Search results for: stock price prediction

Authors: Samy A. Khalil, U. Ali Rahoma

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The measurements of solar radiation, satellite data has been routinely utilize to estimate solar energy. However, the temporal coverage of satellite data has some limits. The reanalysis, also known as "retrospective analysis" of the atmosphere's parameters, is produce by fusing the output of NWP (Numerical Weather Prediction) models with observation data from a variety of sources, including ground, and satellite, ship, and aircraft observation. The result is a comprehensive record of the parameters affecting weather and climate. The effectiveness of reanalysis datasets (ERA-5) for North Africa was evaluate against high-quality surfaces measured using statistical analysis. Estimating the distribution of global solar radiation (GSR) over five chosen areas in North Africa through ten-years during the period time from 2011 to 2020. To investigate seasonal change in dataset performance, a seasonal statistical analysis was conduct, which showed a considerable difference in mistakes throughout the year. By altering the temporal resolution of the data used for comparison, the performance of the dataset is alter. Better performance is indicate by the data's monthly mean values, but data accuracy is degraded. Solar resource assessment and power estimation are discuses using the ERA-5 solar radiation data. The average values of mean bias error (MBE), root mean square error (RMSE) and mean absolute error (MAE) of the reanalysis data of solar radiation vary from 0.079 to 0.222, 0.055 to 0.178, and 0.0145 to 0.198 respectively during the period time in the present research. The correlation coefficient (R2) varies from 0.93 to 99% during the period time in the present research. This research's objective is to provide a reliable representation of the world's solar radiation to aid in the use of solar energy in all sectors.

Keywords: solar energy, ERA-5 analysis data, global solar radiation, North Africa

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Authors: Brindha Senthil Kumar, Payel Chakraborty, Senthil Kumar Nachimuthu, Arindam Maitra, Prem Nath

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Gastric cancer is predominantly caused by demographic and diet factors as compared to other cancer types. The aim of the study is to predict Early Gastric Cancer (ECG) from diet and lifestyle factors using supervised machine learning algorithms. For this study, 160 healthy individual and 80 cases were selected who had been followed for 3 years (2016-2019), at Civil Hospital, Aizawl, Mizoram. A dataset containing 11 features that are core risk factors for the gastric cancer were extracted. Supervised machine algorithms: Logistic Regression, Naive Bayes, Support Vector Machine (SVM), Multilayer perceptron, and Random Forest were used to analyze the dataset using Python Jupyter Notebook Version 3. The obtained classified results had been evaluated using metrics parameters: minimum_false_positives, brier_score, accuracy, precision, recall, F1_score, and Receiver Operating Characteristics (ROC) curve. Data analysis results showed Naive Bayes - 88, 0.11; Random Forest - 83, 0.16; SVM - 77, 0.22; Logistic Regression - 75, 0.25 and Multilayer perceptron - 72, 0.27 with respect to accuracy and brier_score in percent. Naive Bayes algorithm out performs with very low false positive rates as well as brier_score and good accuracy. Naive Bayes algorithm classification results in predicting ECG showed very satisfactory results using only diet cum lifestyle factors which will be very helpful for the physicians to educate the patients and public, thereby mortality of gastric cancer can be reduced/avoided with this knowledge mining work.

Keywords: Early Gastric cancer, Machine Learning, Diet, Lifestyle Characteristics

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Authors: Jing (Claire) LI

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The topic of corporate social responsibility (CSR) is significant for pharmaceutical companies in China at this current stage. This is because, as a rapid growth industry in China in recent years, the pharmaceutical industry in China has been undergone continuous and terrible incidents relating to CSR. However, there is limited research and practice of CSR in Chinese pharmaceutical companies. Also, there is an urgent call for more research in an international context to understand the implications of corporate life cycle on CSR performance. To respond to the research need and research call, this study examines the relationship between corporate life cycle and CSR performance of Chinese listed companies in pharmaceutical industry. This research studies Chinese listed companies in pharmaceutical industry for the period of 2010-2017, where the data is available in database. Following the literature, this study divides CSR performance with regards to CSR dimensions, including shareholders, creditors, employees, customers, suppliers, the government, and the society. This study uses CSR scores of HEXUN database and financial measures of these CSR dimensions to measure the CSR performance. This study performed regression analysis to examine the relationship between corporate life cycle stages and CSR performance with regards to CSR dimensions for pharmaceutical listed companies in China. Using cash flow pattern as proxy of corporate life cycle to classify corporate life cycle stages, this study found that most (least) pharmaceutical companies in China are in maturity (decline) stage. This study found that CSR performance for most dimensions are highest (lowest) in maturity (decline) stage as well. Among these CSR dimensions, performing responsibilities for shareholder is the most important among all CSR responsibilities for pharmaceutical companies. This study is the first to provide important empirical evidence from Chinese pharmaceutical industry on the association between life cycle and CSR performance, supporting that corporate life cycle is a key factor in CSR performance. The study expands corporate life cycle and CSR literatures and has both empirical and theoretical contributions to the literature. From perspective of empirical contributions, the findings contribute to the argument that whether there is a relationship between CSR performance and various corporate life cycle stages in the literature. This study also provides empirical evidence that companies in different corporate life cycles have difference in CSR performance. From perspective of theoretical contributions, this study relates CSR and stakeholders to corporate life cycle stages and complements the corporate life cycle and CSR literature. This study has important implications for managers and policy makers. First, the results will be helpful for managers to have an understanding in the essence of CSR, and their company’s current and future CSR focus over corporate life cycle. This study provides a reference for their actions and may help them make more wise resources allocation decisions of CSR investment. Second, policy makers (in the government, stock exchanges, and securities commission) may consider corporate life cycle as an important factor in formulating future regulations for companies. Future research can explore the "process-based" differences in CSR performance and more industries.

Keywords: China, corporate life cycle, corporate social responsibility, pharmaceutical industry

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Authors: Eun-Soo Lim, Young-Min Kang

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M-type Sr-hexaferrite (SrFe₁₂O₁₉) have been studied during the past decades because it is the most utilized materials in permanent magnets due to their low price, outstanding chemical stability, and appropriate hard magnetic properties. Many attempts have been made to improve the intrinsic magnetic properties of M-type Sr-hexaferrites (SrM), such as by improving the saturation magnetization (MS) and crystalline anisotropy by cation substitution. It is well proved that the Ca-La-Co substitutions are one of the most successful approaches, which lead to a significant enhancement in the crystalline anisotropy without reducing MS, and thus the Ca-La-Co-doped SrM have been commercialized in high-grade magnet products. In this research, the effect of respective doping of Ca and La into the SrM lattices were studied with assumptions that these elements could substitute both of Fe and Sr sites. The hexaferrite samples of stoichiometric SrFe₁₂O₁₉ (SrM) and the Ca substituted SrM with formulae of Sr₁₋ₓCaₓFe₁₂Oₐ (x = 0.1, 0.2, 0.3, 0.4) and SrFe₁₂₋ₓCaₓOₐ (x = 0.1, 0.2, 0.3, 0.4), and also La substituted SrM of Sr₁₋ₓLaₓFe₁₂Oₐ (x = 0.1, 0.2, 0.3, 0.4) and SrFe₁₂₋ₓLaₓOₐ (x = 0.1, 0.2, 0.3, 0.4) were prepared by conventional solid state reaction processes. X-ray diffraction (XRD) with a Cu Kα radiation source (λ=0.154056 nm) was used for phase analysis. Microstructural observation was conducted with a field emission scanning electron microscopy (FE-SEM). M-H measurements were performed using a vibrating sample magnetometer (VSM) at 300 K. Almost pure M-type phase could be obtained in the all series of hexaferrites calcined at > 1250 ºC. Small amount of Fe₂O₃ phases were detected in the XRD patterns of Sr₁₋ₓCaₓFe₁₂Oₐ (x = 0.2, 0.3, 0.4) and Sr₁₋ₓLaₓFe₁₂Oₐ (x = 0.1, 0.2, 0.3, 0.4) samples. Also, small amount of unidentified secondary phases without the Fe₂O₃ phase were found in the samples of SrFe₁₂₋ₓCaₓOₐ (x = 0.4) and SrFe₁₂₋ₓLaₓOₐ (x = 0.3, 0.4). Although the Ca substitution (x) into SrM structure did not exhibit a clear tendency in the cell parameter change in both series of samples, Sr₁₋ₓCaₓFe₁₂Oₐ and SrFe₁₂₋ₓCaₓOₐ , the cell volume slightly decreased with doping of Ca in the Sr₁₋ₓCaₓFe₁₂Oₐ samples and increased in the SrFe₁₂₋ₓCaₓOₐ samples. Considering relative ion sizes between Sr²⁺ (0.113 nm), Ca²⁺ (0.099 nm), Fe³⁺ (0.064 nm), these results imply that the Ca substitutes both of Sr and Fe in the SrM. A clear tendency of cell parameter change was observed in case of La substitution into Sr site of SrM ( Sr₁₋ₓLaₓFe₁₂Oₐ); the cell volume decreased with increase of x. It is owing to the similar but smaller ion size of La³⁺ (0.106 nm) than that of Sr²⁺. In case of SrFe₁₂₋ₓLaₓOₐ, the cell volume first decreased at x = 0.1 and then remained almost constant with increase of x from 0.2 to 0.4. These results mean that La only substitutes Sr site in the SrM structure. Besides, the microstructure and magnetic properties of these samples, and correlation between them will be revealed.

Keywords: M-type hexaferrite, substitution, cell parameter, magnetic properties

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Authors: Joonas Pääkkönen

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In sports, individuals and teams are typically interested in final rankings. Final results, such as times or distances, dictate these rankings, also known as places. Places can be further associated with ordered random variables, commonly referred to as order statistics. In this work, we introduce a simple, yet accurate order statistical ordinal regression function that predicts relay race places with changeover-times. We call this function the Fenton-Wilkinson Order Statistics model. This model is built on the following educated assumption: individual leg-times follow log-normal distributions. Moreover, our key idea is to utilize Fenton-Wilkinson approximations of changeover-times alongside an estimator for the total number of teams as in the notorious German tank problem. This original place regression function is sigmoidal and thus correctly predicts the existence of a small number of elite teams that significantly outperform the rest of the teams. Our model also describes how place increases linearly with changeover-time at the inflection point of the log-normal distribution function. With real-world data from Jukola 2019, a massive orienteering relay race, the model is shown to be highly accurate even when the size of the training set is only 5% of the whole data set. Numerical results also show that our model exhibits smaller place prediction root-mean-square-errors than linear regression, mord regression and Gaussian process regression.

Keywords: Fenton-Wilkinson approximation, German tank problem, log-normal distribution, order statistics, ordinal regression, orienteering, sports analytics, sports modeling

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Authors: Aaron Herve Mbwe Mbissik, Lotfi Khiari, Otmane Raji, Abdellatif Elghali, Abdelkarim Lajili, Muhammad Ouabid, Martin Jemo, Jean-Louis Bodinier

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Potassium (K) is an essential macronutrient for plant growth, helping to regulate several physiological and metabolic processes. Evaporite-related potash salts, mainly sylvite minerals (K chloride or KCl), are the principal source of K for the fertilizer industry. However, due to the high potash-supply risk associated with its considerable price fluctuations and uneven geographic distribution for most agriculture-based developing countries, the development of alternative sources of fertilizer K is imperative to maintain adequate crop yield, reduce yield gaps, and food security. Alkaline Igneous rocks containing significant K-rich silicate minerals such as K feldspar are increasingly seen as the best alternative available. However, these rocks may require to be hydrothermally treatment to enhance the release of potassium. In this study, we evaluate the fertilizing capacity of raw and hydrothermally treated K-bearing silicate rocks from different areas in Morocco. The effectiveness of rock powders was tested in a greenhouse experiment using ryegrass (Lolium multiflorum) by comparing them to a control (no K added) and to a conventional fertilizer (muriate of potash: MOP or KCl). The trial was conducted in a randomized complete block design with three replications, and plants were grown on K-depleted soils for three growing cycles. To achieve our objective, in addition to the analysis of the muriate response curve and the different biomasses, we also examined three necessary coefficients, namely: the K uptake, then apparent K recovery (AKR), and the relative K efficiency (RKE). The results showed that based on the optimum economic rate of MOP (230 kg.K.ha⁻¹) and the optimum yield (44 000 kg.K.ha⁻¹), the efficiency of K silicate rocks was as high as that of MOP. Although the plants took up only half of the K supplied by the powdered rock, the hydrothermal material was found to be satisfactory, with a biomass value reaching the optimum economic limit until the second crop cycle. In comparison, the AKR of the MOP (98.6%) and its RKE in the 1st cycle were higher than our materials: 39% and 38%, respectively. Therefore, the raw and hydrothermal materials mixture could be an appropriate solution for long-term agronomic use based on the obtained results.

Keywords: K-uptake, AKR, RKE, K-bearing silicate rock, MOP

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Authors: Takuro Kida, Yuichi Kida

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In this paper, it is shown a base of the new trend of algorithm mathematically that treats a historical reason of continuous discrimination in the world as well as its solution by introducing new concepts of parallel world that includes an invisible set of errors as its companion. With respect to a matrix operator-filter bank that the matrix operator-analysis-filter bank H and the matrix operator-sampling-filter bank S are given, firstly, we introduce the detail algorithm to derive the optimum matrix operator-synthesis-filter bank Z that minimizes all the worst-case measures of the matrix operator-error-signals E(ω) = F(ω) − Y(ω) between the matrix operator-input-signals F(ω) and the matrix operator-output-signals Y(ω) of the matrix operator-filter bank at the same time. Further, feedback is introduced to the above approximation theory, and it is indicated that introducing conversations with feedback do not superior automatically to the accumulation of existing knowledge of signal prediction. Secondly, the concept of category in the field of mathematics is applied to the above optimum signal approximation and is indicated that the category-based approximation theory is applied to the set-theoretic consideration of the recognition of humans. Based on this discussion, it is shown naturally why the narrow perception that tends to create isolation shows an apparent advantage in the short term and, often, why such narrow thinking becomes intimate with discriminatory action in a human group. Throughout these considerations, it is presented that, in order to abolish easy and intimate discriminatory behavior, it is important to create a parallel world of conception where we share the set of invisible error signals, including the words and the consciousness of both worlds.

Keywords: matrix filterbank, optimum signal approximation, category theory, simultaneous minimization

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Authors: Ghada El-Husseiny, Dina Yousri, Christian Richter

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Social services are often characterized by market failures, which justifies government intervention in the provision of these services. It is widely acknowledged that government intervention breeds corruption since resources are being transferred from one party to another. However, what is still being extensively studied is the magnitude of the negative impact of corruption on publicly provided services and development outcomes. Corruption has the power to hinder development and cripple our march towards the Sustainable Development Goals. Corruption diminishes the efficiency and effectiveness of public health and education spending and directly impacts the outcomes of these sectors. This paper empirically examines the impact of Institutional Failure on public sector services provision, with the sole purpose of studying the impact of corruption on SDG3 and 4; Good health and wellbeing and Quality education, respectively. The paper explores the effect of corruption on these goals from various perspectives and extends the analysis by examining if the impact of corruption on these goals differed when it accounted for the current corruption state. Using Pooled OLS(Ordinary Least Square) and Fixed effects panel estimation on 22 corrupt and 22 clean countries between 2000 and 2017. Results show that corruption in both corrupt and clean countries has a more severe impact on Health than the Education sector. In almost all specifications, corruption has an insignificant effect on School Enrollment rates but a significant effect on Infant Mortality rates. Results further indicate that, on average, a 1 point increase in the CPI(Consumer Price Index) can increase health expenditures by 0.116% in corrupt and clean countries. However, the fixed effects model indicates that the way Health and Education expenditures are determined in clean and corrupt countries are completely country-specific, in which corruption plays a minimal role. Moreover, the findings show that School Enrollment rates and Infant Mortality rates depend, to a large extent, on public spending. The most astounding results-driven is that corrupt countries, on average, have more effective and efficient healthcare expenditures. While some insights are provided as to why these results prevail, they should be further researched. All in all, corruption impedes development outcomes, and any Anti-corrupt policies taken will bring forth immense improvements and speed up the march towards sustainability.

Keywords: corruption, education, health, public spending, sustainable development

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Authors: Bi-Huei Tsai

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This work explores the inter-region investment behaviors of integrated circuit (IC) design industry from Taiwan to China using the amount of foreign direct investment (FDI). According to the mutual dependence among different IC design industrial locations, Lotka-Volterra model is utilized to explore the FDI interactions between South and East China. Effects of inter-regional collaborations on FDI flows into China are considered. Evolutions of FDIs into South China for IC design industry significantly inspire the subsequent FDIs into East China, while FDIs into East China for Taiwan’s IC design industry significantly hinder the subsequent FDIs into South China. The supply chain along IC industry includes IC design, manufacturing, packing and testing enterprises. I C manufacturing, packaging and testing industries depend on IC design industry to gain advanced business benefits. The FDI amount from Taiwan’s IC design industry into East China is the greatest among the four regions: North, East, Mid-West and South China. The FDI amount from Taiwan’s IC design industry into South China is the second largest. If IC design houses buy more equipment and bring more capitals in South China, those in East China will have pressure to undertake more FDIs into East China to maintain the leading position advantages of the supply chain in East China. On the other hand, as the FDIs in East China rise, the FDIs in South China will successively decline since capitals have concentrated in East China. Prediction of Lotka-Volterra model in FDI trends is accurate because the industrial interactions between the two regions are included. Finally, this work confirms that the FDI flows cannot reach a stable equilibrium point, so the FDI inflows into East and South China will expand in the future.

Keywords: Lotka-Volterra model, foreign direct investment, competitive, Equilibrium analysis

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Authors: Theresa Ukamaka Nwagha, Angela Ogechukwu Ugwu, Martins Nweke

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Background and Objectives: Blood transfusion is an effective and proven treatment for some severe complications of sickle cell disease. Recurrent transfusions have put patients with sickle cell disease at risk of developing antibodies against the various antigens they were exposed to. This study aims to investigate the frequency of red blood cell alloimmunization in patients with sickle disease in Africa. Materials and Methods: This is a systematic review of peer-reviewed literature published in English. The review was conducted consistent with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses checklist. Data sources for the review include MEDLINE, PubMed, CINAHL, and Academic Search Complete. Included in this review are articles that reported the frequency/prevalence of red blood cell alloimmunization in sickle cell disease patients in Africa. Eligible studies were subjected to independent full-text screening and data extraction. Risk of bias assessment was conducted with the aid of the mixed method appraisal tool. We employed a random-effects model of meta-analysis to estimate the pooled prevalence. We computed Cochrane’s Q statistics and I2 and prediction interval to quantify heterogeneity in effect size. Results: The prevalence estimates range from 2.6% to 29%. Pooled prevalence was estimated to be 10.4% (CI 7.7.–13.8); PI = 3.0 – 34.0%), with significant heterogeneity (I2 = 84.62; PI = 2.0-32.0%) and publication bias (Egger’s t-test = 1.744, p = 0.0965). Conclusion: The frequency of red cell alloantibody varies considerably in Africa. The alloantibodies appeared frequent in this order: the Rhesus, Kell, Lewis, Duffy, MNS, and Lutheran

Keywords: frequency, red blood cell, alloimmunization, sickle cell disease, Africa

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Authors: Łukasz Ambroziak

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Although the impact of the production fragmentation on trade flows has been examined many times since the 1990s, the research was not comprehensive because of the limitations in traditional trade statistics. Early 2010s the complex databases containing world input-output tables (or indicators calculated on their basis) has made available. It increased the possibilities of examining the production sharing in the world. The trade statistic in value-added terms enables us better to estimate trade changes resulted from the internationalisation and globalisation as well as benefits of the countries from international trade. In the literature, there are many research studies on this topic. Unfortunately, trade in value added of the Central and Eastern European Countries (CEECs) has been so far insufficiently studied. Thus, the aim of the paper is to present changes in value added trade of the CEECs (Bulgaria, the Czech Republic, Estonia, Hungary, Latvia, Lithuania, Poland, Romania, Slovakia and Slovenia) in the period of 1995-2011. The concept 'trade in value added' or 'value added trade' is defined as the value added of a country which is directly and indirectly embodied in final consumption of another country. The typical question would be: 'How much value added is created in a country due to final consumption in the other countries?' The data will be downloaded from the World Input-Output Database (WIOD). The structure of this paper is as follows. First, theoretical and methodological aspects related to the application of the input-output tables in the trade analysis will be studied. Second, a brief survey of the empirical literature on this topic will be presented. Third, changes in exports and imports in value added of the CEECs will be analysed. A special attention will be paid to the differences in bilateral trade balances using traditional trade statistics (in gross terms) on one side, and value added statistics on the other. Next, in order to identify factors influencing value added exports and value added imports of the CEECs the generalised gravity model, based on panel data, will be used. The dependent variables will be value added exports and imports. The independent variables will be, among others, the level of GDP of trading partners, the level of GDP per capita of trading partners, the differences in GDP per capita, the level of the FDI inward stock, the geographical distance, the existence (or non-existence) of common border, the membership (or not) in preferential trade agreements or in the EU. For comparison, an estimation will also be made based on exports and imports in gross terms. The initial research results show that the gravity model better explained determinants of trade in value added than gross trade (R2 in the former is higher). The independent variables had the same direction of impact both on value added exports/imports and gross exports/imports. Only value of coefficients differs. The most difference concerned geographical distance. It had smaller impact on trade in value added than gross trade.

Keywords: central and eastern European countries, gravity model, input-output tables, trade in value added

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Authors: Muhammed Ashiq Villanthenkodath, Shreya Pal

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

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

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Authors: Zhongmin Wang, Wudong Fan, Hengshan Zhang, Yimin Zhou

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In data-driven prognostic methods, the prediction accuracy of the estimation for remaining useful life of bearings mainly depends on the performance of health indicators, which are usually fused some statistical features extracted from vibrating signals. However, the existing health indicators have the following two drawbacks: (1) The differnet ranges of the statistical features have the different contributions to construct the health indicators, the expert knowledge is required to extract the features. (2) When convolutional neural networks are utilized to tackle time-frequency features of signals, the time-series of signals are not considered. To overcome these drawbacks, in this study, the method combining convolutional neural network with gated recurrent unit is proposed to extract the time-frequency image features. The extracted features are utilized to construct health indicator and predict remaining useful life of bearings. First, original signals are converted into time-frequency images by using continuous wavelet transform so as to form the original feature sets. Second, with convolutional and pooling layers of convolutional neural networks, the most sensitive features of time-frequency images are selected from the original feature sets. Finally, these selected features are fed into the gated recurrent unit to construct the health indicator. The results state that the proposed method shows the enhance performance than the related studies which have used the same bearing dataset provided by PRONOSTIA.

Keywords: continuous wavelet transform, convolution neural net-work, gated recurrent unit, health indicators, remaining useful life

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Authors: Tugba Bayoglu

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Aerodynamic parameter estimation is very crucial in missile design phase, since accurate high fidelity aerodynamic model is required for designing high performance and robust control system, developing high fidelity flight simulations and verification of computational and wind tunnel test results. However, in literature, there is not enough missile aerodynamic parameter identification study for three main reasons: (1) most air to air missiles cannot fly with constant speed, (2) missile flight test number and flight duration are much less than that of fixed wing aircraft, (3) variation of the missile aerodynamic parameters with respect to Mach number is higher than that of fixed wing aircraft. In addition to these challenges, identification of aerodynamic parameters for high wind angles by using classical estimation techniques brings another difficulty in the estimation process. The reason for this, most of the estimation techniques require employing polynomials or splines to model the behavior of the aerodynamics. However, for the missiles with a large variation of aerodynamic parameters with respect to flight variables, the order of the proposed model increases, which brings computational burden and complexity. Therefore, in this study, it is aimed to solve nonlinear aerodynamic parameter identification problem for a supersonic air to air missile by using Artificial Neural Networks. The method proposed will be tested by using simulated data which will be generated with a six degree of freedom missile model, involving a nonlinear aerodynamic database. The data will be corrupted by adding noise to the measurement model. Then, by using the flight variables and measurements, the parameters will be estimated. Finally, the prediction accuracy will be investigated.

Keywords: air to air missile, artificial neural networks, open loop simulation, parameter identification

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Authors: Lusi Susanti, Prima Fithri

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The rapid growth of Indonesia population is directly proportional to the energy needs of the country, but not all of Indonesian population can relish the electricity. Indonesia's electrification ratio is still around 80.1%, which means that approximately 19.9% of households in Indonesia have not been getting the flow of electrical energy. Household electricity consumptions in Indonesia are generally still dominated by the public urban. In the city of Padang, West Sumatera, Indonesia, about 94.10% are power users of government services (PLN). The most important thing of the issue is human resources efficient energy. User behavior in utilizing electricity becomes significant. However repair solution will impact the user's habits sustainable energy issues. This study attempts to identify the user behavior and lifestyle that affect household electricity consumption and to evaluate the potential for energy saving. The behavior component is frequently underestimated or ignored in analyses of household electrical energy end use, partly because of its complexity. It is influenced by socio-demographic factors, culture, attitudes, aesthetic norms and comfort, as well as social and economic variables. Intensive questioner survey, in-depth interview and statistical analysis are carried out to collect scientific evidences of the behavioral based changes instruments to reduce electricity consumption in household sector. The questioner was developed to include five factors assuming affect the electricity consumption pattern in household sector. They are: attitude, energy price, household income, knowledge and other determinants. The survey was carried out in Padang, West Sumatra Province Indonesia. About 210 questioner papers were proportionally distributed to households in 11 districts in Padang. Stratified sampling was used as a method to select respondents. The results show that the household size, income, payment methods and size of house are factors affecting electricity saving behavior in residential sector. Household expenses on electricity are strongly influenced by gender, type of job, level of education, size of house, income, payment method and level of installed power. These results provide a scientific evidence for stakeholders on the potential of controlling electricity consumption and designing energy policy by government in residential sector.

Keywords: electricity, energy saving, household, behavior, policy

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Authors: Mohammed Saleh Rezk, Reza Kashani

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Auxiliary damping has gained popularity in recent years, especially in structures such as mid- and high-rise buildings. Distributed damping systems (typically viscous and viscoelastic) or reactive damping systems (such as tuned mass dampers) are the two types of damping choices for such structures. Distributed VE dampers are normally configured as braces or damping panels, which are engaged through relatively small movements between the structural members when the structure sways under wind or earthquake loading. In addition to being used as stand-alone dampers in distributed damping applications, VE dampers can also be incorporated into the suspension element of tuned mass dampers (TMDs). In this study, analytical and numerical tools for modeling and design of multilayer viscoelastic damping devices to be used in dampening the vibration of large structures are developed. Considering the limitations of analytical models for the synthesis and analysis of realistic, large, multilayer VE dampers, the emphasis of the study has been on numerical modeling using the finite element method. To verify the finite element models, a two-layer VE damper using ½ inch synthetic viscoelastic urethane polymer was built, tested, and the measured parameters were compared with the numerically predicted ones. The numerical model prediction and experimentally evaluated damping and stiffness of the test VE damper were in very good agreement. The effectiveness of VE dampers in adding auxiliary damping to larger structures is numerically demonstrated by chevron bracing one such damper numerically into the model of a massive frame subject to an abrupt lateral load. A comparison of the responses of the frame to the aforementioned load, without and with the VE damper, clearly shows the efficacy of the damper in lowering the extent of frame vibration.

Keywords: viscoelastic, damper, distributed damping, tuned mass damper

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Authors: Ashirgul Kozhagulova, Ainash Shabdirova, Galym Tokazhanov, Minh Nguyen

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The synthetic rocks have been advantageous over the natural rocks in terms of availability and the consistent studying the impact of a particular parameter. The artificial rocks can be fabricated using variety of techniques such as mixing sand and Portland cement or gypsum, firing the mixture of sand and fine powder of borosilicate glass or by in-situ precipitation of calcite solution. In this study, sodium silicate solution has been used as the cementing agent for the quartz sand. The molded soft cylindrical sandstone samples are placed in the gas-tight pressure vessel, where the hardening of the material takes place as the chemical reaction between carbon dioxide and the silicate solution progresses. The vessel allows uniform disperse of carbon dioxide and control over the ambient gas pressure. Current paper shows how the bonding material is initially distributed in the intergranular space and the surface of the sand particles by the usage of Electron Microscopy and the Energy Dispersive Spectroscopy. During the study, the strength of the cement bond as a function of temperature is observed. The impact of cementing agent dosage on the micro and macro characteristics of the sandstone is investigated. The analysis of the cement bond at micro level helps to trace the changes to particles bonding damage after a potential yielding. Shearing behavior and compressional response have been examined resulting in the estimation of the shearing resistance and cohesion force of the sandstone. These are considered to be main input values to the mathematical prediction models of sand production from weak clastic oil reservoir formations.

Keywords: artificial sanstone, cement bond, microstructure, SEM, triaxial shearing

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Authors: Ashis Mallick, Rajeev Ranjan

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The closed form solution for thermal stresses in an annular fin with hyperbolic profile is derived using Adomian decomposition method (ADM). The conductive-convective fin with variable thermal conductivity is considered in the analysis. The nonlinear heat transfer equation is efficiently solved by ADM considering insulated convective boundary conditions at the tip of fin. The constant of integration in the solution is to be estimated using minimum decomposition error method. The solution of temperature field is represented in a polynomial form for convenience to use in thermo-elasticity equation. The non-dimensional thermal stress fields are obtained using the ADM solution of temperature field coupled with the thermo-elasticity solution. The influence of the various thermal parameters in temperature field and stress fields are presented. In order to show the accuracy of the ADM solution, the present results are compared with the results available in literature. The stress fields in fin with hyperbolic profile are compared with those of uniform thickness profile. Result shows that hyperbolic fin profile is better choice for enhancing heat transfer. Moreover, less thermal stresses are developed in hyperbolic profile as compared to rectangular profile. Next, Nelder-Mead based simplex search method is employed for the inverse estimation of unknown non-dimensional thermal parameters in a given stress fields. Owing to the correlated nature of the unknowns, the best combinations of the model parameters which are satisfying the predefined stress field are to be estimated. The stress fields calculated using the inverse parameters give a very good agreement with the stress fields obtained from the forward solution. The estimated parameters are suitable to use for efficient and cost effective fin designing.

Keywords: Adomian decomposition, inverse analysis, hyperbolic fin, variable thermal conductivity

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Authors: Omar Bouledroua, Djamel Zelmati, Zahreddine Hafsi, Milos B. Djukic

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Transporting hydrogen gas through the existing natural gas pipeline network offers an efficient solution for energy storage and conveyance. Hydrogen generated from excess renewable electricity can be conveyed through the API 5L steel-made pipelines that already exist. In recent years, there has been a growing demand for the transportation of hydrogen through existing gas pipelines. Therefore, numerical and experimental tests are required to verify and ensure the mechanical integrity of the API 5L steel pipelines that will be used for pressurized hydrogen transportation. Internal pressure loading is likely to accelerate hydrogen diffusion through the internal pipe wall and consequently accentuate the hydrogen embrittlement of steel pipelines. Furthermore, pre-cracked pipelines are susceptible to quick failure, mainly under a time-dependent cyclic pressure loading that drives fatigue crack propagation. Meanwhile, after several loading cycles, the initial cracks will propagate to a critical size. At this point, the remaining service life of the pipeline can be estimated, and inspection intervals can be determined. This paper focuses on the hydrogen embrittlement of API 5L steel-made pipeline under cyclic pressure loading. Pressurized hydrogen gas is transported through a network of pipelines where demands at consumption nodes vary periodically. The resulting pressure profile over time is considered a cyclic loading on the internal wall of a pre-cracked pipeline made of API 5L steel-grade material. Numerical modeling has allowed the prediction of fatigue crack evolution and estimation of the remaining service life of the pipeline. The developed methodology in this paper is based on the ASME B31.12 standard, which outlines the guidelines for hydrogen pipelines.

Keywords: hydrogen embrittlement, pipelines, transient flow, cyclic pressure, fatigue crack growth

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Authors: Mauro Iannazzone, Carmine D'Agostino

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Off-shore wind turbines are currently considered as a reliable source of renewable energy Worldwide and especially in the UK. Most of the operational off-shore wind turbines located in shallow waters (i.e. < 30 m) are supported on monopiles. Monopiles are open-ended steel tubes with diameter ranging between 4 to 6 m. It is expected that future off-shore wind farms will be located in water depths as high as 70 m. Therefore, alternative foundation arrangements are needed. Foundations for off-shore structures normally consist of open-ended piles driven into the soil by means of impact hammers. During pile installation, the soil inside the pile may be mobilized by the increasing shear strength such as to prevent more soil from entering the pile. This phenomenon is known as soil plugging, and represents an important issue as it may change significantly the driving resistance of open-ended piles. In fact, if the plugging formation is unexpected, the installation may require more powerful and more expensive hammers. Engineers need to estimate whether the driven pile will be installed in a plugged or unplugged mode. As a consequence, a prediction of the degree of soil plugging is required in order to correctly predict the drivability of the pile. This work presents a brief review of the state-of-the-art of pile driving and approaches used to predict formation of soil plugs. In addition, a novel analytical approach is proposed, which is based on the vertical equilibrium of a plugged pile. Differently from previous studies, this research takes into account the enhancement of the stress within the soil plug. Finally, the work presents and discusses a series of experimental tests, which are carried out on small-scale models piles to validate the analytical solution.

Keywords: off-shore wind turbines, pile installation, soil plugging, wind energy

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Authors: Tegene Nigussie

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Introduction: Maize is the most domesticated of all the field crops. Wild maize has not been found to date and there has been much speculation on its origin. Regardless of the validity of different theories, it is generally agreed that the center of origin of maize is Central America, primarily Mexico and the Caribbean. Maize in Africa is of a recent introduction although data suggest that it was present in Nigeria even before Columbus voyages. After being taken to Europe in 1493, maize was introduced to Africa and distributed through the continent by different routes. Maize is an important cereal crop in Ethiopia. In general, it is the primarily stable food, and rural households show a strong preference. For human food, the important constituents of grain are carbohydrates (starch and sugars), protein, fat or oil (in the embryo) and minerals. About 75 percent of the kernel is starch, a range of 60.80 percent, but low protein content (8-15). In Ethiopia, the introduction of modern farming techniques appears to be a priority. However, the adoption of modern inputs by peasant farmers is found to be very slow; for example, the adoption rate of fertilizer, an input that is relatively adopted, is very slow. The difference socio economic factors lied behind the low rate of technology adoption, including price &marketing input. Objective: The objective of this study is to determine the optimum application rate or level of different nitrogen fertilizers for the vegetative growth of maize and to identify the effect of different nitrogen rates on the growth and development of maize. Methods: The vegetative parameter (above ground) measurement from five plants randomly sampled from the middle rows of each plot. Results: The interaction of nitrogen and maize variety showed a significant at (p<0.01) effect on plant height, with the application of 60kg/ha and BH140 maize variety in combination and root length with the application of 60kg/ha of nitrogen and BH140 variety of maize. The highest mean (12.33) of the number of leaves per plant and mean (7.1) of the number of nodes per plant can be used as an alternative for better vegetative growth of maize. Conclusion: Maize is one of the most popular and cultivated crops in Ethiopia. The study was conducted to investigate the best dosage of nitrogen for vegetative growth, yield, and better quality of maize variety and to recommend a level of nitrogen rate and the best variety adaptable to the specific soil condition or area.

Keywords: parameter, chlorosis, germination, flood, sesbania, cultivar

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Authors: Levente Kovács, Fruzsina Luca Kézér, Ottó Szenci

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Prediction of the onset of calving and recognizing difficulties at calving has great importance in decreasing neonatal losses and reducing the risk of health problems in the early postpartum period. In this study, changes of rumination time, reticuloruminal pH and temperature were investigated in eutocic (EUT, n = 10) and dystocic (DYS, n = 8) dairy cows around parturition. Rumination time was continuously recorded using an acoustic biotelemetry system, whereas reticuloruminal pH and temperature were recorded using an indwelling and wireless data transmitting system. The recording period lasted from 3 d before calving until 7 days in milk. For the comparison of rumination time and reticuloruminal characteristics between groups, time to return to baseline (the time interval required to return to baseline from the delivery of the calf) and area under the curve (AUC, both for prepartum and postpartum periods) were calculated for each parameter. Rumination time decreased from baseline 28 h before calving both for EUT and DYS cows (P = 0.023 and P = 0.017, respectively). After 20 h before calving, it decreased onwards to reach 32.4 ± 2.3 and 13.2 ± 2.0 min/4 h between 8 and 4 h before delivery in EUT and DYS cows, respectively, and then it decreased below 10 and 5 min during the last 4 h before calving (P = 0.003 and P = 0.008, respectively). Until 12 h after delivery rumination time reached 42.6 ± 2.7 and 51.0 ± 3.1 min/4 h in DYS and EUT dams, respectively, however, AUC and time to return to baseline suggested lower rumination activity in DYS cows than in EUT dams for the 168-h postpartum observational period (P = 0.012 and P = 0.002, respectively). Reticuloruminal pH decreased from baseline 56 h before calving both for EUT and DYS cows (P = 0.012 and P = 0.016, respectively), but did not differ between groups before delivery. In DYS cows, reticuloruminal temperature decreased from baseline 32 h before calving by 0.23 ± 0.02 °C (P = 0.012), whereas in EUT cows such a decrease was found only 20 h before delivery (0.48 ± 0.05 °C, P < 0.01). AUC of reticuloruminal temperature calculated for the prepartum period was greater in EUT cows than in DYS cows (P = 0.042). During the first 4 h after calving, it decreased from 39.7 ± 0.1 to 39.00 ± 0.1 °C and from 39.8 ± 0.1 to 38.8 ± 0.1 °C in EUT and DYS cows, respectively (P < 0.01 for both groups) and reached baseline levels after 35.4 ± 3.4 and 37.8 ± 4.2 h after calving in EUT and DYS cows, respectively. Based on our results, continuous monitoring of changes in rumination time and reticuloruminal temperature seems to be promising in the early detection of cows with a higher risk of dystocia. Depressed postpartum rumination time of DYS cows highlights the importance of the monitoring of cows experiencing difficulties at calving.

Keywords: reticuloruminal pH, reticuloruminal temperature, rumination time, dairy cows, dystocia

Procedia PDF Downloads 306

Authors: N. D. Iswarya, M. A. Maluk Mohamed, N. Vijaya

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Grid is infrastructure that allows the deployment of distributed data in large size from multiple locations to reach a common goal. Scheduling data intensive applications becomes challenging as the size of data sets are very huge in size. Only two solutions exist in order to tackle this challenging issue. First, computation which requires huge data sets to be processed can be transferred to the data site. Second, the required data sets can be transferred to the computation site. In the former scenario, the computation cannot be transferred since the servers are storage/data servers with little or no computational capability. Hence, the second scenario can be considered for further exploration. During scheduling, transferring huge data sets from one site to another site requires more network bandwidth. In order to mitigate this issue, this work focuses on incorporating cognitive science in scheduling. Cognitive Science is the study of human brain and its related activities. Current researches are mainly focused on to incorporate cognitive science in various computational modeling techniques. In this work, the problem solving approach of human brain is studied and incorporated during the data intensive scheduling in grid environments. Here, a cognitive engine is designed and deployed in various grid sites. The intelligent agents present in CE will help in analyzing the request and creating the knowledge base. Depending upon the link capacity, decision will be taken whether to transfer data sets or to partition the data sets. Prediction of next request is made by the agents to serve the requesting site with data sets in advance. This will reduce the data availability time and data transfer time. Replica catalog and Meta data catalog created by the agents assist in decision making process.

Keywords: data grid, grid workflow scheduling, cognitive artificial intelligence

Procedia PDF Downloads 382

Authors: Richard Sogah

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The significance of transport infrastructure investments for economic growth and development has been central to the World Bank’s strategy for poverty reduction. Among the conventional surface transport infrastructures, road infrastructure is significant in facilitating the movement of human capital goods and services. When transport projects (i.e., roads, super-highways) are implemented, they come along with some negative social values (costs), such as increased noise and air pollution for local residents living near these facilities, displaced individuals, etc. However, these projects also facilitate better utilization of existing capital stock and generate other observable benefits that can be easily quantified. For example, the improvement or construction of roads creates employment, stimulates revenue generation (toll), reduces vehicle operating costs and accidents, increases accessibility, trade expansion, safety improvement, etc. Aside from these benefits, travel time savings (TTSs) which are the major economic benefits of urban and inter-urban transport projects and therefore integral in the economic assessment of transport projects, are often overlooked and omitted when estimating the benefits of transport projects, especially in developing countries. The absence of current and reliable domestic travel data and the inability of replicated models from the developed world to capture the actual value of travel time savings due to the large unemployment, underemployment, and other labor-induced distortions has contributed to the failure to assign value to travel time savings when estimating the benefits of transport schemes in developing countries. This omission of the value of travel time savings from the benefits of transport projects in developing countries poses problems for investors and stakeholders to either accept or dismiss projects based on schemes that favor reduced vehicular operating costs and other parameters rather than those that ease congestion, increase average speed, facilitate walking and handloading, and thus save travel time. Given the complex reality in the estimation of the value of travel time savings and the presence of widespread informal labour activities in Sub-Saharan Africa, we construct a “nationally ranked distribution of time values” and estimate the value of travel time savings based on the area beneath the distribution. Compared with other approaches, our method captures both formal sector workers and individuals/people who work outside the formal sector and hence changes in their time allocation occur in the informal economy and household production activities. The dataset for the estimations is sourced from the World Bank, the International Labour Organization, etc.

Keywords: road infrastructure, transport projects, travel time savings, congestion, Sub-Sahara Africa

Procedia PDF Downloads 93

Authors: Didier Auroux, Vladimir Groza

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This work is part of STEEP Marie-Curie ITN project, and it focuses on the identification of unknown parameters of the proposed generic Abrasive WaterJet Milling (AWJM) PDE model, that appears as an ill-posed inverse problem. The necessity of studying this problem comes from the industrial milling applications where the possibility to predict and model the final surface with high accuracy is one of the primary tasks in the absence of any knowledge of the model parameters that should be used. In this framework, we propose the identification of model parameters by minimizing a cost function, measuring the difference between experimental and numerical solutions. The adjoint approach based on corresponding Lagrangian gives the opportunity to find out the unknowns of the AWJM model and their optimal values that could be used to reproduce the required trench profile. Due to the complexity of the nonlinear problem and a large number of model parameters, we use an automatic differentiation software tool (TAPENADE) for the adjoint computations. By adding noise to the artificial data, we show that in fact the parameter identification problem is highly unstable and strictly depends on input measurements. Regularization terms could be effectively used to deal with the presence of data noise and to improve the identification correctness. Based on this approach we present results in 2D and 3D of the identification of the model parameters and of the surface prediction both with self-generated data and measurements obtained from the real production. Considering different types of model and measurement errors allows us to obtain acceptable results for manufacturing and to expect the proper identification of unknowns. This approach also gives us the ability to distribute the research on more complex cases and consider different types of model and measurement errors as well as 3D time-dependent model with variations of the jet feed speed.

Keywords: Abrasive Waterjet Milling, inverse problem, model parameters identification, regularization

Procedia PDF Downloads 305

Authors: Moses Jenkins

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Much of the focus when improving energy efficiency in buildings fall on the raising of standards within new build dwellings. However, as a significant proportion of the building stock across Europe is of historic or traditional construction, there is also a pressing need to improve the thermal performance of structures of this sort. On average, around twenty percent of buildings across Europe are built of historic masonry construction. In order to meet carbon reduction targets, these buildings will require to be retrofitted with insulation to improve their thermal performance. At the same time, there is also a need to balance this with maintaining the ability of historic masonry construction to allow moisture movement through building fabric to take place. This moisture transfer, often referred to as 'breathable construction', is critical to the success, or otherwise, of retrofit projects. The significance of this paper is to demonstrate that substantial thermal improvements can be made to historic buildings whilst avoiding damage to building fabric through surface or interstitial condensation. The paper will analyze the results of a wide range of retrofit measures installed to twenty buildings as part of Historic Environment Scotland's technical research program. This program has been active for fourteen years and has seen interventions across a wide range of building types, using over thirty different methods and materials to improve the thermal performance of historic buildings. The first part of the paper will present the range of interventions which have been made. This includes insulating mass masonry walls both internally and externally, warm and cold roof insulation and improvements to floors. The second part of the paper will present the results of monitoring work which has taken place to these buildings after being retrofitted. This will be in terms of both thermal improvement, expressed as a U-value as defined in BS EN ISO 7345:1987, and also, crucially, will present the results of moisture monitoring both on the surface of masonry walls the following retrofit and also within the masonry itself. The aim of this moisture monitoring is to establish if there are any problems with interstitial condensation. This monitoring utilizes Interstitial Hygrothermal Gradient Monitoring (IHGM) and similar methods to establish relative humidity on the surface of and within the masonry. The results of the testing are clear and significant for retrofit projects across Europe. Where a building is of historic construction the use of materials for wall, roof and floor insulation which are permeable to moisture vapor provides both significant thermal improvements (achieving a u-value as low as 0.2 Wm²K) whilst avoiding problems of both surface and intestinal condensation. As the evidence which will be presented in the paper comes from monitoring work in buildings rather than theoretical modeling, there are many important lessons which can be learned and which can inform retrofit projects to historic buildings throughout Europe.

Keywords: insulation, condensation, masonry, historic

Procedia PDF Downloads 159

Authors: Idris M. Olatunde, Kareem B.

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In manufacturing systems, especially job shops, service performance is a key factor that determines customer satisfaction. Service performance depends not only on the quality of the output but on the delivery lead times as well. Besides product quality enhancement, delivery lead time must be minimized for optimal patronage. Quoting accurate due dates is sine quo non for job shop operational survival in a global competitive environment. Quoting accurate due dates in job shops has been a herculean task that nearly defiled solutions from many methods employed due to complex jobs routing nature of the system. This class of NP-hard problems possessed no rigid algorithms that can give an optimal solution. Jobshop operational problem is more complex in developing nations due to some peculiar factors. Operational complexity in job shops emanated from political instability, poor economy, technological know-how, and the non-promising socio-political environment. The mentioned exogenous factors were hardly considered in the previous studies on scheduling problem related to due date determination in job shops. This study has filled the gap created in the past studies by developing a dynamic model that incorporated the exogenous factors for accurate determination of due dates for varying jobs complexity. Real data from six job shops selected from the different part of Nigeria, were used to test the efficacy of the model, and the outcomes were analyzed statistically. The results of the analyzes showed that the model is more promising in determining accurate due dates than the traditional models deployed by many job shops in terms of patronage and lead times minimization.

Keywords: due dates prediction, improved performance, customer satisfaction, dynamic model, exogenous factors, job shops

Procedia PDF Downloads 402

Authors: Gajanan M. Sonwane

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Nowadays, the entire pharmaceutical industry is facing the challenge of increasing efficiency and innovation. The major hurdles are the growing cost of research and development and a concurrent stagnating number of new chemical entities (NCEs). Hence, the challenge is to select the most druggable targets and to search the equivalent drug-like compounds, which also possess specific pharmacokinetic and toxicological properties that allow them to be developed as drugs. The present research work includes the studies of developing new anticancer heterocycles by using molecular modeling techniques. The heterocycles synthesized through such methodology are much effective as various physicochemical parameters have been already studied and the structure has been optimized for its best fit in the receptor. Hence, on the basis of the literature survey and considering the need to develop newer anticancer agents, new phenazinamine derivatives were designed by subjecting the nucleus to molecular modeling, viz., GQSAR analysis and docking studies. Simultaneously, these designed derivatives were subjected to in silico prediction of biological activity through PASS studies and then in silico toxicity risk assessment studies. In PASS studies, it was found that all the derivatives exhibited a good spectrum of biological activities confirming its anticancer potential. The toxicity risk assessment studies revealed that all the derivatives obey Lipinski’s rule. Amongst these series, compounds 4c, 5b and 6c were found to possess logP and drug-likeness values comparable with the standard Imatinib (used for anticancer activity studies) and also with the standard drug methotrexate (used for antimitotic activity studies). One of the most notable mutations is the threonine to isoleucine mutation at codon 315 (T315I), which is known to be resistant to all currently available TKI. Enzyme assay planned for confirmation of target selective activity.

Keywords: drug design, tyrosine kinases, anticancer, Phenazinamine

Procedia PDF Downloads 104

Authors: Maryam Zarabian, Hector Guzman, Pedro Pereira-Almao, Abraham Fapojuwo

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Dry reforming of methane (DRM) has sparked significant industrial and scientific interest not only as a viable alternative for addressing the environmental concerns of two main contributors of the greenhouse effect, i.e., carbon dioxide (CO₂) and methane (CH₄), but also produces syngas, i.e., a mixture of hydrogen (H₂) and carbon monoxide (CO) utilized by a wide range of downstream processes as a feedstock for other chemical productions. In this study, we develop an AI-enable syngas production model to tackle the problem of achieving an equivalent H₂/CO ratio [1:1] with respect to the most efficient conversion. Firstly, the unsupervised density-based spatial clustering of applications with noise (DBSAN) algorithm removes outlier data points from the original experimental dataset. Then, random forest (RF) and deep neural network (DNN) models employ the error-free dataset to predict the DRM results. DNN models inherently would not be able to obtain accurate predictions without a huge dataset. To cope with this limitation, we employ reusing pre-trained layers’ approaches such as transfer learning and greedy layer-wise pretraining. Compared to the other deep models (i.e., pure deep model and transferred deep model), the greedy layer-wise pre-trained deep model provides the most accurate prediction as well as similar accuracy to the RF model with R² values 1.00, 0.999, 0.999, 0.999, 0.999, and 0.999 for the total outlet flow, H₂/CO ratio, H₂ yield, CO yield, CH₄ conversion, and CO₂ conversion outputs, respectively.

Keywords: artificial intelligence, dry reforming of methane, artificial neural network, deep learning, machine learning, transfer learning, greedy layer-wise pretraining

Procedia PDF Downloads 71

Authors: K. Geetha Ramesh, A. Ramachandraiah

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In an internal building space, daylight becomes a powerful source of illumination. The challenge therefore, is to develop means of utilizing both direct and diffuse natural light in buildings while maintaining and improving occupant's visual comfort, particularly at greater distances from the windows throwing daylight. The geometrical features of windows in a building have significant effect in providing daylight. The main goal of this research is to develop an innovative window geometry, which will effectively provide the daylight component adequately together with internal reflected component(IRC) and also the external reflected component(ERC), if any. This involves exploration of a light redirecting system using fractal geometry for windows, in order to penetrate and distribute daylight more uniformly to greater depths, minimizing heat gain and glare, and also to reduce building energy use substantially. Of late the creation of fractal geometrical window and the occurrence of daylight illuminance due to such windows is becoming an interesting study. The amount of daylight can change significantly based on the window geometry and sky conditions. This leads to the (i) exploration of various fractal patterns suitable for window designs, and (ii) quantification of the effect of chosen fractal window based on the relationship between the fractal pattern, size, orientation and glazing properties for optimizing daylighting. There are a lot of natural lighting applications able to predict the behaviour of a light in a room through a traditional opening - a regular window. The conventional prediction methodology involves the evaluation of the daylight factor, the internal reflected component and the external reflected component. Having evaluated the daylight illuminance level for a conventional window, the technical performance of a fractal window for an optimal daylighting is to be studied and compared with that of a regular window. The methodologies involved are highlighted in this paper.

Keywords: daylighting, fractal geometry, fractal window, optimization

Procedia PDF Downloads 291