about positive short and long term effect of stock market development on GDP per capita.

Keywords: banking sector, economic development, financial system’s development, stock market, private bond market

Procedia PDF Downloads 367

Authors: Chakrit Chotamonsak, Eric P. Salathé Jr, Jiemjai Kreasuwan

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Dynamical downscaling of the ECHAM5 global climate model is applied at 20-km horizontal resolution using the WRF regional climate model (WRF-ECHAM5), to project changes from 1990–2009 to 2045–2064 of temperature and precipitation over the Upper Ping River Basin. The analysis found that monthly changes in daily temperature and precipitation over the basin for the 2045-2064 compared to the 1990-2009 are revealed over the basin all months, with the largest warmer in December and the smallest warmer in February. The future simulated precipitation is smaller than that of the baseline value in May, July and August, while increasing of precipitation is revealed during pre-monsoon (April) and late monsoon (September and October). This means that the rainy season likely becomes longer and less intensified during the rainy season. During the cool-dry season and hot-dry season, precipitation is substantial increasing over the basin. For the annual cycle of changes in daily temperature and precipitation over the upper Ping River basin, the largest warmer in the mean temperature over the basin is 1.93 °C in December and the smallest is 0.77 °C in February. Increase in nighttime temperature (minimum temperature) is larger than that of daytime temperature (maximum temperature) during the dry season, especially in wintertime (November to February), resulted in decreasing the diurnal temperature range. The annual and seasonal changes in daily temperature and precipitation averaged over the basin. The annual mean rising are 1.43, 1.54 and 1.30 °C for mean temperature, maximum temperature and minimum temperature, respectively. The increasing of maximum temperature is larger than that of minimum temperature in all months during the dry season (November to April).

Keywords: climate change, regional climate model, upper Ping River basin, WRF

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Authors: I. Szer, J. Szer, K. Czarnocki, E. Błazik-Borowa

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People on construction scaffoldings work in dynamically changing, often unfavourable climate. Additionally, this kind of work is performed on low stiffness structures at high altitude, which increases the risk of accidents. It is therefore desirable to define the parameters of the work environment that contribute to increasing the construction worker occupational safety level. The aim of this article is to present how changes in microclimate parameters on scaffolding can impact the development of dangerous situations and accidents. For this purpose, indicators based on the human thermal balance were used. However, use of this model under construction conditions is often burdened by significant errors or even impossible to implement due to the lack of precise data. Thus, in the target model, the modified parameter was used – apparent environmental temperature. Apparent temperature in the proposed Scaffold Use Risk Assessment Model has been a perceived outdoor temperature, caused by the combined effects of air temperature, radiative temperature, relative humidity and wind speed (wind chill index, heat index). In the paper, correlations between component factors and apparent temperature for facade scaffolding with a width of 24.5 m and a height of 42.3 m, located at south-west side of building are presented. The distribution of factors on the scaffolding has been used to evaluate fitting of the microclimate model. The results of the studies indicate that observed ranges of apparent temperature on the scaffolds frequently results in a worker’s inability to adapt. This leads to reduced concentration and increased fatigue, adversely affects health, and consequently increases the risk of dangerous situations and accidental injuries

Keywords: apparent temperature, health, safety work, scaffoldings

Procedia PDF Downloads 165

Authors: Mingming Jiang

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This literature review aims to offer an overview of existing research on learning analytics and learning design, the alignment between the two, and how learning analytics has been leveraged to inform learning design in higher education. Current research suggests a need to create more alignment and integration between learning analytics and learning design in order to not only ground learning analytics on learning sciences but also enable data-driven decisions in learning design to improve learning outcomes. In addition, multiple conceptual frameworks have been proposed to enhance the synergy and alignment between learning analytics and learning design. Future research should explore this synergy further in the unique context of higher education, identifying learning analytics metrics in higher education that can offer insight into learning processes, evaluating the effect of learning analytics outcomes on learning design decision-making in higher education, and designing learning environments in higher education that make the capturing and deployment of learning analytics outcomes more efficient.

Keywords: learning analytics, learning design, big data in higher education, online learning environments

Procedia PDF Downloads 142

Authors: Fatemeh Nemati, Lucinda Leonard, Gwyn Lintern, Richard Thomson

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In this study, we will use modern numerical modeling approaches to estimate tsunami risks to the southern coast of British Columbia from landslides. Wave generation is to be simulated using the NHWAVE model, which solves the Navier-Stokes equations due to the more complex behavior of flow near the landslide source; far-field wave propagation will be simulated using the simpler model FUNWAVE_TVD with high-order Boussinesq-type wave equations, with a focus on the accurate simulation of wave propagation and regional- or coastal-scale inundation predictions.

Keywords: FUNWAVE-TVD, landslide-generated tsunami, NHWAVE, tsunami risk

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Authors: Amit Kumar, Amanpreet Chander, Ashish Sahani

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This paper presents our recent work on real-time human activity detection based on the media pipe pipeline and machine learning algorithms. The proposed system can detect human activities, including running, jumping, squatting, bending to the left or right, and standing still. This is a robust solution for developing a yoga, dance, metaverse, and fitness application that checks for the correction of the pose without having any additional monitor like a personal trainer. MediaPipe solution offers an open-source cross-platform which utilizes a two-step detector-tracker ML pipeline for live detection of key landmarks on our body which can be used for motion data collection. The prediction of real-time poses uses a variety of machine learning techniques and different types of analysis. Without primarily relying on powerful desktop environments for inference, our method achieves real-time performance on the majority of contemporary mobile phones, desktops/laptops, Python, or even the web. Experimental results show that our method outperforms the existing method in terms of accuracy and real-time capability, achieving an accuracy of 99.92% on testing datasets.

Keywords: human activity detection, media pipe, machine learning, metaverse applications

Procedia PDF Downloads 158

Authors: Ramon Santana

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The use of biometric identifiers in the field of information security, access control to resources, authentication in ATMs and banking among others, are of great concern because of the safety of biometric data. In the general architecture of a biometric system have been detected eight vulnerabilities, six of them allow obtaining minutiae template in plain text. The main consequence of obtaining minutia templates is the loss of biometric identifier for life. To mitigate these vulnerabilities several models to protect minutiae templates have been proposed. Several vulnerabilities in the cryptographic security of these models allow to obtain biometric data in plain text. In order to increase the cryptographic security and ease of reversibility, a minutiae templates protection model is proposed. The model aims to make the cryptographic protection and facilitate the reversibility of data using two levels of security. The first level of security is the data transformation level. In this level generates invariant data to rotation and translation, further transformation is irreversible. The second level of security is the evaluation level, where the encryption key is generated and data is evaluated using a defined evaluation function. The model is aimed at mitigating known vulnerabilities of the proposed models, basing its security on the impossibility of the polynomial reconstruction.

Keywords: fingerprint, template protection, bio-cryptography, minutiae protection

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Authors: Latif Adnane, C. E. Ait Zaouiat, M. Eddabbah

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In Wireless Body Area Networks, the issue of systems lifetime is a big challenge to complete. In this paper, we have tackled this subject to suggest some solutions. For this aim, we have studied some batteries characteristics related to human body temperature. Moreover, we have analyzed a mathematical model which defines sensors lifetime (battery lifetime). Based on this model, we note that the random access increases the energy consumption, because nodes are waking up during the whole superframe period. Results show that using scheduled mode access of IEEE 802.15.6 maximizes the lifetime function, by setting nodes in the sleep mode in the inactive period of transmission.

Keywords: battery, energy consumption, IEEE 802.15.6, lifetime, polling

Procedia PDF Downloads 324

Authors: Eman M. Eissa, Hany M. Hasanin, Mahmoud Abd-Elhamid, S. M. Muyeen, T. Fernando, H. H. C. Iu

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Among all available wind energy conversion systems (WECS), the direct driven permanent magnet synchronous generator integrated with power electronic interfaces is becoming popular due to its capability of extracting optimal energy capture, reduced mechanical stresses, no need to external excitation current, meaning less losses, and more compact size. Simple structure, low maintenance cost; and its decoupling control performance is much less sensitive to the parameter variations of the generator. This paper attempts to present a review of the control and optimization strategies of WECS based on permanent magnet synchronous generator (PMSG) and overview the most recent research trends in this field. The main aims of this review include; the generalized overall WECS starting from turbines, generators, and control strategies including converters, maximum power point tracking (MPPT), ending with DC-link control. The optimization methods of the controller parameters necessary to guarantee the operation of the system efficiently and safely, especially when connected to the power grid are also presented.

Keywords: control and optimization techniques, permanent magnet synchronous generator, variable speed wind turbines, wind energy conversion system

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Authors: David Amoah Oduro

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In the ever-evolving terrain of international business, a profound revolution is underway, guided by the swift integration and advancement of disruptive technologies like digital analytics. In today's international business landscape, where competition is fierce, and decisions are data-driven, the essence of this paper lies in offering a tangible roadmap for practitioners. It is a guide that bridges the chasm between theory and actionable insights, helping businesses, investors, and entrepreneurs navigate the complexities of international expansion into sub-Saharan Africa. This practitioner paper distils essential insights, methodologies, and actionable recommendations for businesses seeking to leverage digital analytics in their pursuit of market entry and expansion across the African continent. What sets this paper apart is its unwavering focus on a region ripe with potential: sub-Saharan Africa. The adoption and adaptation of digital analytics are not mere luxuries but essential strategic tools for evaluating countries and entering markets within this dynamic region. With the spotlight firmly fixed on sub-Saharan Africa, the aim is to provide a compelling resource to guide practitioners in their quest to unearth the vast opportunities hidden within sub-Saharan Africa's digital desert. The paper illuminates the pivotal role of digital analytics in providing a data-driven foundation for market entry decisions. It highlights the ability to uncover market trends, consumer behavior, and competitive landscapes. By understanding Africa's incredible diversity, the paper underscores the importance of tailoring market entry strategies to account for unique cultural, economic, and regulatory factors. For practitioners, this paper offers a set of actionable recommendations, including the creation of cross-functional teams, the integration of local expertise, and the cultivation of long-term partnerships to ensure sustainable market entry success. It advocates for a commitment to continuous learning and flexibility in adapting strategies as the African market evolves. This paper represents an invaluable resource for businesses, investors, and entrepreneurs who are keen on unlocking the potential of digital analytics for informed market entry in Africa. It serves as a guiding light, equipping practitioners with the essential tools and insights needed to thrive in this dynamic and diverse continent. With these key insights, methodologies, and recommendations, this paper is a roadmap to prosperous and sustainable market entry in Africa. It is vital for anyone looking to harness the transformational potential of digital analytics to create prosperous and sustainable ventures in a region brimming with promise. In the ever-advancing digital age, this practitioner paper becomes a lodestar, guiding businesses and visionaries toward success amidst the unique challenges and rewards of sub-Saharan Africa's international business landscape.

Keywords: global analytics, digital analytics, sub-Saharan Africa, data analytics

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Authors: Basant K. Jha, M. L. Kaurangini

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An approximate analytical solution is presented for convective flow in a horizontal channel filled with porous material. The Brinkman-Forchheimer extension of Darcy equation is utilized to model the fluid flow while the energy equation is utilized to model temperature distribution in the channel. The solutions were obtained utilizing the newly suggested technique and compared with those obtained from an implicit finite-difference solution.

Keywords: approximate analytical, convective flow, porous material, Brinkman-Forchiemer

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Authors: Ishmael Obaeko Iwara

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The Point of Sale (POS) cash and cashless semi-formal business has emerged as a significant driver of employment in countries like Nigeria and Kenya, similar to other micro and small-scale enterprises. This business model enables individuals to establish cash in/out outlets, offering entrepreneurs and small business owners a lucrative opportunity to generate additional income. However, the benefits extend beyond employment, as the POS model has become an integral part of the payment system in these countries. It facilitates convenient fund transfers, cash deposits, and withdrawals for individuals residing in both urban and rural areas. Given South Africa's high youth unemployment rate and limited banking services in rural households, coupled with a vibrant informal business economy akin to Nigeria and Kenya, the POS model potentially presents a business opportunity for the unemployed and serves as a banking solution for remote communities. Nonetheless, its implementation within South Africa's entrepreneurial landscape remains a subject of contention. Through qualitative research employing a participatory community-led action research approach, this study analyzes feedback, critiques, and potential interventions from various stakeholders, including business actors, grassroots communities, financial institutions, and policymakers. The findings offer crucial insights into the challenges associated with the adoption of the POS model and suggest mitigating factors to facilitate its successful implementation.

Keywords: grassroots entrepreneurs, rural households, POS banking, youth employment

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Authors: Gizem Kayar, Ramazan Bakir, M. Ilkay Koşar, Ceren U. Gencer, Alperen Ayyildiz

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Anatomy classes are crucial for general education of medical students, whereas learning anatomy is quite challenging and requires memorization of thousands of structures. In traditional teaching methods, learning materials are still based on books, anatomy mannequins, or videos. This results in forgetting many important structures after several years. However, more interactive teaching methods like virtual reality, augmented reality, gamification, and motion sensors are becoming more popular since such methods ease the way we learn and keep the data in mind for longer terms. During our study, we designed a virtual reality based digital head anatomy platform to investigate whether a fully interactive anatomy platform is effective to learn anatomy and to understand the level of teaching and learning optimization. The Head is one of the most complicated human anatomy structures, with thousands of tiny, unique structures. This makes the head anatomy one of the most difficult parts to understand during class sessions. Therefore, we developed a fully interactive digital tool with 3D model marking, quiz structures, 2D/3D puzzle structures, and VR support so as to integrate the power of VR and gamification. The project has been developed in Unity game engine with HTC Vive Cosmos VR headset. The head anatomy 3D model has been selected with full skeletal, muscular, integumentary, head, teeth, lymph, and vein system. The biggest issue during the development was the complexity of our model and the marking of it in the 3D world system. 3D model marking requires to access to each unique structure in the counted subsystems which means hundreds of marking needs to be done. Some parts of our 3D head model were monolithic. This is why we worked on dividing such parts to subparts which is very time-consuming. In order to subdivide monolithic parts, one must use an external modeling tool. However, such tools generally come with high learning curves, and seamless division is not ensured. Second option was to integrate tiny colliders to all unique items for mouse interaction. However, outside colliders which cover inner trigger colliders cause overlapping, and these colliders repel each other. Third option is using raycasting. However, due to its own view-based nature, raycasting has some inherent problems. As the model rotate, view direction changes very frequently, and directional computations become even harder. This is why, finally, we studied on the local coordinate system. By taking the pivot point of the model into consideration (back of the nose), each sub-structure is marked with its own local coordinate with respect to the pivot. After converting the mouse position to the world position and checking its relation with the corresponding structure’s local coordinate, we were able to mark all points correctly. The advantage of this method is its applicability and accuracy for all types of monolithic anatomical structures.

Keywords: anatomy, e-learning, virtual reality, 3D model marking

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Authors: N. P. G. N. Chandrasekara, R. M. Pashley

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Ion exchange (IEX) resins are commonly available as cationic or anionic resins but not as polyampholytic resins. This is probably because sequential acid and base washing cannot produce complete regeneration of polyampholytic resins with chemically attached anionic and cationic groups in close proximity. The ‘Sirotherm’ process, developed by the Commonwealth Scientific and Industrial Research Organization (CSIRO) in Melbourne, Australia was originally based on the use of a physical mixture of weakly basic (WB) and weakly acidic (WA) ion-exchange resin beads. These resins were regenerated thermally and they were capable of removing salts from an aqueous solution at higher temperatures compared to the salt sorbed at ambient temperatures with a significant reduction of the sorption capacity with increasing temperature. A new process for the efficient regeneration of mixed bead resins using ammonium bicarbonate with heat was studied recently and this chemical/thermal regeneration technique has the capability for completely regenerating polyampholytic resins. Even so, the low IEX capacities of polyampholytic resins restrict their commercial applications. Recently, we have established another novel process for increasing the IEX capacity of a typical polyampholytic resin. In this paper we will discuss the chemical/thermal regeneration of a polyampholytic (WA/WB) resin and a novel process for enhancing its ion exchange capacity, by increasing its internal pore area. We also show how effective this method is for completely recycled regeneration, with the potential of substantially reducing chemical waste.

Keywords: capacity, ion exchange, polyampholytic resin, regeneration

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Authors: Shahid Nishat, Keith Thomas

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E-government initiatives attract substantial public investments around the world. These investments are based on the premise of digital transformation of the public services, improved efficiency and transparency, and citizen participation in the social democratic processes. However, many e-Government projects, especially in developing countries, fail to achieve their intended outcomes, and a strong disparity exists between the investments made and outcomes achieved, often referred to as e-Government paradox. Further, there is lack of research on evaluating the impacts of e-Government in terms of public value it creates, which ultimately drives usage. This study aims to address these gaps by identifying key enablers of e-Government success and by proposing a public value based framework to examine impact of e-Government services. The study will extend Delone and McLean Information System (IS) Success model by integrating Technology Readiness (TR) characteristics to develop an integrated success model. Level of analysis will be mobile government applications, and the framework will be empirically tested using quantitative methods. The research will add to the literature on e-Government success and will be beneficial for governments, especially in developing countries aspiring to improve public services through the use of Information Communication Technologies (ICT).

Keywords: e-Government, IS success model, public value, technology adoption, technology readiness

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Authors: M. Mohemmed Sha, T. Manesh, A. Ahmed Mohamed Mustaq

Abstract:

In this corporate world, the technology of Web services has grown rapidly and its significance for the development of web based applications gradually rises over time. The success of Business to Business integration rely on finding novel partners and their services in a global business environment. But the selection of the most suitable Web service from the list of services with the identical functionality is more vital. The satisfaction level of the customer and the provider’s reputation of the Web service are primarily depending on the range it reaches the customer’s requirements. In most cases the customer of the Web service feels that he is spending for the service which is undelivered. This is because the customer always thinks that the real functionality of the web service is not reached. This will lead to change of the service frequently. In this paper, a framework is proposed to evaluate the Quality of Service (QoS) and its cost that makes the optimal correlation between each other. Also this research work proposes some management decision against the functional deviancy of the web service that are guaranteed at time of selection.

Keywords: web service, service level agreement, quality of a service, cost of a service, QoS, CoS, SOA, WSLA, WsRF

Procedia PDF Downloads 397

Authors: Qamar J. A. Khan, Fatma Ahmed Al Kharousi

Abstract:

A prey-predator eco-epidemiological model is studied where transmission of the disease between infected and uninfected prey is nonlinear. The interaction of the predator with infected and uninfected prey species depend on their numerical superiority. Harvesting of both uninfected and infected prey is considered. Stability analysis is carried out for equilibrium values. Using the parameter µ, the death rate of infected prey as a bifurcation parameter it is shown that Hopf bifurcation could occur. The theoretical results are compared with numerical results for different set of parameters.

Keywords: bifurcation, optimal harvesting, predator, prey, stability

Procedia PDF Downloads 290

Authors: Bambang Piscesa, Mario M. Attard, Dwi Presetya, Ali K. Samani

Abstract:

A numerical strategy formulated using a plasticity approach is presented to model spalling of the concrete cover in reinforced concrete columns. The stage at which the concrete cover within reinforced concrete column spalls has a direct bearing on the load capacity. The concrete cover can prematurely spall before the full cross-section can be utilized if the concrete is very brittle under compression such as for very high strength concretes. If the confinement to the core is high enough, the column can achieve a higher peak load by utilizing the core. A numerical strategy is presented to model spalling of the concrete cover. Various numerical strategies are employed to model the behavior of reinforced concrete columns which include: (1) adjusting the material properties to incorporate restrained shrinkage; (2) modifying the plastic dilation rate in the presence of the tensile pressure; (3) adding a tension cut-off failure surface and (4) giving the concrete cover region and the column core different material properties. Numerical comparisons against experimental results are carried out that shown excellent agreement with the experimental results and justify the use of the proposed strategies to predict the axial load capacity of reinforce concrete columns.

Keywords: spalling, concrete, plastic dilation, reinforced concrete columns

Procedia PDF Downloads 142

Authors: H. C. Chinwenyi, H. D. Ibrahim, F. A. Ahmed

Abstract:

In modern financial mathematics, valuing derivatives such as options is often a tedious task. This is simply because their fair and correct prices in the future are often probabilistic. This paper examines three different Stochastic Differential Equation (SDE) models in finance; the Constant Elasticity of Variance (CEV) model, the Balck-Karasinski model, and the Heston model. The various Martingales option price valuation formulas for these three models were obtained using the replicating portfolio method. Also, the numerical solution of the derived Martingales options price valuation equations for the SDEs models was carried out using the Monte Carlo method which was implemented using MATLAB. Furthermore, results from the numerical examples using published data from the Nigeria Stock Exchange (NSE), all share index data show the effect of increase in the underlying asset value (stock price) on the value of the European Put Option for these models. From the results obtained, we see that an increase in the stock price yields a decrease in the value of the European put option price. Hence, this guides the option holder in making a quality decision by not exercising his right on the option.

Keywords: equivalent martingale measure, European put option, girsanov theorem, martingales, monte carlo method, option price valuation formula

Procedia PDF Downloads 119

Authors: Xiaowei Zhang, Min Xu, Saeid Habibi, Fengjun Yan, Ryan Ahmed

Abstract:

Recently, Electric Vehicles (EVs) have received extensive consideration since they offer a more sustainable and greener transportation alternative compared to fossil-fuel propelled vehicles. Lithium-Ion (Li-ion) batteries are increasingly being deployed in EVs because of their high energy density, high cell-level voltage, and low rate of self-discharge. Since Li-ion batteries represent the most expensive component in the EV powertrain, accurate monitoring and control strategies must be executed to ensure their prolonged lifespan. The Battery Management System (BMS) has to accurately estimate parameters such as the battery State-of-Charge (SOC), State-of-Health (SOH), and Remaining Useful Life (RUL). In order for the BMS to estimate these parameters, an accurate and control-oriented battery model has to work collaboratively with a robust state and parameter estimation strategy. Since battery physical parameters, such as the internal resistance and diffusion coefficient change depending on the battery state-of-life (SOL), the BMS has to be adaptive to accommodate for this change. In this paper, an extensive battery aging study has been conducted over 12-months period on 5.4 Ah, 3.7 V Lithium polymer cells. Instead of using fixed charging/discharging aging cycles at fixed C-rate, a set of real-world driving scenarios have been used to age the cells. The test has been interrupted every 5% capacity degradation by a set of reference performance tests to assess the battery degradation and track model parameters. As battery ages, the combined model parameters are optimized and tracked in an offline mode over the entire batteries lifespan. Based on the optimized model, a state and parameter estimation strategy based on the Extended Kalman Filter (EKF) and the relatively new Smooth Variable Structure Filter (SVSF) have been applied to estimate the SOC at various states of life.

Keywords: lithium-ion batteries, genetic algorithm optimization, battery aging test, parameter identification

Procedia PDF Downloads 253