Search results for: grey wolf optimization
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3487

Search results for: grey wolf optimization

1507 Multi-Pass Shape Drawing Process Design for Manufacturing of Automotive Reinforcing Agent with Closed Cross-Section Shape using Finite Element Method Analysis

Authors: Mok-Tan Ahn, Hyeok Choi, Joon-Hong Park

Abstract:

Multi-stage drawing process is an important technique for forming a shape that cannot be molded in a single process. multi-stage drawing process in number of passes and the shape of the die are an important factor influencing the productivity and moldability of the product. The number and shape of the multi-path in the mold of the drawing process is very influencing the productivity and moldability of the product. Half angle of the die and mandrel affects the drawing force and it also affects the completion of the final shape. Thus reducing the number of pass and the die shape optimization are necessary to improve the formability of the billet. The purpose of this study, Analyzing the load on the die through the FEM analysis and in consideration of the formability of the material presents a die model.

Keywords: automotive reinforcing agent, multi-pass shape drawing, automotive parts, FEM analysis

Procedia PDF Downloads 455
1506 Model-Independent Price Bounds for the Swiss Re Mortality Bond 2003

Authors: Raj Kumari Bahl, Sotirios Sabanis

Abstract:

In this paper, we are concerned with the valuation of the first Catastrophic Mortality Bond that was launched in the market namely the Swiss Re Mortality Bond 2003. This bond encapsulates the behavior of a well-defined mortality index to generate payoffs for the bondholders. Pricing this bond is a challenging task. We adapt the payoff of the terminal principal of the bond in terms of the payoff of an Asian put option and present an approach to derive model-independent bounds exploiting comonotonic theory. We invoke Jensen’s inequality for the computation of lower bounds and employ Lagrange optimization technique to achieve the upper bound. The success of these bounds is based on the availability of compatible European mortality options in the market. We carry out Monte Carlo simulations to estimate the bond price and illustrate the strength of these bounds across a variety of models. The fact that our bounds are model-independent is a crucial breakthrough in the pricing of catastrophic mortality bonds.

Keywords: mortality bond, Swiss Re Bond, mortality index, comonotonicity

Procedia PDF Downloads 250
1505 Restoration and Conservation of Historical Textiles Using Covalently Immobilized Enzymes on Nanoparticles

Authors: Mohamed Elbehery

Abstract:

Historical textiles in the burial environment or in museums are exposed to many types of stains and dirt that are associated with historical textiles by multiple chemical bonds that cause damage to historical textiles. The cleaning process must be carried out with great care, with no irreversible damage, and sediments removed without affecting the original material of the surface being cleaned. Science and technology continue to provide innovative systems in the bio-cleaning process (using pure enzymes) of historical textiles and artistic surfaces. Lipase and α-amylase were immobilized on nanoparticles of alginate/κ-carrageenan nanoparticle complex and used in historical textiles cleaning. Preparation of nanoparticles, activation, and enzymes immobilization were characterized. Optimization of loading time and units of the two enzymes were done. It was found that, the optimum time and units of amylase were 4 hrs and 25U, respectively. While, the optimum time and units of lipase were 3 hrs and 15U, respectively. The methods used to examine the fibers using a scanning electron microscope equipped with an X-ray energy dispersal unit: SEM with EDX unit.

Keywords: nanoparticles, enzymes, immobilization, textiles

Procedia PDF Downloads 99
1504 The Possibility to Assess the Industrial Enterprise Sustainability

Authors: G. Khasaev, S. Ashmarina , A. Zotova

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The priority of Russian enterprises development has been given to the optimization process of industrial enterprise activity for their sustainable development in a long-term period. The assessment of sustainable development level as one of the most efficient instruments of sustainable development management at the industrial enterprise gives a complex view of its state. In order to perform accurate analysis of the current state of the industrial enterprise, it is necessary to perform the assessment of its sustainable development and using its results to elaborate the further tactic of enterprise functioning. The assessment of sustainable development level of the enterprise may help the effective management of strategy development only if the corresponding indicators system is created. The elaboration and usage the sustainable development indicators allows the enterprise to implement analysis of its activity results and monitoring of sustainable enterprise functioning. The authors’ methods are based on general aspects of the industrial enterprise functioning such as finance, customers, inner economic process, and staff system.

Keywords: assessment methods, indicators system, industrial enterprise, sustainable development

Procedia PDF Downloads 366
1503 Optimizing Boiler Combustion System in a Petrochemical Plant Using Neuro-Fuzzy Inference System and Genetic Algorithm

Authors: Yul Y. Nazaruddin, Anas Y. Widiaribowo, Satriyo Nugroho

Abstract:

Boiler is one of the critical unit in a petrochemical plant. Steam produced by the boiler is used for various processes in the plant such as urea and ammonia plant. An alternative method to optimize the boiler combustion system is presented in this paper. Adaptive Neuro-Fuzzy Inference System (ANFIS) approach is applied to model the boiler using real-time operational data collected from a boiler unit of the petrochemical plant. Nonlinear equation obtained is then used to optimize the air to fuel ratio using Genetic Algorithm, resulting an optimal ratio of 15.85. This optimal ratio is then maintained constant by ratio controller designed using inverse dynamics based on ANFIS. As a result, constant value of oxygen content in the flue gas is obtained which indicates more efficient combustion process.

Keywords: ANFIS, boiler, combustion process, genetic algorithm, optimization.

Procedia PDF Downloads 253
1502 Perinatal Optimisation for Preterm Births Less than 34 Weeks at OLOL, Drogheda, Ireland

Authors: Stephane Maingard, Babu Paturi, Maura Daly, Finnola Armstrong

Abstract:

Background: Perinatal optimization involves the implementation of twelve intervention bundles of care at Our Lady of Lourdes Hospital, reliably delivering evidence-based interventions in the antenatal, intrapartum, and neonatal period to improve preterm outcomes. These key interventions (e.g. Antenatal steroids, Antenatal counselling, Optimal cord management, Respiratory management etc.) are based on WHO (World Health Organization, BAPM (British Association of Perinatal Medicine), and the latest 2022 European Consensus guidelines recommendations. Methodology: In February 2023, a quality improvement project team (pediatricians, neonatologists, obstetricians, clinical skills managers) was established, and a project implementation plan was developed. The Program Study Act implemented the following: 1. Antenatal consultation pathway, 2. Creation and implementation of a perinatal checklist for preterm births less than 34 weeks of gestation, 3. Process changes to ensure the checklist is completed, 4. Completion of parent and staff surveys, 5. Ongoing training. We collected and compared a range of data before and after implementation. Results: Preliminary analysis so far at 1 month demonstrates improvement in the following areas: 50% increase in antenatal counselling. Right place of birth increased from 85% to 100%. Magnesium sulphate increased from 56% to 100%. No change was observed in buccal colostrum administration (28%), delayed cord clamping (75%), caffeine administration (100%), blood glucose level at one hour of life > 2,6mmol (85%). There was also no change noted in respiratory support at resuscitation, CPAP only (47%), IPPV with CPAP (45%), IPPV with intubation (20%), and surfactant administration (28%). A slight decrease in figures was noted in the following: steroid administration from 80% to 75% and thermal care obtaining optimal temperature on admission (65% to 50%). Discussion: Even though the findings are preliminary, the directional improvement shows promise. Improved communication has been achieved between all stakeholders, including our patients, who are key team members. Adherence to the bundles of care will help to improve survival and neurodevelopmental outcomes as well as reduce the length of stay, thereby overall reducing the financial cost, considering the lifetime cost of cerebral palsy is estimated at €800,000 and reducing the length of stay can result in savings of up to €206,000. Conclusion: Preliminary results demonstrate improvements across a range of patient, process, staff, and financial outcomes. Our future goal is a seamless pathway of patient centered care for babies and their families. This project is an interdisciplinary collaboration to implement best practices for a vulnerable patient cohort. Our two main challenges are changing our organization’s culture as well as ensuring the sustainability of the project.

Keywords: perinatal, optimization, antenatal, counselling, IPPV

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1501 Development of Microwave-Assisted Alkalic Salt Pretreatment Regimes for Enhanced Sugar Recovery from Corn Cobs

Authors: Yeshona Sewsynker

Abstract:

This study presents three microwave-assisted alkalic salt pretreatments to enhance delignification and enzymatic saccharification of corn cobs. The effects of process parameters of salt concentration (0-15%), microwave power intensity (0-800 W) and pretreatment time (2-8 min) on reducing sugar yield from corn cobs were investigated. Pretreatment models were developed with the high coefficient of determination values (R2>0.85). Optimization gave a maximum reducing sugar yield of 0.76 g/g. Scanning electron microscopy (SEM) and Fourier Transform Infrared analysis (FTIR) showed major changes in the lignocellulosic structure after pretreatment. A 7-fold increase in the sugar yield was observed compared to previous reports on the same substrate. The developed pretreatment strategy was effective for enhancing enzymatic saccharification from lignocellulosic wastes for microbial biofuel production processes and value-added products.

Keywords: pretreatment, lignocellulosic biomass, enzymatic hydrolysis, delignification

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1500 The Delaying Influence of Degradation on the Divestment of Gas Turbines for Associated Gas Utilisation: Part 1

Authors: Mafel Obhuo, Dodeye I. Igbong, Duabari S. Aziaka, Pericles Pilidis

Abstract:

An important feature of the exploitation of associated gas as fuel for gas turbine engines is a declining supply. So when exploiting this resource, the divestment of prime movers is very important as the fuel supply diminishes with time. This paper explores the influence of engine degradation on the timing of divestments. Hypothetical but realistic gas turbine engines were modelled with Turbomatch, the Cranfield University gas turbine performance simulation tool. The results were deployed in three degradation scenarios within the TERA (Techno-economic and environmental risk analysis) framework to develop economic models. An optimisation with Genetic Algorithms was carried out to maximize the economic benefit. The results show that degradation will have a significant impact. It will delay the divestment of power plants, while they are running less efficiently. Over a 20 year investment, a decrease of $0.11bn, $0.26bn and $0.45bn (billion US dollars) were observed for the three degradation scenarios as against the clean case.

Keywords: economic return, flared associated gas, net present value, optimization

Procedia PDF Downloads 137
1499 A Parallel Algorithm for Solving the PFSP on the Grid

Authors: Samia Kouki

Abstract:

Solving NP-hard combinatorial optimization problems by exact search methods, such as Branch-and-Bound, may degenerate to complete enumeration. For that reason, exact approaches limit us to solve only small or moderate size problem instances, due to the exponential increase in CPU time when problem size increases. One of the most promising ways to reduce significantly the computational burden of sequential versions of Branch-and-Bound is to design parallel versions of these algorithms which employ several processors. This paper describes a parallel Branch-and-Bound algorithm called GALB for solving the classical permutation flowshop scheduling problem as well as its implementation on a Grid computing infrastructure. The experimental study of our distributed parallel algorithm gives promising results and shows clearly the benefit of the parallel paradigm to solve large-scale instances in moderate CPU time.

Keywords: grid computing, permutation flow shop problem, branch and bound, load balancing

Procedia PDF Downloads 283
1498 Use of Artificial Neural Networks to Estimate Evapotranspiration for Efficient Irrigation Management

Authors: Adriana Postal, Silvio C. Sampaio, Marcio A. Villas Boas, Josué P. Castro

Abstract:

This study deals with the estimation of reference evapotranspiration (ET₀) in an agricultural context, focusing on efficient irrigation management to meet the growing interest in the sustainable management of water resources. Given the importance of water in agriculture and its scarcity in many regions, efficient use of this resource is essential to ensure food security and environmental sustainability. The methodology used involved the application of artificial intelligence techniques, specifically Multilayer Perceptron (MLP) Artificial Neural Networks (ANNs), to predict ET₀ in the state of Paraná, Brazil. The models were trained and validated with meteorological data from the Brazilian National Institute of Meteorology (INMET), together with data obtained from a producer's weather station in the western region of Paraná. Two optimizers (SGD and Adam) and different meteorological variables, such as temperature, humidity, solar radiation, and wind speed, were explored as inputs to the models. Nineteen configurations with different input variables were tested; amidst them, configuration 9, with 8 input variables, was identified as the most efficient of all. Configuration 10, with 4 input variables, was considered the most effective, considering the smallest number of variables. The main conclusions of this study show that MLP ANNs are capable of accurately estimating ET₀, providing a valuable tool for irrigation management in agriculture. Both configurations (9 and 10) showed promising performance in predicting ET₀. The validation of the models with cultivator data underlined the practical relevance of these tools and confirmed their generalization ability for different field conditions. The results of the statistical metrics, including Mean Absolute Error (MAE), Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and Coefficient of Determination (R²), showed excellent agreement between the model predictions and the observed data, with MAE as low as 0.01 mm/day and 0.03 mm/day, respectively. In addition, the models achieved an R² between 0.99 and 1, indicating a satisfactory fit to the real data. This agreement was also confirmed by the Kolmogorov-Smirnov test, which evaluates the agreement of the predictions with the statistical behavior of the real data and yields values between 0.02 and 0.04 for the producer data. In addition, the results of this study suggest that the developed technique can be applied to other locations by using specific data from these sites to further improve ET₀ predictions and thus contribute to sustainable irrigation management in different agricultural regions. The study has some limitations, such as the use of a single ANN architecture and two optimizers, the validation with data from only one producer, and the possible underestimation of the influence of seasonality and local climate variability. An irrigation management application using the most efficient models from this study is already under development. Future research can explore different ANN architectures and optimization techniques, validate models with data from multiple producers and regions, and investigate the model's response to different seasonal and climatic conditions.

Keywords: agricultural technology, neural networks in agriculture, water efficiency, water use optimization

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1497 Adsorption of Xylene Cyanol FF onto Activated Carbon from Brachystegia Eurycoma Seed Hulls: Determination of the Optimal Conditions by Statistical Design of Experiments

Authors: F. G Okibe, C. E Gimba, V. O Ajibola, I. G Ndukwe, E. D. Paul

Abstract:

A full factorial experimental design technique at two levels and four factors (24) was used to optimize the adsorption at 615 nm of Xylene Cyanol ff in aqueous solutions onto activated carbon prepared from brachystegia eurycoma seed hulls by chemical carbonization method. The effect of pH (3 and 5), initial dye concentration (20 and 60 mg/l), adsorbent dosage (0.01 and 0.05 g), and contact time (30 and 60 min) on removal efficiency of the adsorbent for the dye were investigated at 298K. From the analysis of variance, response surface and cube plot, adsorbent dosage was observed to be the most significant factor affecting the adsorption process. However, from the interaction between the variables studied, the optimum removal efficiency was 96.80 % achieved with adsorbent dosage of 0.05 g, contact time 45 minutes, pH 3, and initial dye concentration 60 mg/l.

Keywords: factorial experimental design, adsorption, optimization, brachystegia eurycoma, xylene cyanol ff

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1496 Optimization of Tilt Angle for Solar Collectors: A Case Study for Bursa, Turkey

Authors: N. Arslanoglu

Abstract:

This paper deals with the optimum tilt angle for the solar collector in order to collect the maximum solar radiation. The optimum angle for tilted surfaces varying from 0 to 90 in steps of 1was computed. In present study, a theoretical model is used to predict the global solar radiation on a tilted surface and to obtain the optimum tilt angle for a solar collector in Bursa, Turkey. Global solar energy radiation on the solar collector surface with an optimum tilt angle is calculated for specific periods. It is determined that the optimum slope angle varies between 0 (June) and 59 (December) throughout the year. In winter (December, January, and February) the tilt should be 55, in spring (March, April, and May) 19.6, in summer (June, July, and August) 5.6, and in autumn (September, October, and November) 44.3. The yearly average of this value was obtained to be 31.1 and this would be the optimum fixed slope throughout the year.

Keywords: Bursa, global solar radiation, optimum tilt angle, tilted surface

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1495 A Study on How to Improve PMBOK (Project Management Body of Knowledge) Guidelines Performance by Simulation

Authors: Fatemeh Jaferi, Moslem Parsa, Seyed Mehdi Sajadi

Abstract:

The project-oriented organizations are more appropriate for sustainable environments. Any effective project-oriented organization should institutionalize its project management processes in such a manner to yield the greatest possible profits. The aim of this paper is to study the relationship between the project management PMBOK guideline (Project Management Body of Knowledge) and simulation technology in project-oriented organizations. The methodology involves using five steps for applying these two tools aimed at enhancing project management processes in the Lorestan Gas Corporation, as one of the project-oriented organization. Results show the implementation of such management approach leads to a 5% performance improvement and using PMBOK can be instrumental in effective delay management. The implementation of the aforementioned improvement package was effective in improving the efficiency of organizational processes; in terms of optimizing the resource utilization that has manifested itself in resource losses and cost reductions.

Keywords: project-orientation, processes, PMBOK, optimization, organization, management

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1494 Optimization of Extraction Conditions for Phenolic Compounds from Deverra Scoparia Coss and Dur

Authors: Roukia Hammoudi, Chabrouk Farid, Dehak Karima, Mahfoud Hadj Mahammed, Mohamed Didi Ouldelhadj

Abstract:

The objective of this study was to optimise the extraction conditions for phenolic compounds from Deverra scoparia Coss and Dur. Apiaceae plant by ultrasound assisted extraction (UAE). The effects of solvent type (acetone, ethanol and methanol), solvent concentration (%), extraction time (mins) and extraction temperature (°C) on total phenolic content (TPC) were determined. The optimum extraction conditions were found to be acetone concentration of 80%, extraction time of 25 min and extraction temperature of 25°C. Under the optimized conditions, the value for TPC was 9.68 ± 1.05 mg GAE/g of extract. The study of the antioxidant power of these oils was performed by the method of DPPH. The results showed that antioxidant activity of the Deverra scoparia essential oil was more effective as compared to ascorbic acid and trolox.

Keywords: Deverra scoparia, phenolic compounds, ultrasound assisted extraction, total phenolic content, antioxidant activity

Procedia PDF Downloads 603
1493 Optimization of Extraction Conditions for Phenolic Compounds from Deverra scoparia Coss. and Dur

Authors: Roukia Hammoudi, Dehak Karima, Chabrouk Farid, Mahfoud Hadj Mahammed, Mohamed Didi Ouldelhadj

Abstract:

The objective of this study was to optimise the extraction conditions for phenolic compounds from Deverra scoparia Coss and Dur. Apiaceae plant by ultrasound assisted extraction (UAE). The effects of solvent type (Acetone, Ethanol and methanol), solvent concentration (%), extraction time (mins) and extraction temperature (°C) on total phenolic content (TPC) were determined. the optimum extraction conditions were found to be acetone concentration of 80%, extraction time of 25 min and extraction temperature of 25°C. Under the optimized conditions, the value for TPC was 9.68 ± 1.05 mg GAE/g of extract. The study of the antioxidant power of these oils was performed by the method of DPPH. The results showed that antioxidant activity of the Deverra scoparia essential oil was more effective as compared to ascorbic acid and trolox.

Keywords: Deverra scoparia, phenolic compounds, ultrasound assisted extraction, total phenolic content, antioxidant activity

Procedia PDF Downloads 595
1492 Redefining the Croatian Economic Sentiment Indicator

Authors: Ivana Lolic, Petar Soric, Mirjana Cizmesija

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Based on Business and Consumer Survey (BCS) data, the European Commission (EC) regularly publishes the monthly Economic Sentiment Indicator (ESI) for each EU member state. ESI is conceptualized as a leading indicator, aimed ad tracking the overall economic activity. In calculating ESI, the EC employs arbitrarily chosen weights on 15 BCS response balances. This paper raises the predictive quality of ESI by applying nonlinear programming to find such weights that maximize the correlation coefficient of ESI and year-on-year GDP growth. The obtained results show that the highest weights are assigned to the response balances of industrial sector questions, followed by questions from the retail trade sector. This comes as no surprise since the existing literature shows that the industrial production is a plausible proxy for the overall Croatian economic activity and since Croatian GDP is largely influenced by the aggregate personal consumption.

Keywords: business and consumer survey, economic sentiment indicator, leading indicator, nonlinear optimization with constraints

Procedia PDF Downloads 462
1491 SFE as a Superior Technique for Extraction of Eugenol-Rich Fraction from Cinnamomum tamala Nees (Bay Leaf) - Process Analysis and Phytochemical Characterization

Authors: Sudip Ghosh, Dipanwita Roy, Dipan Chatterjee, Paramita Bhattacharjee, Satadal Das

Abstract:

Highest yield of eugenol-rich fractions from Cinnamomum tamala (bay leaf) leaves were obtained by supercritical carbon dioxide (SC-CO2), compared to hydro-distillation, organic solvents, liquid CO2 and subcritical CO2 extractions. Optimization of SC-CO2 extraction parameters was carried out to obtain an extract with maximum eugenol content. This was achieved using a sample size of 10 g at 55°C, 512 bar after 60 min at a flow rate of 25.0 cm3/sof gaseous CO2. This extract has the best combination of phytochemical properties such as phenolic content (1.77 mg gallic acid/g dry bay leaf), reducing power (0.80 mg BHT/g dry bay leaf), antioxidant activity (IC50 of 0.20 mg/ml) and anti-inflammatory potency (IC50 of 1.89 mg/ml). Identification of compounds in this extract was performed by GC-MS analysis and its antimicrobial potency was also evaluated. The MIC values against E. coli, P. aeruginosa and S. aureus were 0.5, 0.25 and 0.5 mg/ml, respectively.

Keywords: antimicrobial potency, Cinnamomum tamala, eugenol, supercritical carbon dioxide extraction

Procedia PDF Downloads 341
1490 Synthesis of Carboxylate Gemini Surfactant

Authors: Rui Wang, Shanfa Tang, Yuanwu Dong, Siyao Wang

Abstract:

A carboxylate Gemini surfactant N, N`-bis (3-chloro-2 -hydroxypropane-N-dodecyl secondary amine) p-phenylenediamine diacetate sodium (GD12-P-12) was synthesized by substitution and ring-opening reaction from p-phenylenediamine, sodium chloroacetate, epichlorohydrin, and dodecylamine. The synthesis conditions were optimized by controlling variables. The structure of GD12-P-12 was characterized by FT-IR and 1H NMR, and its foam performance, interfacial tension, viscosity was evaluated. The results show that the molecular structure of the synthesized product is consistent with that of the target product, the GD12-P-12 can reduce the oil-water interfacial tension to 7.49×10⁻³mN/m (ultra-low interfacial tension level) in 20min. GD12-P-12 surfactant has excellent foam performance, ultra-low interfacial tension, good temperature-resistant viscosity-increasing properties, has good application prospect in foam flooding.

Keywords: gemini surfactant, optimization of synthesis conditions, foam performance, low interfacial tension

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1489 Co-Culture with Murine Stromal Cells Enhances the In-vitro Expansion of Hematopoietic Stem Cells in Response to Low Concentrations of Trans-Resveratrol

Authors: Mariyah Poonawala, Selvan Ravindran, Anuradha Vaidya

Abstract:

Despite much progress in understanding the regulatory factors and cytokines that support the maturation of the various cell lineages of the hematopoietic system, factors that govern the self-renewal and proliferation of hematopoietic stem cells (HSCs) is still a grey area of research. Hematopoietic stem cell transplantation (HSCT) has evolved over the years and gained tremendous importance in the treatment of both malignant and non-malignant diseases. However, factors such as graft rejection and multiple organ failure have challenged HSCT from time to time, underscoring the urgent need for development of milder processes for successful hematopoietic transplantation. An emerging concept in the field of stem cell biology states that the interactions between the bone-marrow micro-environment and the hematopoietic stem and progenitor cells is essential for regulation, maintenance, commitment and proliferation of stem cells. Understanding the role of mesenchymal stromal cells in modulating the functionality of HSCs is, therefore, an important area of research. Trans-resveratrol has been extensively studied for its various properties to combat and prevent cancer, diabetes and cardiovascular diseases etc. The aim of the present study was to understand the effect of trans-resveratrol on HSCs using single and co-culture systems. We have used KG1a cells since it is a well accepted hematopoietic stem cell model system. Our preliminary experiments showed that low concentrations of trans-resveratrol stimulated the HSCs to undergo proliferation whereas high concentrations of trans-resveratrol did not stimulate the cells to proliferate. We used a murine fibroblast cell line, M210B4, as a stromal feeder layer. On culturing the KG1a cells with M210B4 cells, we observed that the stimulatory as well as inhibitory effects of trans-resveratrol at low and high concentrations respectively, were enhanced. Our further experiments showed that low concentration of trans-resveratrol reduced the generation of reactive oxygen species (ROS) and nitric oxide (NO) whereas high concentrations increased the oxidative stress in KG1a cells. We speculated that perhaps the oxidative stress was imposing inhibitory effects at high concentration and the same was confirmed by performing an apoptotic assay. Furthermore, cell cycle analysis and growth kinetic experiments provided evidence that low concentration of trans-resveratrol reduced the doubling time of the cells. Our hypothesis is that perhaps at low concentration of trans-resveratrol the cells get pushed into the G0/G1 phase and re-enter the cell cycle resulting in their proliferation, whereas at high concentration the cells are perhaps arrested at G2/M phase or at cytokinesis and therefore undergo apoptosis. Liquid Chromatography-Quantitative-Time of Flight–Mass Spectroscopy (LC-Q-TOF MS) analyses indicated the presence of trans-resveratrol and its metabolite(s) in the supernatant of the co-cultured cells incubated with high concentration of trans-resveratrol. We conjecture that perhaps the metabolites of trans-resveratrol are responsible for the apoptosis observed at the high concentration. Our findings may shed light on the unsolved problems in the in vitro expansion of stem cells and may have implications in the ex vivo manipulation of HSCs for therapeutic purposes.

Keywords: co-culture system, hematopoietic micro-environment, KG1a cell line, M210B4 cell line, trans-resveratrol

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1488 Presenting a Job Scheduling Algorithm Based on Learning Automata in Computational Grid

Authors: Roshanak Khodabakhsh Jolfaei, Javad Akbari Torkestani

Abstract:

As a cooperative environment for problem-solving, it is necessary that grids develop efficient job scheduling patterns with regard to their goals, domains and structure. Since the Grid environments facilitate distributed calculations, job scheduling appears in the form of a critical problem for the management of Grid sources that influences severely on the efficiency for the whole Grid environment. Due to the existence of some specifications such as sources dynamicity and conditions of the network in Grid, some algorithm should be presented to be adjustable and scalable with increasing the network growth. For this purpose, in this paper a job scheduling algorithm has been presented on the basis of learning automata in computational Grid which the performance of its results were compared with FPSO algorithm (Fuzzy Particle Swarm Optimization algorithm) and GJS algorithm (Grid Job Scheduling algorithm). The obtained numerical results indicated the superiority of suggested algorithm in comparison with FPSO and GJS. In addition, the obtained results classified FPSO and GJS in the second and third position respectively after the mentioned algorithm.

Keywords: computational grid, job scheduling, learning automata, dynamic scheduling

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1487 Efficient Ground Targets Detection Using Compressive Sensing in Ground-Based Synthetic-Aperture Radar (SAR) Images

Authors: Gherbi Nabil

Abstract:

Detection of ground targets in SAR radar images is an important area for radar information processing. In the literature, various algorithms have been discussed in this context. However, most of them are of low robustness and accuracy. To this end, we discuss target detection in SAR images based on compressive sensing. Firstly, traditional SAR image target detection algorithms are discussed, and their limitations are highlighted. Secondly, a compressive sensing method is proposed based on the sparsity of SAR images. Next, the detection problem is solved using Multiple Measurements Vector configuration. Furthermore, a robust Alternating Direction Method of Multipliers (ADMM) is developed to solve the optimization problem. Finally, the detection results obtained using raw complex data are presented. Experimental results on real SAR images have verified the effectiveness of the proposed algorithm.

Keywords: compressive sensing, raw complex data, synthetic aperture radar, ADMM

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1486 Optimizing Microgrid Operations: A Framework of Adaptive Model Predictive Control

Authors: Ruben Lopez-Rodriguez

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In a microgrid, diverse energy sources (both renewable and non-renewable) are combined with energy storage units to form a localized power system. Microgrids function as independent entities, capable of meeting the energy needs of specific areas or communities. This paper introduces a Model Predictive Control (MPC) approach tailored for grid-connected microgrids, aiming to optimize their operation. The formulation employs Mixed-Integer Programming (MIP) to find optimal trajectories. This entails the fulfillment of continuous and binary constraints, all while accounting for commutations between various operating conditions such as storage unit charge/discharge, import/export from/towards the main grid, as well as asset connection/disconnection. To validate the proposed approach, a microgrid case study is conducted, and the simulation results are compared with those obtained using a rule-based strategy.

Keywords: microgrids, mixed logical dynamical systems, mixed-integer optimization, model predictive control

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1485 Active Flutter Suppression of Sports Aircraft Tailplane by Supplementary Control Surface

Authors: Aleš Kratochvíl, Svatomír Slavík

Abstract:

The paper presents an aircraft flutter suppression by active damping of supplementary control surface at trailing edge. The mathematical model of thin oscillation airfoil with control surface driven by pilot is developed. The supplementary control surface driven by control law is added. Active damping of flutter by several control law is present. The structural model of tailplane with an aerodynamic strip theory based on the airfoil model is developed by a finite element method. The optimization process of stiffens parameters is carried out to match the structural model with results from a ground vibration test of a small sport airplane. The implementation of supplementary control surface driven by control law is present. The active damping of tailplane model is shown.

Keywords: active damping, finite element method, flutter, tailplane model

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1484 Systematic Review of Quantitative Risk Assessment Tools and Their Effect on Racial Disproportionality in Child Welfare Systems

Authors: Bronwen Wade

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Over the last half-century, child welfare systems have increasingly relied on quantitative risk assessment tools, such as actuarial or predictive risk tools. These tools are developed by performing statistical analysis of how attributes captured in administrative data are related to future child maltreatment. Some scholars argue that attributes in administrative data can serve as proxies for race and that quantitative risk assessment tools reify racial bias in decision-making. Others argue that these tools provide more “objective” and “scientific” guides for decision-making instead of subjective social worker judgment. This study performs a systematic review of the literature on the impact of quantitative risk assessment tools on racial disproportionality; it examines methodological biases in work on this topic, summarizes key findings, and provides suggestions for further work. A search of CINAHL, PsychInfo, Proquest Social Science Premium Collection, and the ProQuest Dissertations and Theses Collection was performed. Academic and grey literature were included. The review includes studies that use quasi-experimental methods and development, validation, or re-validation studies of quantitative risk assessment tools. PROBAST (Prediction model Risk of Bias Assessment Tool) and CHARMS (CHecklist for critical Appraisal and data extraction for systematic Reviews of prediction Modelling Studies) were used to assess the risk of bias and guide data extraction for risk development, validation, or re-validation studies. ROBINS-I (Risk of Bias in Non-Randomized Studies of Interventions) was used to assess for bias and guide data extraction for the quasi-experimental studies identified. Due to heterogeneity among papers, a meta-analysis was not feasible, and a narrative synthesis was conducted. 11 papers met the eligibility criteria, and each has an overall high risk of bias based on the PROBAST and ROBINS-I assessments. This is deeply concerning, as major policy decisions have been made based on a limited number of studies with a high risk of bias. The findings on racial disproportionality have been mixed and depend on the tool and approach used. Authors use various definitions for racial equity, fairness, or disproportionality. These concepts of statistical fairness are connected to theories about the reason for racial disproportionality in child welfare or social definitions of fairness that are usually not stated explicitly. Most findings from these studies are unreliable, given the high degree of bias. However, some of the less biased measures within studies suggest that quantitative risk assessment tools may worsen racial disproportionality, depending on how disproportionality is mathematically defined. Authors vary widely in their approach to defining and addressing racial disproportionality within studies, making it difficult to generalize findings or approaches across studies. This review demonstrates the power of authors to shape policy or discourse around racial justice based on their choice of statistical methods; it also demonstrates the need for improved rigor and transparency in studies of quantitative risk assessment tools. Finally, this review raises concerns about the impact that these tools have on child welfare systems and racial disproportionality.

Keywords: actuarial risk, child welfare, predictive risk, racial disproportionality

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1483 A Reinforcement Learning Approach for Evaluation of Real-Time Disaster Relief Demand and Network Condition

Authors: Ali Nadi, Ali Edrissi

Abstract:

Relief demand and transportation links availability is the essential information that is needed for every natural disaster operation. This information is not in hand once a disaster strikes. Relief demand and network condition has been evaluated based on prediction method in related works. Nevertheless, prediction seems to be over or under estimated due to uncertainties and may lead to a failure operation. Therefore, in this paper a stochastic programming model is proposed to evaluate real-time relief demand and network condition at the onset of a natural disaster. To address the time sensitivity of the emergency response, the proposed model uses reinforcement learning for optimization of the total relief assessment time. The proposed model is tested on a real size network problem. The simulation results indicate that the proposed model performs well in the case of collecting real-time information.

Keywords: disaster management, real-time demand, reinforcement learning, relief demand

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1482 Optimal Design of Redundant Hybrid Manipulator for Minimum Singularity

Authors: Arash Rahmani, Ahmad Ghanbari, Abbas Baghernezhad, Babak Safaei

Abstract:

In the design of parallel manipulators, usually mean value of a dexterity measure over the workspace volume is considered as the objective function to be used in optimization algorithms. The mentioned indexes in a hybrid parallel manipulator (HPM) are quite complicated to solve thanks to infinite solutions for every point within the workspace of the redundant manipulators. In this paper, spatial isotropic design axioms are extended as a well-known method for optimum design of manipulators. An upper limit for the isotropy measure of HPM is calculated and instead of computing and minimizing isotropy measure, minimizing the obtained limit is considered. To this end, two different objective functions are suggested which are obtained from objective functions of comprising modules. Finally, by using genetic algorithm (GA), the best geometric parameters for a specific hybrid parallel robot which is composed of two modified Gough-Stewart platforms (MGSP) are achieved.

Keywords: hybrid manipulator, spatial isotropy, genetic algorithm, optimum design

Procedia PDF Downloads 336
1481 Methodology of Choosing Technology and Sizing of the Hybrid Energy Storage Based on Cost-benefit Analysis

Authors: Krzysztof Rafał, Weronika Radziszewska, Hubert Biedka, Oskar Grabowski, Krzysztof Mik

Abstract:

We present a method to choose energy storage technologies and their parameters for the economic operation of a microgrid. A grid-connected system with local loads and PV generation is assumed, where an energy storage system (ESS) is attached to minimize energy cost by providing energy balancing and arbitrage functionalities. The ESS operates in a hybrid configuration and consists of two unique technologies operated in a coordinated way. Based on given energy profiles and economical data a model calculates financial flow for ESS investment, including energy cost and ESS depreciation resulting from degradation. The optimization strategy proposes a hybrid set of two technologies with their respective power and energy ratings to minimize overall system cost in a given timeframe. Results are validated through microgrid simulations using real-life input profiles.

Keywords: energy storage, hybrid energy storage, cost-benefit analysis, microgrid, battery sizing

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1480 Sorption of Congo Red from Aqueous Solution by Surfactant-Modified Bentonite: Kinetic and Factorial Design Study

Authors: B. Guezzen, M. A. Didi, B. Medjahed

Abstract:

An organoclay (HDTMA-B) was prepared from sodium bentonite (Na-B). The starting material was modified using the hexadecyltrimethylammonium ion (HDTMA+) in the amounts corresponding to 100 % of the CEC value. Batch experiments were carried out in order to model and optimize the sorption of Congo red dye from aqueous solution. The pseudo-first order and pseudo-second order kinetic models have been developed to predict the rate constant and the sorption capacity at equilibrium with the effect of temperature, the solid/solution ratio and the initial dye concentration. The equilibrium time was reached within 60 min. At room temperature (20 °C), optimum dye sorption of 49.4 mg/g (98.9%) was achieved at pH 6.6, sorbent dosage of 1g/L and initial dye concentration of 50 mg/L, using surfactant modified bentonite. The optimization of adsorption parameters mentioned above on dye removal was carried out using Box-Behnken design. The sorption parameters were analyzed statistically by means of variance analysis by using the Statgraphics Centurion XVI software.

Keywords: adsorption, dye, factorial design, kinetic, organo-bentonite

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1479 Bit Error Rate Monitoring for Automatic Bias Control of Quadrature Amplitude Modulators

Authors: Naji Ali Albakay, Abdulrahman Alothaim, Isa Barshushi

Abstract:

The most common quadrature amplitude modulator (QAM) applies two Mach-Zehnder Modulators (MZM) and one phase shifter to generate high order modulation format. The bias of MZM changes over time due to temperature, vibration, and aging factors. The change in the biasing causes distortion to the generated QAM signal which leads to deterioration of bit error rate (BER) performance. Therefore, it is critical to be able to lock MZM’s Q point to the required operating point for good performance. We propose a technique for automatic bias control (ABC) of QAM transmitter using BER measurements and gradient descent optimization algorithm. The proposed technique is attractive because it uses the pertinent metric, BER, which compensates for bias drifting independently from other system variations such as laser source output power. The proposed scheme performance and its operating principles are simulated using OptiSystem simulation software for 4-QAM and 16-QAM transmitters.

Keywords: automatic bias control, optical fiber communication, optical modulation, optical devices

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1478 Streamlines: Paths of Fluid Flow through Sandstone Samples Based on Computed Microtomography

Authors: Ł. Kaczmarek, T. Wejrzanowski, M. Maksimczuk

Abstract:

The study presents the use of the numerical calculations based on high-resolution computed microtomography in analysis of fluid flow through Miocene sandstones. Therefore, the permeability studies of rocks were performed. Miocene samples were taken from well S-3, located in the eastern part of the Carpathian Foredeep. For aforementioned analysis, two series of X-ray irradiation were performed. The first set of samples was selected to obtain the spatial distribution of grains and pores. At this stage of the study length of voxel side amounted 27 microns. The next set of X-ray irradation enabled recognition of microstructural components as well as petrophysical features. The length of voxel side in this stage was up to 2 µm. Based on this study, the samples were broken down into two distinct groups. The first one represents conventional reservoir deposits, in opposite to second one - unconventional type. Appropriate identification of petrophysical parameters such as porosity and permeability of the formation is a key element for optimization of the reservoir development.

Keywords: grains, permeability, pores, pressure distribution

Procedia PDF Downloads 254