Search results for: reduced order macro models
21885 Cement Bond Characteristics of Artificially Fabricated Sandstones
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
Procedia PDF Downloads 16921884 Performance Evaluation of Polyethyleneimine/Polyethylene Glycol Functionalized Reduced Graphene Oxide Membranes for Water Desalination via Forward Osmosis
Authors: Mohamed Edokali, Robert Menzel, David Harbottle, Ali Hassanpour
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Forward osmosis (FO) process has stood out as an energy-efficient technology for water desalination and purification, although the practical application of FO for desalination still relies on RO-based Thin Film Composite (TFC) and Cellulose Triacetate (CTA) polymeric membranes which have a low performance. Recently, graphene oxide (GO) laminated membranes have been considered an ideal selection to overcome the bottleneck of the FO-polymeric membranes owing to their simple fabrication procedures, controllable thickness and pore size and high water permeability rates. However, the low stability of GO laminates in wet and harsh environments is still problematic. The recent developments of modified GO and hydrophobic reduced graphene oxide (rGO) membranes for FO desalination have demonstrated attempts to overcome the ongoing trade-off between desalination performance and stability, which is yet to be achieved prior to the practical implementation. In this study, acid-functionalized GO nanosheets cooperatively reduced and crosslinked by the hyperbranched polyethyleneimine (PEI) and polyethylene glycol (PEG) polymers, respectively, are applied for fabrication of the FO membrane, to enhance the membrane stability and performance, and compared with other functionalized rGO-FO membranes. PEI/PEG doped rGO membrane retained two compacted d-spacings (0.7 and 0.31 nm) compared to the acid-functionalized GO membrane alone (0.82 nm). Besides increasing the hydrophilicity, the coating layer of PEG onto the PEI-doped rGO membrane surface enhanced the structural integrity of the membrane chemically and mechanically. As a result of these synergetic effects, the PEI/PEG doped rGO membrane exhibited a water permeation of 7.7 LMH, salt rejection of 97.9 %, and reverse solute flux of 0.506 gMH at low flow rates in the FO desalination process.Keywords: desalination, forward osmosis, membrane performance, polyethyleneimine, polyethylene glycol, reduced graphene oxide, stability
Procedia PDF Downloads 9921883 Understanding the Effects of Lamina Stacking Sequence on Structural Response of Composite Laminates
Authors: Awlad Hossain
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Structural weight reduction with improved functionality is one of the targeted desires of engineers, which drives materials and structures to be lighter. One way to achieve this objective is through the replacement of metallic structures with composites. The main advantages of composite materials are to be lightweight and to offer high specific strength and stiffness. Composite materials can be classified in various ways based on the fiber types and fiber orientations. Fiber reinforced composite laminates are prepared by stacking single sheet of continuous fibers impregnated with resin in different orientation to get the desired strength and stiffness. This research aims to understand the effects of Lamina Stacking Sequence (LSS) on the structural response of a symmetric composite laminate, defined by [0/60/-60]s. The Lamina Stacking Sequence (LSS) represents how the layers are stacked together in a composite laminate. The [0/60/-60]s laminate represents a composite plate consists of 6 layers of fibers, which are stacked at 0, 60, -60, -60, 60 and 0 degree orientations. This laminate is also called symmetric (defined by subscript s) as it consists of same material and having identical fiber orientations above and below the mid-plane. Therefore, the [0/60/-60]s, [0/-60/60]s, [60/-60/0]s, [-60/60/0]s, [60/0/-60]s, and [-60/0/60]s represent the same laminate but with different LSS. In this research, the effects of LSS on laminate in-plane and bending moduli was investigated first. The laminate moduli dictate the in-plane and bending deformations upon loading. This research also provided all the setup and techniques for measuring the in-plane and bending moduli, as well as how the stress distribution was assessed. Then, the laminate was subjected to in-plane force load and bending moment. The strain and stress distribution at each ply for different LSS was investigated using the concepts of Macro-Mechanics. Finally, several numerical simulations were conducted using the Finite Element Analysis (FEA) software ANSYS to investigate the effects of LSS on deformations and stress distribution. The FEA results were also compared to the Macro-Mechanics solutions obtained by MATLAB. The outcome of this research helps composite users to determine the optimum LSS requires to minimize the overall deformation and stresses. It would be beneficial to predict the structural response of composite laminates analytically and/or numerically before in-house fabrication.Keywords: composite, lamina, laminate, lamina stacking sequence, laminate moduli, laminate strength
Procedia PDF Downloads 1421882 Importance of Solubility and Bubble Pressure Models to Predict Pressure of Nitrified Oil Based Drilling Fluid in Dual Gradient Drilling
Authors: Sajjad Negahban, Ruihe Wang, Baojiang Sun
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Gas-lift dual gradient drilling is a solution for deepwater drilling challenges. As well, Continuous development of drilling technology leads to increase employment of mineral oil based drilling fluids and synthetic-based drilling fluids, which have adequate characteristics such as: high rate of penetration, lubricity, shale inhibition and low toxicity. The paper discusses utilization of nitrified mineral oil base drilling for deepwater drilling and for more accurate prediction of pressure in DGD at marine riser, solubility and bubble pressure were considered in steady state hydraulic model. The Standing bubble pressure and solubility correlations, and two models which were acquired from experimental determination were applied in hydraulic model. The effect of the black oil correlations, and new solubility and bubble pressure models was evaluated on the PVT parameters such as oil formation volume factor, density, viscosity, volumetric flow rate. Eventually, the consequent simulated pressure profile due to these models was presented.Keywords: solubility, bubble pressure, gas-lift dual gradient drilling, steady state hydraulic model
Procedia PDF Downloads 27821881 Personal Information Classification Based on Deep Learning in Automatic Form Filling System
Authors: Shunzuo Wu, Xudong Luo, Yuanxiu Liao
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Recently, the rapid development of deep learning makes artificial intelligence (AI) penetrate into many fields, replacing manual work there. In particular, AI systems also become a research focus in the field of automatic office. To meet real needs in automatic officiating, in this paper we develop an automatic form filling system. Specifically, it uses two classical neural network models and several word embedding models to classify various relevant information elicited from the Internet. When training the neural network models, we use less noisy and balanced data for training. We conduct a series of experiments to test my systems and the results show that our system can achieve better classification results.Keywords: artificial intelligence and office, NLP, deep learning, text classification
Procedia PDF Downloads 20221880 Analysis on the Building Energy Performance of a Retrofitted Residential Building with RETScreen Expert Software
Authors: Abdulhameed Babatunde Owolabi, Benyoh Emmanuel Kigha Nsafon, Jeung-Soo Huh
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Energy efficiency measures for residential buildings in South Korea is a national issue because most of the apartments built in the last decades were constructed without proper energy efficiency measures making the energy performance of old buildings to be very poor when compared with new buildings. However, the adoption of advanced building technologies and regulatory building codes are effective energy efficiency strategies for new construction. There is a need to retrofits the existing building using energy conservation measures (ECMs) equipment’s in order to conserve energy and reduce GHGs emissions. To achieve this, the Institute for Global Climate Change and Energy (IGCCE), Kyungpook National University (KNU), Daegu, South Korea employed RETScreen Expert software to carry out measurement and verification (M&V) analysis on an existing building in Korea by using six years gas consumption data collected from Daesung Energy Co., Ltd in order to determine the building energy performance after the introduction of ECM. Through the M&V, energy efficiency is attained, and the resident doubt was reduced. From the analysis, a total of 657 Giga Joules (GJ) of liquefied natural gas (LNG) was consumed at the rate of 0.34 GJ/day having a peak in the year 2015, which cost the occupant the sum of $10,821.Keywords: energy efficiency, measurement and verification, performance analysis, RETScreen experts
Procedia PDF Downloads 14021879 Validation and Projections for Solar Radiation up to 2100: HadGEM2-AO Global Circulation Model
Authors: Elison Eduardo Jardim Bierhals, Claudineia Brazil, Deivid Pires, Rafael Haag, Elton Gimenez Rossini
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The objective of this work is to evaluate the results of solar radiation projections between 2006 and 2013 for the state of Rio Grande do Sul, Brazil. The projections are provided by the General Circulation Models (MCGs) belonging to the Coupled Model Intercomparison Phase 5 (CMIP5). In all, the results of the simulation of six models are evaluated, compared to monthly data, measured by a network of thirteen meteorological stations of the National Meteorological Institute (INMET). The performance of the models is evaluated by the Nash coefficient and the Bias. The results are presented in the form of tables, graphs and spatialization maps. The ACCESS1-0 RCP 4.5 model presented the best results for the solar radiation simulations, for the most optimistic scenario, in much of the state. The efficiency coefficients (CEF) were between 0.95 and 0.98. In the most pessimistic scenario, HADGen2-AO RCP 8.5 had the best accuracy among the analyzed models, presenting coefficients of efficiency between 0.94 and 0.98. From this validation, solar radiation projection maps were elaborated, indicating a seasonal increase of this climatic variable in some regions of the Brazilian territory, mainly in the spring.Keywords: climate change, projections, solar radiation, validation
Procedia PDF Downloads 20921878 A Study on the Chemical Composition of Kolkheti's Sphagnum Peat Peloids to Evaluate the Perspective of Use in Medical Practice
Authors: Al. Tsertsvadze. L. Ebralidze, I. Matchutadze. D. Berashvili, A. Bakuridze
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Peatlands are landscape elements, they are formed over a very long period by physical, chemical, biologic, and geologic processes. In the moderate zone of Caucasus, the Kolkheti lowlands are distinguished by the diversity of relictual plants, a high degree of endemism, orographic, climate, landscape, and other characteristics of high levels of biodiversity. The unique properties of the Kolkheti region lead to the formation of special, so-called, endemic peat peloids. The composition and properties of peloids strongly depend on peat-forming plants. Peat is considered a unique complex of raw materials, which can be used in different fields of the industry: agriculture, metallurgy, energy, biotechnology, chemical industry, health care. They are formed in permanent wetland areas. As a result of decay, higher plants remain in the anaerobic area, with the participation of microorganisms. Peat mass absorbs soil and groundwater. Peloids are predominantly rich with humic substances, which are characterized by high biological activity. Humic acids stimulate enzymatic activity, regenerative processes, and have anti-inflammatory activity. Objects of the research were Kolkheti peat peloids (Ispani, Anaklia, Churia, Chirukhi, Peranga) possessing different formation phases. Due to specific physical and chemical properties of research objects, the aim of the research was to develop analytical methods in order to study the chemical composition of the objects. The research was held using modern instrumental methods of analysis: Ultraviolet-visible spectroscopy and Infrared spectroscopy, Scanning Electron Microscopy, Centrifuge, dry oven, Ultraturax, pH meter, fluorescence spectrometer, Gas chromatography-mass spectrometry (GC-MS/MS), Gas chromatography. Based on the research ration between organic and inorganic substances, the spectrum of micro and macro elements, also the content of minerals was determined. The content of organic nitrogen was determined using the Kjeldahl method. The total composition of amino acids was studied by a spectrophotometric method using standard solutions of glutamic and aspartic acids. Fatty acid was determined using GC (Gas chromatography). Based on the obtained results, we can conclude that the method is valid to identify fatty acids in the research objects. The content of organic substances in the research objects was held using GC-MS. Using modern instrumental methods of analysis, the chemical composition of research objects was studied. Each research object is predominantly reached with a broad spectrum of organic (fatty acids, amino acids, carbocyclic and heterocyclic compounds, organic acids and their esters, steroids) and inorganic (micro and macro elements, minerals) substances. Modified methods used in the presented research may be utilized for the evaluation of cosmetological balneological and pharmaceutical means prepared on the base of Kolkheti's Sphagnum Peat Peloids.Keywords: modern analytical methods, natural resources, peat, chemistry
Procedia PDF Downloads 12721877 Design and Fabrication of an Electrostatically Actuated Parallel-Plate Mirror by 3D-Printer
Authors: J. Mizuno, S. Takahashi
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In this paper, design and fabrication of an actuated parallel-plate mirror based on a 3D-printer is described. The mirror and electrode layers are fabricated separately and assembled thereafter. The alignment is performed by dowel pin-hole pairs fabricated on the respective layers. The electrodes are formed on the surface of the electrode layer by Au ion sputtering using a suitable mask, which is also fabricated by a 3D-printer.For grounding the mirror layer, except the contact area with the electrode paths, all the surface is Au ion sputtered. 3D-printers are widely used for creating 3D models or mock-ups. The authors have recently proposed that these models can perform electromechanical functions such as actuators by suitably masking them followed by metallization process. Since the smallest possible fabrication size is in the order of sub-millimeters, these electromechanical devices are named by the authors as SMEMS (Sub-Milli Electro-Mechanical Systems) devices. The proposed mirror described in this paper which consists of parallel-plate electrostatic actuators is also one type of SMEMS devices. In addition, SMEMS is totally environment-clean compared to MEMS (Micro Electro-Mechanical Systems) fabrication processes because any hazardous chemicals or gases are utilized.Keywords: MEMS, parallel-plate mirror, SMEMS, 3D-printer
Procedia PDF Downloads 43821876 Stock Price Prediction Using Time Series Algorithms
Authors: Sumit Sen, Sohan Khedekar, Umang Shinde, Shivam Bhargava
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This study has been undertaken to investigate whether the deep learning models are able to predict the future stock prices by training the model with the historical stock price data. Since this work required time series analysis, various models are present today to perform time series analysis such as Recurrent Neural Network LSTM, ARIMA and Facebook Prophet. Applying these models the movement of stock price of stocks are predicted and also tried to provide the future prediction of the stock price of a stock. Final product will be a stock price prediction web application that is developed for providing the user the ease of analysis of the stocks and will also provide the predicted stock price for the next seven days.Keywords: Autoregressive Integrated Moving Average, Deep Learning, Long Short Term Memory, Time-series
Procedia PDF Downloads 14321875 Eco-Friendly Synthesis of Carbon Quantum Dots as an Effective Adsorbent
Authors: Hebat‑Allah S. Tohamy, Mohamed El‑Sakhawy, Samir Kamel
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Fluorescent carbon quantum dots (CQDs) were prepared by an economical, green, and single-step procedure based on microwave heating of urea with sugarcane bagasse (SCB), cellulose (C), or carboxymethyl cellulose (CMC). The prepared CQDs were characterized using a series of spectroscopic techniques, and they had small size, strong absorption in the UV, and excitation wavelength-dependent fluorescence. The prepared CQDs were used for Pb(II) adsorption from an aqueous solution. The removal efficiency percentages (R %) were 99.16, 96.36, and 98.48 for QCMC, QC, and QSCB. The findings validated the efficiency of CQDs synthesized from CMC, cellulose, and SCB as excellent materials for further utilization in the environmental fields of wastewater pollution detection, adsorption, and chemical sensing applications. The kinetics and isotherms studied found that all CQD isotherms fit well with the Langmuir model than Freundlich and Temkin models. According to R², the pseudo-second-order fits the adsorption of QCMC, while the first-order one fits with QC and QSCB.Keywords: carbon quantum dots, graphene quantum dots, fluorescence, quantum yield, water treatment, agricultural wastes
Procedia PDF Downloads 13321874 In-Context Meta Learning for Automatic Designing Pretext Tasks for Self-Supervised Image Analysis
Authors: Toktam Khatibi
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Self-supervised learning (SSL) includes machine learning models that are trained on one aspect and/or one part of the input to learn other aspects and/or part of it. SSL models are divided into two different categories, including pre-text task-based models and contrastive learning ones. Pre-text tasks are some auxiliary tasks learning pseudo-labels, and the trained models are further fine-tuned for downstream tasks. However, one important disadvantage of SSL using pre-text task solving is defining an appropriate pre-text task for each image dataset with a variety of image modalities. Therefore, it is required to design an appropriate pretext task automatically for each dataset and each downstream task. To the best of our knowledge, the automatic designing of pretext tasks for image analysis has not been considered yet. In this paper, we present a framework based on In-context learning that describes each task based on its input and output data using a pre-trained image transformer. Our proposed method combines the input image and its learned description for optimizing the pre-text task design and its hyper-parameters using Meta-learning models. The representations learned from the pre-text tasks are fine-tuned for solving the downstream tasks. We demonstrate that our proposed framework outperforms the compared ones on unseen tasks and image modalities in addition to its superior performance for previously known tasks and datasets.Keywords: in-context learning (ICL), meta learning, self-supervised learning (SSL), vision-language domain, transformers
Procedia PDF Downloads 8121873 Bioremoval of Malachite Green Dye from Aqueous Solution Using Marine Algae: Isotherm, Kinetic and Mechanistic Study
Authors: M. Jerold, V. Sivasubramanian
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This study reports the removal of Malachite Green (MG) from simulated wastewater by using marine macro algae Ulva lactuca. Batch biosorption experiments were carried out to determine the biosorption capacity. The biosorption capacity was found to be maximum at pH 10. The effect of various other operation parameters such as biosorbent dosage, initial dye concentration, contact time and agitation was also investigated. The equilibrium attained at 120 min with 0.1 g/L of biosorbent. The isotherm experimental data fitted well with Langmuir Model with R² value of 0.994. The maximum Langmuir biosorption capacity was found to be 76.92 mg/g. Further, Langmuir separation factor RL value was found to be 0.004. Therefore, the adsorption is favorable. The biosorption kinetics of MG was found to follow pseudo second-order kinetic model. The mechanistic study revealed that the biosorption of malachite onto Ulva lactuca was controlled by film diffusion. The solute transfer in a solid-liquid adsorption process is characterized by the film diffusion and/or particle diffusion. Thermodynamic study shows ΔG° is negative indicates the feasibility and spontaneous nature for the biosorption of malachite green. The biosorbent was characterized using Scanning Electron Microscopy, Fourier Transform Infrared Spectroscopy, and elemental analysis (CHNS: Carbon, Hydrogen, Nitrogen, Sulphur). This study showed that Ulva lactuca can be used as promising biosorbent for the removal of MG from wastewater.Keywords: biosorption, Ulva lactuca, wastewater, malachite green, isotherm, kinetics
Procedia PDF Downloads 15721872 A High Efficiency Reduced Rules Neuro-Fuzzy Based Maximum Power Point Tracking Controller for Photovoltaic Array Connected to Grid
Authors: Lotfi Farah, Nadir Farah, Zaiem Kamar
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This paper achieves a maximum power point tracking (MPPT) controller using a high-efficiency reduced rules neuro-fuzzy inference system (HE2RNF) for a 100 kW stand-alone photovoltaic (PV) system connected to the grid. The suggested HE2RNF based MPPT seeks the optimal duty cycle for the boost DC-DC converter, making the designed PV system working at the maximum power point (MPP), then transferring this power to the grid via a three levels voltage source converter (VSC). PV current variation and voltage variation are chosen as HE2RNF-based MPPT controller inputs. By using these inputs with the duty cycle as the only single output, a six rules ANFIS is generated. The high performance of the proposed HE2RNF numerically in the MATLAB/Simulink environment is shown. The 0.006% steady-state error, 0.006s of tracking time, and 0.088s of starting time prove the robustness of this six reduced rules against the widely used twenty-five ones.Keywords: PV, MPPT, ANFIS, HE2RNF-based MPPT controller, VSC, grid connection
Procedia PDF Downloads 18521871 Escaping Domestic Violence in Time of Conflict: The Ways Female Refugees Decide to Flee
Authors: Zofia Wlodarczyk
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I study the experiences of domestic violence survivors who flee their countries of origin in times of political conflict using insight and evidence from forty-five biographical interviews with female Chechen refugees and twelve refugee resettlement professionals in Poland. Both refugees and women are often described as having less agency—that is, they lack the power to decide to migrate – refugees less than economic migrants and women less than men. In this paper, I focus on how female refugees who have been victims of domestic violence make decisions about leaving their countries of origin during times of political conflict. I use several existing migration theories to trace how the migration experience of these women is shaped by dynamics at different levels of society: the macro level, the meso level and the micro level. At the macro level of analysis, I find that political conflict can be both a source of and an escape from domestic violence. Ongoing conflict can strengthen the patriarchal cultural norms, increase violence and constrain women’s choices when it comes to marriage. However, political conflict can also destabilize families and make pathways for women to escape. At the meso level I demonstrate that other political migrants and institutions that emerge due to politically triggered migration can guide those fleeing domestic violence. Finally, at the micro level, I show that family dynamics often force domestic abuse survivors to make their decision to escape alone or with the support of only the most trusted female relatives. Taken together, my analyses show that we cannot look solely at one level of society when describing decision-making processes of women fleeing domestic violence. Conflict-related micro, meso and macro forces interact with and influence each other: on the one hand, strengthening an abusive trap, and on the other hand, opening a door to escape. This study builds upon several theoretical and empirical debates. First, it expands theories of migration by incorporating both refugee and gender perspectives. Few social scientists have used the migration theory framework to discuss the unique circumstances of refugee flows. Those who have mainly focus on “political” migrants, a designation that frequently fails to account for gender, does not incorporate individuals fleeing gender-based violence, including domestic-violence victims. The study also enriches migration scholarship, typically focused on the US and Western-European context, with research from Eastern Europe and Caucasus. Moreover, it contributes to the literature on the changing roles of gender in the context of migration. I argue that understanding how gender roles and hierarchies influence the pre-migration stage of female refugees is crucial, as it may have implications for policy-making efforts in host countries that recognize the asylum claims of those fleeing domestic violence. This study also engages in debates about asylum and refugee law. Domestic violence is normatively and often legally considered an individual-level problem whereas political persecution is recognized as a structural or societal level issue. My study challenges these notions by showing how the migration triggered by domestic violence is closely intertwined with politically motivated refuge.Keywords: AGENCY, DOMESTIC VIOLENCE, FEMALE REFUGEES, POLITICAL REFUGE, SOCIAL NETWORKS
Procedia PDF Downloads 17021870 Reducing Greenhouse Gass Emissions by Recyclable Material Bank Project of Universities in Central Region of Thailand
Authors: Ronbanchob Apiratikul
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This research studied recycled waste by the Recyclable Material Bank Project of 4 universities in the central region of Thailand for the evaluation of reducing greenhouse gas emissions compared with landfilling activity during July 2012 to June 2013. The results showed that the projects collected total amount of recyclable wastes of about 911,984.80 kilograms. Office paper had the largest amount among these recycled wastes (50.68% of total recycled waste). Groups of recycled waste can be prioritized from high to low according to their amount as paper, plastic, glass, mixed recyclables, and metal, respectively. The project reduced greenhouse gas emissions equivalent to about 2814.969 metric tons of carbon dioxide. The most significant recycled waste that affects the reduction of greenhouse gas emissions is office paper which is 70.16% of total reduced greenhouse gasses emission. According to amount of reduced greenhouse gasses emission, groups of recycled waste can be prioritized from high to low significances as paper, plastic, metals, mixed recyclables, and glass, respectively.Keywords: recycling, garbage bank, waste management, recyclable wastes, greenhouse gases
Procedia PDF Downloads 42621869 Repeatable Scalable Business Models: Can Innovation Drive an Entrepreneurs Un-Validated Business Model?
Authors: Paul Ojeaga
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Can the level of innovation use drive un-validated business models across regions? To what extent does industrial sector attractiveness drive firm’s success across regions at the time of start-up? This study examines the role of innovation on start-up success in six regions of the world (namely Sub Saharan Africa, the Middle East and North Africa, Latin America, South East Asia Pacific, the European Union and the United States representing North America) using macroeconomic variables. While there have been studies using firm level data, results from such studies are not suitable for national policy decisions. The need to drive a regional innovation policy also begs for an answer, therefore providing room for this study. Results using dynamic panel estimation show that innovation counts in the early infancy stage of new business life cycle. The results are robust even after controlling for time fixed effects and the study present variance-covariance estimation robust standard errors.Keywords: industrial economics, un-validated business models, scalable models, entrepreneurship
Procedia PDF Downloads 28321868 Optimisation of Nitrogen as a Protective Gas via the Alternating Shielding Gas Technique in the Gas Metal Arc Welding Process
Authors: M. P. E. E Silva, A. M. Galloway, A. I. Toumpis
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An increasing concern exists in the welding industry in terms of faster joining processes. Methods such as the alternation between shielding gases such Ar, CO₂ and He have been able to provide improved penetration of the joint, reduced heat transfer to the workpiece, and increased travel speeds of the welding torch. Nitrogen as a shielding gas is not desirable due to its reactive behavior within the arc plasma, being absorbed by the molten pool during the welding process. Below certain amounts, nitrogen is not harmful. However, the nitrogen threshold is reduced during the solidification of the joint, and if its subsequent desorption is not completed on time, gas entrapment and blowhole formation may occur. The present study expanded the use of the alternating shielding gas method in the gas metal arc welding (GMAW) process by alternately supplying Ar/5%N₂ and He. Improvements were introduced in terms of joint strength and grain refinement. Microstructural characterization findings showed porosity-free welds with reduced inclusion formation while mechanical tests such as tensile and bend tests confirmed the reinforcement of the joint by the addition of nitrogen. Additionally, significant reductions of the final distortion of the workpiece were found after the welding procedure as well as decreased heat affected zones and temperatures of the weld.Keywords: alternating shielding gas method, GMAW, grain refinement, nitrogen, porosity, mechanical testing
Procedia PDF Downloads 11021867 Adapted Intersection over Union: A Generalized Metric for Evaluating Unsupervised Classification Models
Authors: Prajwal Prakash Vasisht, Sharath Rajamurthy, Nishanth Dara
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In a supervised machine learning approach, metrics such as precision, accuracy, and coverage can be calculated using ground truth labels to help in model tuning, evaluation, and selection. In an unsupervised setting, however, where the data has no ground truth, there are few interpretable metrics that can guide us to do the same. Our approach creates a framework to adapt the Intersection over Union metric, referred to as Adapted IoU, usually used to evaluate supervised learning models, into the unsupervised domain, which solves the problem by factoring in subject matter expertise and intuition about the ideal output from the model. This metric essentially provides a scale that allows us to compare the performance across numerous unsupervised models or tune hyper-parameters and compare different versions of the same model.Keywords: general metric, unsupervised learning, classification, intersection over union
Procedia PDF Downloads 5021866 Model for Introducing Products to New Customers through Decision Tree Using Algorithm C4.5 (J-48)
Authors: Komol Phaisarn, Anuphan Suttimarn, Vitchanan Keawtong, Kittisak Thongyoun, Chaiyos Jamsawang
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This article is intended to analyze insurance information which contains information on the customer decision when purchasing life insurance pay package. The data were analyzed in order to present new customers with Life Insurance Perfect Pay package to meet new customers’ needs as much as possible. The basic data of insurance pay package were collect to get data mining; thus, reducing the scattering of information. The data were then classified in order to get decision model or decision tree using Algorithm C4.5 (J-48). In the classification, WEKA tools are used to form the model and testing datasets are used to test the decision tree for the accurate decision. The validation of this model in classifying showed that the accurate prediction was 68.43% while 31.25% were errors. The same set of data were then tested with other models, i.e. Naive Bayes and Zero R. The results showed that J-48 method could predict more accurately. So, the researcher applied the decision tree in writing the program used to introduce the product to new customers to persuade customers’ decision making in purchasing the insurance package that meets the new customers’ needs as much as possible.Keywords: decision tree, data mining, customers, life insurance pay package
Procedia PDF Downloads 42921865 Analysis of Lead Time Delays in Supply Chain: A Case Study
Authors: Abdel-Aziz M. Mohamed, Nermeen Coutry
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Lead time is an important measure of supply chain performance. It impacts both customer satisfactions as well as the total cost of inventory. This paper presents the result of a study on the analysis of the customer order lead-time for a multinational company. In the study, the lead time was divided into three stages: order entry, order fulfillment, and order delivery. A sample of size 2,425 order lines from the company records were considered for this study. The sample data includes information regarding customer orders from the time of order entry until order delivery. Data regarding the lead time of each sage for different orders were also provided. Summary statistics on lead time data reveals that about 30% of the orders were delivered after the scheduled due date. The result of the multiple linear regression analysis technique revealed that component type, logistics parameter, order size and the customer type have significant impact on lead time. Data analysis on the stages of lead time indicates that stage 2 consumes over 50% of the lead time. Pareto analysis was made to study the reasons for the customer order delay in each of the 3 stages. Recommendation was given to resolve the problem.Keywords: lead time reduction, customer satisfaction, service quality, statistical analysis
Procedia PDF Downloads 73321864 Improving Oxidative Stability of Encapsulated Krill and Black Cumin Oils and its Application in Functional Yogurt
Authors: Tamer El-Messery, Beraat Ozcelik
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This study aimed to produce functional yogurt supplemented with microencapsulated krill oil as a source of omega 3, which is known, to maintain the normal brain function, reduce the risk of cancer, and preventing cardiovascular disease. Krill oil was mixed with black cumin oil (1:1) in order to increase its oxidative stability. β-caroteine (10 mg/100 ml) was used as a standard antioxidant. Maltodextrin (MD) was mixed with whey protein concentrate (WPC) and gum Arabic (GA) at the ratio of 8:2:0.5 ratios and used for microencapsulation of single or mixed oils. The microcapsules were dried by freeze and spray drying in order to maximize encapsulation efficiency and minimize lipid oxidation. The feed emulsions used for particle production were characterized for stability, viscosity and particle size, zeta potential, and oxidative stability. The oxidative stability for mixed krill oil and black cumin oil was the highest. The highest encapsulation efficiency was obtained using spray drying, which also showed the highest oxidative stability. The addition of encapsulated krill and black cumin oils (1:1) powder in yogurt manufacture reduced slightly effects on the development of acidity, textural parameters, and water holding capacity of yogurt as compared to control.Keywords: Krill oil, black cumin oil, micro-encapsulation, oxidative stability, functional yogurt
Procedia PDF Downloads 10721863 Detection of Cardiac Arrhythmia Using Principal Component Analysis and Xgboost Model
Authors: Sujay Kotwale, Ramasubba Reddy M.
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Electrocardiogram (ECG) is a non-invasive technique used to study and analyze various heart diseases. Cardiac arrhythmia is a serious heart disease which leads to death of the patients, when left untreated. An early-time detection of cardiac arrhythmia would help the doctors to do proper treatment of the heart. In the past, various algorithms and machine learning (ML) models were used to early-time detection of cardiac arrhythmia, but few of them have achieved better results. In order to improve the performance, this paper implements principal component analysis (PCA) along with XGBoost model. The PCA was implemented to the raw ECG signals which suppress redundancy information and extracted significant features. The obtained significant ECG features were fed into XGBoost model and the performance of the model was evaluated. In order to valid the proposed technique, raw ECG signals obtained from standard MIT-BIH database were employed for the analysis. The result shows that the performance of proposed method is superior to the several state-of-the-arts techniques.Keywords: cardiac arrhythmia, electrocardiogram, principal component analysis, XGBoost
Procedia PDF Downloads 12021862 Response of Chickpea (Cicer arietinum L.) Genotypes to Drought Stress at Different Growth Stages
Authors: Ali. Marjani, M. Farsi, M. Rahimizadeh
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Chickpea (Cicer arietinum L.) is one of the important grain legume crops in the world. However, drought stress is a serious threat to chickpea production, and development of drought-resistant varieties is a necessity. Field experiments were conducted to evaluate the response of 8 chickpea genotypes (MCC* 696, 537, 80, 283, 392, 361, 252, 397) and drought stress (S1: non-stress, S2: stress at vegetative growth stage, S3: stress at early bloom, S4: stress at early pod visible) at different growth stages. Experiment was arranged in split plot design with four replications. Difference among the drought stress time was found to be significant for investigated traits except biological yield. Differences were observed for genotypes in flowering time, pod information time, physiological maturation time and yield. Plant height reduced due to drought stress in vegetative growth stage. Stem dry weight reduced due to drought stress in pod visibly. Flowering time, maturation time, pod number, number of seed per plant and yield cause of drought stress in flowering was also reduced. The correlation between yield and number of seed per plant and biological yield was positive. The MCC283 and MCC696 were the high-tolerance genotypes. These results demonstrated that drought stress delayed phonological growth in chickpea and that flowering stage is sensitive.Keywords: chickpea, drought stress, growth stage, tolerance
Procedia PDF Downloads 26221861 Double Clustering as an Unsupervised Approach for Order Picking of Distributed Warehouses
Authors: Hsin-Yi Huang, Ming-Sheng Liu, Jiun-Yan Shiau
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Planning the order picking lists of warehouses to achieve when the costs associated with logistics on the operational performance is a significant challenge. In e-commerce era, this task is especially important productive processes are high. Nowadays, many order planning techniques employ supervised machine learning algorithms. However, the definition of which features should be processed by such algorithms is not a simple task, being crucial to the proposed technique’s success. Against this background, we consider whether unsupervised algorithms can enhance the planning of order-picking lists. A Zone2 picking approach, which is based on using clustering algorithms twice, is developed. A simplified example is given to demonstrate the merit of our approach.Keywords: order picking, warehouse, clustering, unsupervised learning
Procedia PDF Downloads 16021860 UniFi: Universal Filter Model for Image Enhancement
Authors: Aleksei Samarin, Artyom Nazarenko, Valentin Malykh
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Image enhancement is becoming more and more popular, especially on mobile devices. Nowadays, it is a common approach to enhance an image using a convolutional neural network (CNN). Such a network should be of significant size; otherwise, a possibility for the artifacts to occur is overgrowing. The existing large CNNs are computationally expensive, which could be crucial for mobile devices. Another important flaw of such models is they are poorly interpretable. There is another approach to image enhancement, namely, the usage of predefined filters in combination with the prediction of their applicability. We present an approach following this paradigm, which outperforms both existing CNN-based and filter-based approaches in the image enhancement task. It is easily adaptable for mobile devices since it has only 47 thousand parameters. It shows the best SSIM 0.919 on RANDOM250 (MIT Adobe FiveK) among small models and is thrice faster than previous models.Keywords: universal filter, image enhancement, neural networks, computer vision
Procedia PDF Downloads 10221859 Soliton Solutions of the Higher-Order Nonlinear Schrödinger Equation with Dispersion Effects
Authors: H. Triki, Y. Hamaizi, A. El-Akrmi
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We consider the higher order nonlinear Schrödinger equation model with fourth-order dispersion, cubic-quintic terms, and self-steepening. This equation governs the propagation of fem to second pulses in optical fibers. We present new bright and dark solitary wave type solutions for such a model under certain parametric conditions. This kind of solution may be useful to explain some physical phenomena related to wave propagation in a nonlinear optical fiber systems supporting high-order nonlinear and dispersive effects.Keywords: nonlinear Schrödinger equation, high-order effects, soliton solution
Procedia PDF Downloads 63621858 Synthesis of Novel Nanostructure Copper(II) Metal-Organic Complex for Photocatalytic Degradation of Remdesivir Antiviral COVID-19 from Aqueous Solution: Adsorption Kinetic and Thermodynamic Studies
Authors: Sam Bahreini, Payam Hayati
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Metal-organic coordination [Cu(L)₄(SCN)₂] was synthesized applying ultrasonic irradiation, and its photocatalytic performance for the degradation of Remdesivir (RS) under sunlight irradiation was systematically explored for the first time in this study. The physicochemical properties of the synthesized photocatalyst were investigated using Fourier-transform infrared (FT-IR), field emission scanning electron microscopy (FE-SEM), powder x-ray diffraction (PXRD), energy-dispersive x-ray (EDX), thermal gravimetric analysis (TGA), diffuse reflectance spectroscopy (DRS) techniques. Systematic examinations were carried out by changing irradiation time, temperature, solution pH value, contact time, RS concentration, and catalyst dosage. The photodegradation kinetic profiles were modeled in pseudo-first order, pseudo-second-order, and intraparticle diffusion models reflected that photodegradation onto [Cu(L)₄(SCN)₂] catalyst follows pseudo-first order kinetic model. The fabricated [Cu(L)₄(SCN)₂] nanostructure bandgap was determined as 2.60 eV utilizing the Kubelka-Munk formula from the diffuse reflectance spectroscopy method. Decreasing chemical oxygen demand (COD) (from 70.5 mgL-1 to 36.4 mgL-1) under optimal conditions well confirmed mineralizing of the RS drug. The values of ΔH° and ΔS° was negative, implying the process of adsorption is spontaneous and more favorable in lower temperatures.Keywords: Photocatalytic degradation, COVID-19, density functional theory (DFT), molecular electrostatic potential (MEP)
Procedia PDF Downloads 17021857 Characteristics of Inclusive Circular Business Models in Social Entrepreneurship
Authors: Svitlana Yermak, Olubukola Aluko
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The purpose of this study was a literature review on the topic of social entrepreneurship, a review of new trends and best practices, the study of existing inclusive business models and their interaction with the principles of the circular economy for possible implementation in the practice of Ukraine in war and post-war times in conditions of scarce resources. Thus, three research questions were identified and substantiated: to determine the characteristics of social entrepreneurship, consider the features in Ukraine and the UK; highlight the criteria for inclusion in social entrepreneurship and its legal support; explore examples of existing inclusive circular business models to illustrate how the two concepts may be combined. A detailed review of the literature selected from the Scopus and Web of Science databases was carried out. The study revealed signs of social entrepreneurship, the main of which are doing business and making a profit, as well as the social orientation of the business, which is prescribed in the constituent documents of the enterprise immediately upon its creation. Considered are the characteristics of social entrepreneurship in the UK and Ukraine. It has been established that in the UK, social entrepreneurship is clearly regulated by the state; there are special legislative norms and support programs, in contrast to Ukraine, where these processes are only partially regulated. The study identified the main criteria for inclusion in inclusive circular business models: economic (sustainability and efficiency, job creation and economic growth, promotion of local development), social (accessibility, equity and fairness, inclusion and participation), and resources in their interconnection. It is substantiated that the resource criterion is especially important for this type of business model. It provides for the efficient and sustainable use of resources, as well as the cyclical nature of resources. And it was concluded that the principles of the circular economy not only do not contradict but, on the contrary, complement and expand the inclusive business models on which social entrepreneurship is based.Keywords: social entrepreneurship, inclusive business models, circular economy, inclusion criteria
Procedia PDF Downloads 10221856 Comparison of Machine Learning Models for the Prediction of System Marginal Price of Greek Energy Market
Authors: Ioannis P. Panapakidis, Marios N. Moschakis
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The Greek Energy Market is structured as a mandatory pool where the producers make their bid offers in day-ahead basis. The System Operator solves an optimization routine aiming at the minimization of the cost of produced electricity. The solution of the optimization problem leads to the calculation of the System Marginal Price (SMP). Accurate forecasts of the SMP can lead to increased profits and more efficient portfolio management from the producer`s perspective. Aim of this study is to provide a comparative analysis of various machine learning models such as artificial neural networks and neuro-fuzzy models for the prediction of the SMP of the Greek market. Machine learning algorithms are favored in predictions problems since they can capture and simulate the volatilities of complex time series.Keywords: deregulated energy market, forecasting, machine learning, system marginal price
Procedia PDF Downloads 216