Search results for: natural gas optimization

Authors: K.Narasimhulu, Y. Pydi Setty

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The objective of this present study is the optimization of process parameters in biosorption of Ni(II) and Cd(II) ions by Pseudomonas putida using Response Surface Methodology in a Packed bed bioreactor. The experimental data were also tested with theoretical models to find the best fit model. The present paper elucidates RSM as an efficient approach for predictive model building and optimization of Ni(II) and Cd(II) ions using Pseudomonas putida. In packed bed biosorption studies, comparison of the breakthrough curves of Ni(II) and Cd(II) for Agar immobilized and PAA immobilized Pseudomonas putida at optimum conditions of flow rate of 300 mL/h, initial metal ion concentration of 100 mg/L and bed height of 20 cm with weight of biosorbent of 12 g, it was found that the Agar immobilized Pseudomonas putida showed maximum percent biosorption and bed saturation occurred at 20 minutes. Optimization results of Ni(II) and Cd(II) by Pseudomonas putida from the Design Expert software were obtained as bed height of 19.93 cm, initial metal ion concentration of 103.85 mg/L, and flow rate of 310.57 mL/h. The percent biosorption of Ni(II) and Cd(II) is 87.2% and 88.2% respectively. The predicted optimized parameters are in agreement with the experimental results.

Keywords: packed bed bioreactor, response surface mthodology, pseudomonas putida, biosorption, waste water

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Authors: Nesreddine Djafar Henni, Nassim Djedoui, Rachid Chebili

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Recent decades have witnessed significant efforts being made to optimize different types of structures and components. The concept of cost optimization in reinforced concrete structures, which aims at minimizing financial resources while ensuring maximum building safety, comprises multiple materials, and the objective function for their optimal design is derived from the construction cost of the steel as well as concrete that significantly contribute to the overall weight of reinforced concrete (RC) structures. To achieve this objective, this work has been devoted to optimizing the structural design of 3D RC frame buildings which integrates, for the first time, the Algerian regulations. Three different test examples were investigated to assess the efficiency of our work in optimizing RC frame buildings. The hybrid GWOPSO algorithm is used, and 30000 generations are made. The cost of the building is reduced by iteration each time. Concrete and reinforcement bars are used in the building cost. As a result, the cost of a reinforced concrete structure is reduced by 30% compared with the initial design. This result means that the 3D cost-design optimization of the framed structure is successfully achieved.

Keywords: optimization, automation, API, Malab, RC structures

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Authors: P. Parthiban, Sonu Rajak, R. Dhanalakshmi

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This paper presents an Ant Colony Optimization (ACO) approach, combined with a Speed Optimization Algorithm (SOA) to solve the Vehicle Routing Problem (VRP) with environmental considerations, which is well known as Pollution-Routing Problem (PRP). It consists of routing a number of vehicles to serve a set of customers, and determining fuel consumption, driver wages and their speed on each route segment, while respecting the capacity constraints and time windows. Since VRP is NP-hard problem, so PRP also a NP-hard problem, which requires metaheuristics to solve this type of problems. The proposed solution method consists of two stages. Stage one is to solve a Vehicle Routing Problem with Time Window (VRPTW) using ACO and in the second stage, a SOA is run on the resulting VRPTW solution. Given a vehicle route, the SOA consists of finding the optimal speed on each arc of the route to minimize an objective function comprising fuel consumption costs and driver wages. The proposed algorithm tested on benchmark problem, the preliminary results show that the proposed algorithm can provide good solutions within reasonable computational time.

Keywords: ant colony optimization, CO2 emissions, speed optimization, vehicle routing

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Authors: Mentor Sulollari

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Albania, according to (UNU-EHS) United Nations University, Institute for Environment and Human Security studies for 2015, is listed as the number one country in Europe for the possibility to be caught by natural catastrophes. This is conditioned by unstudied human activity, which has seriously damaged the environment. Albanian part of Ohrid graben that lies in Southeast of Albania, is endangered by landslides and floods, as a result of uncontrolled urban development and low level of investment in infrastructure, rugged terrain in its western part and capricious climate caused by global warming. To be dealt with natural disasters, which cause casualties and material damage, it is important to study them in order to anticipate and reduce damages in future. As part of this study is the construction of natural hazards map, which show us where they are distributed, and which are the vulnerable areas. This article will also be dealing with socio-economic and environmental costs of those events and what are the measures to be taken to reduce them.

Keywords: flooding, landslides, natural catastrophes mapping, Pogradec, lake Ohrid, Albanian part of Ohrid graben

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Authors: Sneha Thakur, Sanjeev Karmakar

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This paper proposed hybrid Particle Swarm Optimization (PSO) – Long-Short Term Memory (LSTM) model for groundwater level prediction. The evaluation of the performance is realized using the parameters: root mean square error (RMSE) and mean absolute error (MAE). Ground water level forecasting will be very effective for planning water harvesting. Proper calculation of water level forecasting can overcome the problem of drought and flood to some extent. The objective of this work is to develop a ground water level forecasting model using deep learning technique integrated with optimization technique PSO by applying 29 years data of Chhattisgarh state, In-dia. It is important to find the precise forecasting in case of ground water level so that various water resource planning and water harvesting can be managed effectively.

Keywords: long short-term memory, particle swarm optimization, prediction, deep learning, groundwater level

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Authors: Sidra Shaheen, Nadir Naveed Siddiqui, Shah Ali Ul Qader

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In recent years, significant progress has been made in discovering and developing new bacterial polysaccharides producing organisms possessing extremely functional properties. Levan is a natural biopolymer of fructose which is produced by transfructosylation reaction in the presence of levansucrase. It is one of the industrially promising enzymes that offer a variety of industrial applications in the field of cosmetics, foods and pharmaceuticals. Although levan has significant applications but the yield of levan produced is not equal to other biopolymers due to the inefficiency of producer microorganism. Among wide range of levansucrase producing microorganisms, Zymomonas mobilis is considered as a potential candidate for large scale production of this natural polysaccharide. The present investigation is concerned with the isolation of levansucrase producing natural isolate having maximum enzyme production. Furthermore, production parameters were optimized to get higher enzyme yield. Levansucrase was partially purified and characterized to study its applicability on industrial scale. The results of this study revealed that the bacterial strain Z. mobilis KIBGE-IB14 was the best producer of levansucrase. Bacterial growth and enzyme production was greatly influenced by physical and chemical parameters. Maximum levansucrase production was achieved after 24 hours of fermentation at 30°C using modified medium of pH-6.5. Contrary to other levansucrases, the one presented in the current study is able to produce high amount of products in relatively short period of time with optimum temperature at 35°C. Due to these advantages, this enzyme can be used on large scale for commercial production of levan and other important metabolites.

Keywords: levansucrase, metabolites, polysaccharides, transfructosylation

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Authors: Soumitra Satapathi, Anubhav Raghav

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Perovskite solar cell technology has passed through a phase of unprecedented growth in the efficiency scale from 3.8% to above 22% within a half decade. This technology has drawn tremendous research interest. It has been observed that performances of perovskite based solar cells are extremely dependent on the morphology and crystallinity of the perovskite layer. It has also been observed that device lifetime depends on the perovskite morphology; devices with larger perovskite grains degrade slowly than those of the smaller ones. Various methods of perovskite growth have been applied to achieve the most appropriate morphology necessary for high efficient solar cells. The recent progress in morphology optimization by various methods emphasizing on grain sizes, stoichiometry, and ambient compatibility as well as photophysics study in air-processed perovskite solar cells will be discussed.

Keywords: perovskite solar cells, morphology optimization, photophysics study, air-processed solar cells

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Authors: Malcolm Dinovitzer, Calvin Miller, Adam Hacker, Gabriel Wong, Zach Annen, Padmassun Rajakareyar, Jordan Mulvihill, Mostafa S.A. ElSayed

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The research work presented in this paper is developed by the Blended Wing Body (BWB) Unmanned Aerial Vehicle (UAV) team, a fourth-year capstone project at Carleton University Department of Mechanical and Aerospace Engineering. Here, a clean sheet UAV with BWB configuration is designed and optimized using Multiscale Design Optimization (MSDO) approach employing lattice materials taking into consideration design for additive manufacturing constraints. The BWB-UAV is being developed with a mission profile designed for surveillance purposes with a minimum payload of 1000 grams. To demonstrate the design methodology, a single design loop of a sample rib from the airframe is shown in details. This includes presentation of the conceptual design, materials selection, experimental characterization and residual thermal stress distribution analysis of additively manufactured materials, manufacturing constraint identification, critical loads computations, stress analysis and design optimization. A dynamic turbulent critical load case was identified composed of a 1-g static maneuver with an incremental Power Spectral Density (PSD) gust which was used as a deterministic design load case for the design optimization. 2D flat plate Doublet Lattice Method (DLM) was used to simulate aerodynamics in the aeroelastic analysis. The aerodynamic results were verified versus a 3D CFD analysis applying Spalart-Allmaras and SST k-omega turbulence to the rigid UAV and vortex lattice method applied in the OpenVSP environment. Design optimization of a single rib was conducted using topology optimization as well as MSDO. Compared to a solid rib, weight savings of 36.44% and 59.65% were obtained for the topology optimization and the MSDO, respectively. These results suggest that MSDO is an acceptable alternative to topology optimization in weight critical applications while preserving the functional requirements.

Keywords: blended wing body, multiscale design optimization, additive manufacturing, unmanned aerial vehicle

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Authors: Iannick Gagnon, Alain April

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The performance of a metaheuristic on a given problem class depends on the class itself and the choice of parameters. Parameter tuning is the most time-consuming phase of the optimization process after the main calculations and it often nullifies the speed advantage of metaheuristics over traditional optimization algorithms. Several off-the-shelf parameter tuning algorithms are available, but when the objective function is expensive to evaluate, these can be prohibitively expensive to use. This paper presents a surrogate-like method for finding adequate parameters using fitness landscape analysis on simple benchmark functions and real-world objective functions. The result is a simple compound similarity metric based on the empirical correlation coefficient and a measure of convexity. It is then used to find the best benchmark functions to serve as surrogates. The near-optimal parameter set is then found using fractional factorial design. The real-world problem of NACA airfoil lift coefficient maximization is used as a preliminary proof of concept. The overall aim of this research is to reduce the computational overhead of metaheuristics parameterization.

Keywords: metaheuristics, stochastic optimization, particle swarm optimization, exploratory landscape analysis

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Authors: Do-Jin Jang, Sung-Ah Kim

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A kinetic façade responds to user requirements and environmental conditions.  In designing a kinetic façade, kinetic patterns play a key role in determining its performance. This paper proposes a biomimetic method for the multi-objective optimization for kinetic façade design. The autonomous decentralized control system is combined with flocking algorithm. The flocking agents are autonomously reacting to sensor values and bring about kinetic patterns changing over time. A series of experiments were conducted to verify the potential and limitations of the flocking based decentralized control. As a result, it could show the highest performance balancing multiple objectives such as solar radiation and openness among the comparison group.

Keywords: biomimicry, flocking algorithm, autonomous decentralized control, multi-objective optimization

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Authors: Abdulrahman Nami Almutairi

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In the face of escalating climate change concerns, the concept of smart cities emerges as a promising approach to mitigate carbon emissions and move towards carbon neutrality. This paper provides a comprehensive review of the role of Natural Gas in achieving carbon neutrality. Natural gas has often been seen as a transitional fuel in the context of reducing carbon emissions. Its main role stems from being cleaner than coal and oil when burned for electricity generation and industrial processes. The urgent need to address this global issue has prompted a global shift towards cleaner energy sources and sustainable practices. In this endeavor, natural gas has emerged as a pivotal player, hailed for its potential to mitigate carbon emissions, and facilitate the transition to a low-carbon economy. With its lower carbon intensity compared to conventional fossil fuels, natural gas presents itself as a promising alternative for meeting energy demands while reducing environmental impact. As the world stands at a critical juncture in the fight against climate change, exploring the potential of natural gas as a transitional fuel offers insights into pathways towards a more sustainable and resilient future. By critically evaluating its opportunities and challenges, we can harness the potential of natural gas as a transitional fuel while advancing towards a cleaner, more resilient energy system. Through collaborative efforts and informed decision-making, we can pave the way for a future where energy is not only abundant but also environmentally sustainable and socially equitable.

Keywords: natural gas, clean fuel, carbon emissions, global warming, environmental protection

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Authors: Ambali Alade Odebowale, Andargachew Mekonnen Berhe, Haroldo T. Hattori, Andrey E. Miroshnichenko

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Solar thermophotovoltaic systems (STPV) have emerged as a promising solution to overcome the Shockley-Queisser limit, a significant impediment in the direct conversion of solar radiation into electricity using conventional solar cells. The STPV system comprises essential components such as an optical concentrator, selective emitter, and a thermophotovoltaic (TPV) cell. The pivotal element in achieving high efficiency in an STPV system lies in the design of a spectrally selective emitter or absorber. Traditional methods for designing and optimizing selective emitters are often time-consuming and may not yield highly selective emitters, posing a challenge to the overall system performance. In recent years, the application of machine learning techniques in various scientific disciplines has demonstrated significant advantages. This paper proposes a novel nanostructure composed of four-layered materials (SiC/W/SiO2/W) to function as a selective emitter in the energy conversion process of an STPV system. Unlike conventional approaches widely adopted by researchers, this study employs a machine learning-based approach for the design and optimization of the selective emitter. Specifically, a random forest algorithm (RFA) is employed for the design of the selective emitter, while the optimization process is executed using genetic algorithms. This innovative methodology holds promise in addressing the challenges posed by traditional methods, offering a more efficient and streamlined approach to selective emitter design. The utilization of a machine learning approach brings several advantages to the design and optimization of a selective emitter within the STPV system. Machine learning algorithms, such as the random forest algorithm, have the capability to analyze complex datasets and identify intricate patterns that may not be apparent through traditional methods. This allows for a more comprehensive exploration of the design space, potentially leading to highly efficient emitter configurations. Moreover, the application of genetic algorithms in the optimization process enhances the adaptability and efficiency of the overall system. Genetic algorithms mimic the principles of natural selection, enabling the exploration of a diverse range of emitter configurations and facilitating the identification of optimal solutions. This not only accelerates the design and optimization process but also increases the likelihood of discovering configurations that exhibit superior performance compared to traditional methods. In conclusion, the integration of machine learning techniques in the design and optimization of a selective emitter for solar thermophotovoltaic systems represents a groundbreaking approach. This innovative methodology not only addresses the limitations of traditional methods but also holds the potential to significantly improve the overall performance of STPV systems, paving the way for enhanced solar energy conversion efficiency.

Keywords: emitter, genetic algorithm, radiation, random forest, thermophotovoltaic

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Authors: Mehrdad Karimi, Farshad Negintaji

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This study has examined the appearance of identity in the urban landscape and its effects on the natural factors. For this purpose, the components of place identity, emotional attachment, place dependence and social bond which totally constitute place attachment, measures it in three domains of cognitive (place identity), affective (emotional attachment) and behavioral (place dependence and social bond). In order to measure the natural factors, three components of the absolute elements, living entities, natural elements have been measured. The study is descriptive and the statistical population has been Yasouj, a city in Iran. To analyze the data the SPSS software has been used. The results in two level of descriptive and inferential statistics have been investigated. In the inferential statistics, Pearson correlation coefficient test has been used to evaluate the research hypotheses. In this study, the variable of identity is in high level and the natural factors are also in high level. These results indicate a positive relationship between place identity and natural factors. Development of environment and reaching the quality level of the personality or identity will develop the individual and society.

Keywords: identity, place identity, landscape, urban landscape, landscaping

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Authors: Abdel-Tawab H. Mossa

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Synthetic pesticides are widely used in large-scale worldwide for control pests in agriculture and public health sectors in both developed and developing countries. Although the positive role of pesticides, they have many adverse toxic effects on humans, animals, and the ecosystem. Therefore, in the last few years, scientists have been searching for new active compounds from natural resources as an alternative to synthetic pesticides. Currently, many commercial natural pesticides are available commercially worldwide. These products are recommended for uses in organic farmers and considered as safe pesticides. This paper focuses on the adverse effects of natural pesticides on mammals. Available commercial pesticides in the market contain essential oils (e.g. pepper, cinnamon, and garlic), plant extracts, microorganism (e.g. bacteria, fungi or their toxin), mineral oils and some active compounds from natural recourses e.g. spinosad, neem, pyrethrum, rotenone, abamectin and other active compounds from essential oils (EOs). Some EOs components, e.g., thujone, pulegone, and thymol have high acute toxicity (LD50) is 87.5, 150 and 980 mg/kg. B.wt on mice, respectively. Natural pesticides such as spinosad, pyrethrum, neem, abamectin, and others have toxicological effects to mammals and ecosystem. These compounds were found to cause hematotoxicity, hepato-renal toxicity, biochemical alteration, reproductive toxicity, genotoxicity, and mutagenicity. It caused adverse effects on the ecosystem. Therefore, natural pesticides in general not safe and have high acute toxicity and can induce adverse effects at long-term exposure.

Keywords: natural pesticides, toxicity, safety, genotoxicity, ecosystem, biochemical

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Authors: Muhammad Zaheer Babar, Amer Kashif, Muhammad Rizwan Javed

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Nowadays distributed generation integration is best way to overcome the increasing load demand. Optimal allocation of distributed generation plays a vital role in reducing system losses and improves voltage profile. In this paper, a Meta heuristic technique is proposed for allocation of DG in order to reduce power losses and improve voltage profile. The proposed technique is based on Multi Objective Particle Swarm optimization. Fewer control parameters are needed in this algorithm. Modification is made in search space of PSO. The effectiveness of proposed technique is tested on IEEE 33 bus test system. Single DG as well as multiple DG scenario is adopted for proposed method. Proposed method is more effective as compared to other Meta heuristic techniques and gives better results regarding system losses and voltage profile.

Keywords: Distributed generation (DG), Multi Objective Particle Swarm Optimization (MOPSO), particle swarm optimization (PSO), IEEE standard Test System

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Authors: Hanmei Peng, Yiqun Wang, Mao Tan, Zhuocen Dai, Yongxin Su

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Efficient energy management in multi-microgrid distribution systems holds significant importance for enhancing the economic benefits of regional power grids. To better balance conflicts among various stakeholders, a two-stage game-based collaborative optimization approach is proposed in this paper, effectively addressing the realistic scenario involving both competition and collaboration among stakeholders. The first stage, aimed at maximizing individual benefits, involves constructing a non-cooperative tariff game model for the distribution network and surplus microgrid. In the second stage, considering power flow and physical line capacity constraints we establish a cooperative P2P game model for the multi-microgrid distribution system, and the optimization involves employing the Lagrange method of multipliers to handle complex constraints. Simulation results demonstrate that the proposed approach can effectively improve the system economics while harmonizing individual and collective rationality.

Keywords: cooperative game, collaborative optimization, multi-microgrid distribution system, non-cooperative game

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Authors: Tamrat Tesfaye, Bruce Sithole, K. Shabaridharan

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The use of natural dyes to replace synthetic dyes has been advocated for to circumvent the environmental problems associated with synthetic dyes. This paper is a preliminary study on the use of natural dyes extracted from eucalyptus and mango trees. Dyes extracted from eucalyptus bark gave more colourized material than the dyes extracted from eucalyptus leaves and mango pills and leaves. Additionally, the extracts exhibited a deeper colour shade. Cotton fiber dyed using the same dye but with different mordants resulted in fabric that exhibited different colours. It appears that natural dyes from these plants could be effective dyes for use on cotton fabrics especially considering that the dyes exhibited excellent colour fastness.

Keywords: natural dyes, mango, eucalyptus, cotton, mordants, colour fastness

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Authors: J. Zach, J. Hroudova, J. Brozovsky

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Thermal insulation materials based on natural fibers represent a very promising area of materials based on natural easy renewable row sources. These materials may be in terms of the properties of most competing synthetic insulations, but show somewhat higher moisture sensitivity and thermal insulation properties are strongly influenced by the density and orientation of fibers. The paper described the problem of hygrothermal behavior of thermal insulation materials based on natural plant and animal fibers. This is especially the dependence of the thermal properties of these materials on the type of fiber, bulk density, temperature, moisture and the fiber orientation.

Keywords: thermal insulating materials, hemp fibers, sheep wool fibers, thermal conductivity, moisture

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Authors: Ahmed El-Ghorab

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Indigenous foods are promising sources of various chemical bioactive compounds such as vitamins, phenolic compounds and carotenoids. Therefore, the presence o different bioactive compounds in fruits could be used to retard or prevent various diseases such as cardiovascular and cancer. This is an update report on nutritional compositions and health promoting phytochemicals of different indigenous food . This different type of fruits and/ or other sources such as spices, aromatic plants, grains by-products, which containing bioactive compounds might be used as functional foods or for nutraceutical purposes. most common bioactive compounds are vitamin C, polyphenol, β- carotene and lycopene contents. In recent years, there has been a global trend toward the use of natural phytochemical as antioxidants and functional ingredients, which are present in natural resources such as vegetables, fruits, oilseeds and herbs.. Our future trend the Use of Natural antioxidants as a promising alternative to use of synthetic antioxidants and the Production of natural antioxidant on commercial scale to maximize the value addition of indigenous food waste as a good source of bioactive compounds such as antioxidants.

Keywords: bioactive compounds, antioxidants, by-product, indigenous foods, phenolic compounds

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Authors: B. Sellami, M. Belloufi

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Conjugate gradient methods are an important class of methods for unconstrained optimization, especially for large-scale problems. Recently, they have been much studied. In this paper, we propose a new two-parameter family of conjugate gradient methods for unconstrained optimization. The two-parameter family of methods not only includes the already existing three practical nonlinear conjugate gradient methods, but also has other family of conjugate gradient methods as subfamily. The two-parameter family of methods with the Wolfe line search is shown to ensure the descent property of each search direction. Some general convergence results are also established for the two-parameter family of methods. The numerical results show that this method is efficient for the given test problems. In addition, the methods related to this family are uniformly discussed.

Keywords: unconstrained optimization, conjugate gradient method, line search, global convergence

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Authors: Shital Suresh Borse, Vijayalaxmi Kadroli

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E-commerce industries nowadays implement the latest AI, ML Techniques to improve their own performance and prediction accuracy. This helps to gain a huge profit from the online market. Ant Colony Optimization, Genetic algorithm, Particle Swarm Optimization, Neural Network & GWO help many e-commerce industries for up-gradation of their predictive performance. These algorithms are providing optimum results in various applications, such as stock price prediction, prediction of drug-target interaction & user ratings of similar products in e-commerce sites, etc. In this study, customer reviews will play an important role in prediction analysis. People showing much interest in buying a lot of services& products suggested by other customers. This ultimately increases net profit. In this work, a convolution neural network (CNN) is proposed which further is useful to optimize the prediction accuracy of an e-commerce website. This method shows that CNN is used to optimize hyperparameters of GWO algorithm using an appropriate coding scheme. Accurate model results are verified by comparing them to PSO results whose hyperparameters have been optimized by CNN in Amazon's customer review dataset. Here, experimental outcome proves that this proposed system using the GWO algorithm achieves superior execution in terms of accuracy, precision, recovery, etc. in prediction analysis compared to the existing systems.

Keywords: prediction analysis, e-commerce, machine learning, grey wolf optimization, particle swarm optimization, CNN

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Authors: Ahcene Habbi, Yassine Boudouaoui

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This paper deals with the problem of automatic rule generation for fuzzy systems design. The proposed approach is based on hybrid artificial bee colony (ABC) optimization and weighted least squares (LS) method and aims to find the structure and parameters of fuzzy systems simultaneously. More precisely, two ABC based fuzzy modeling strategies are presented and compared. The first strategy uses global optimization to learn fuzzy models, the second one hybridizes ABC and weighted least squares estimate method. The performances of the proposed ABC and ABC-LS fuzzy modeling strategies are evaluated on complex modeling problems and compared to other advanced modeling methods.

Keywords: automatic design, learning, fuzzy rules, hybrid, swarm optimization

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Authors: Roya Ahmadi Ahangar, Hamid Madadyari

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The seeker optimization algorithm (SOA) is increasingly gaining popularity among the researchers society due to its effectiveness in solving some real-world optimization problems. This paper provides the load-frequency control method based on the SOA for removing oscillations in the power system. A three-zone power system includes a thermal zone, a hydraulic zone and a wind zone equipped with robust proportional-integral-differential (PID) controllers. The result of simulation indicates that load-frequency changes in the wind zone for the multi-zone system are damped in a short period of time. Meanwhile, in the oscillation period, the oscillations amplitude is not significant. The result of simulation emphasizes that the PID controller designed using the seeker optimization algorithm has a robust function and a better performance for oscillations damping compared to the traditional PID controller. The proposed controller’s performance has been compared to the performance of PID controller regulated with Particle Swarm Optimization (PSO) and. Genetic Algorithm (GA) and Artificial Bee Colony (ABC) algorithms in order to show the superior capability of the proposed SOA in regulating the PID controller. The simulation results emphasize the better performance of the optimized PID controller based on SOA compared to the PID controller optimized with PSO, GA and ABC algorithms.

Keywords: load-frequency control, multi zone, robust PID controller, wind generation

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Authors: Emrah Çimen, Mustafa Demirelli, Burcu Yilmaz Şahinbaşkan, Mahmure Üstün Özgür

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Natural colours are used on a large area such as textile, food and pharmaceutical industries by many researchers. When tannic acid is used together with metal salts for dyeing with natural dyes, antibacterial and fastness properties of textile materials are increased. In addition, the allegens are removed on wool fabrics. In this experimental work, some red rose petals were applied as a natural dye with three different dyeing methods and eight different mordant salts. The effect of tannic acid and different metal salts on dyeing of wool fabric was studied. Colour differences ΔECMC (2:1) and fastness properties of dyed fabrics were investigated and compared with each other. Finally, dark colours and adequate colour fastness results (4+) were obtained after dyeing of wool fabrics with FeSO4.7H2O, FeCl3.6H2O and CuCl2.2H2O in the presence of the tannic acid.

Keywords: natural dye, red rose petals, tannic acid, mordant salts, wool fabric

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Authors: Omer Oral, Y. Emre Yilmaz

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Topology optimization is an approach that optimizes material distribution within a given design space for a certain load and boundary conditions by providing performance goals. It uses various restrictions such as boundary conditions, set of loads, and constraints to maximize the performance of the system. It is different than size and shape optimization methods, but it reserves some features of both methods. In this study, interior structures of the parts were optimized by using SIMP (Solid Isotropic Material with Penalization) method. The volume of the part was preassigned parameter and minimum deflection was the objective function. The basic idea behind the theory was considered, and different methods were discussed. Rhinoceros 3D design tool was used with Grasshopper and TopOpt plugins to create and optimize parts. A Grasshopper algorithm was designed and tested for different beams, set of arbitrary located forces and support types such as pinned, fixed, etc. Finally, 2.5D shapes were obtained and verified by observing the changes in density function.

Keywords: Grasshopper, lattice structure, microstructures, Rhinoceros, solid isotropic material with penalization method, TopOpt, topology optimization

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Authors: Shahid-ul-Islam, Faqeer Mohammad

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The present study was conducted to investigate the effect of annatto, teak and flame of the forest natural dyes on color, fastness, and antimicrobial property of protein based textile substrate. The color strength (K/S) of wool samples at various concentrations of dyes were analysed using a Reflective Spectrophotometer. The antimicrobial activity of natural dyes before and after application on wool was tested against common human pathogens Escherichia coli, Staphylococcus aureus, and Candida albicans, by using micro-broth dilution method, disc diffusion assay and growth curve studies. The structural morphology of natural protein fibre (wool) was investigated by Scanning Electron Microscopy (SEM). Annatto and teak natural dyes proved very effective in inhibiting the microbial growth in solution phase and after application on wool and resulted in a broad beautiful spectrum of colors with exceptional fastness properties. The results encourage the search and exploitation of new plant species as source of dyes to replace toxic synthetic antimicrobial agents currently used in textile industry.

Keywords: annatto, antimicrobial agents, natural dyes, green textiles

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Authors: Balwinder Singh, Veerpaul Kaur Mann

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A composite material is formed by the combination of two or more phases or materials. Natural minerals-derived Basalt fiber is a kind of fiber being introduced in the polymer composite industry due to its good mechanical properties similar to synthetic fibers and low cost, environment friendly. Also, there is a rising trend towards the use of industrial wastes as fillers in polymer composites with the aim of improving the properties of the composites. The mechanical properties of the fiber-reinforced polymer composites are influenced by various factors like fiber length, fiber weight %, filler weight %, filler size, etc. Thus, a detailed study has been done on the characterization of short-chopped Basalt fiber-reinforced polymer matrix composites using fly ash as filler. Taguchi’s L9 orthogonal array has been used to develop the composites by considering fiber length (6, 9 and 12 mm), fiber weight % (25, 30 and 35 %) and filler weight % (0, 5 and 10%) as input parameters with their respective levels and a thorough analysis on the mechanical characteristics (tensile strength and impact strength) has been done using ANOVA analysis with the help of MINITAB14 software. The investigation revealed that fiber weight is the most significant parameter affecting tensile strength, followed by fiber length and fiber weight %, respectively, while impact characterization showed that fiber length is the most significant factor, followed by fly ash weight, respectively. Introduction of fly ash proved to be beneficial in both the characterization with enhanced values upto 5% fly ash weight. The present study on the natural fibres reinforced epoxy composites using fly ash as filler material to study the effect of input parameters on the tensile strength in order to maximize tensile strength of the composites. Fabrication of composites based on Taguchi L9 orthogonal array design of experiments by using three factors fibre type, fibre weight % and fly ash % with three levels of each factor. The Optimization of composition of natural fibre reinforces composites using ANOVA for obtaining maximum tensile strength on fabricated composites revealed that the natural fibres along with fly ash can be successfully used with epoxy resin to prepare polymer matrix composites with good mechanical properties. Paddy- Paddy fibre gives high elasticity to the fibre composite due to presence of approximately hexagonal structure of cellulose present in paddy fibre. Coir- Coir fibre gives less tensile strength than paddy fibre as Coir fibre is brittle in nature when it pulls breakage occurs showing less tensile strength. Banana- Banana fibre has the least tensile strength in comparison to the paddy & coir fibre due to less cellulose content. Higher fibre weight leads to reduction in tensile strength due to increased nuclei of air pockets. Increasing fly ash content reduces tensile strength due to nonbonding of fly ash particles with natural fibre. Fly ash is also not very strong as compared to the epoxy resin leading to reduction in tensile strength.

Keywords: tensile strength and epoxy resin. basalt Fiber, taguchi, polymer matrix, natural fiber

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Authors: Sri Wartini

Abstract:

Based on the sovereignty over natural resources principle, the Indonesian government has an authority to exploit the natural resources within a national jurisdiction of Indonesia. The forest is one of the natural resources which is very valuable for Indonesia. It becomes the source of raw material for many industrial activities, such as pharmaceutical industry, pulp industry, and household furniture industry. Hence, it contributes to the economic development of Indonesia. However, the exploitation of the forest may cause negative impacts, such as environmental pollution and environmental degradation. The implementation of the sovereignty over natural resources principle in Indonesia may jeopardize the forest and affect the sustainability of the forest if there is no appropriate policy of the government to exploit the forest in a sustainable manner. The exploitation of the forest in Indonesia, in some extent, has caused serious impact to environment and biodiversity. Hence, in order to sustain and to maintain the forest as the valuable resources to the future generation, the government of Indonesia has already adopted many programmes and action plans. The aim of the research is to undertake a critical examination of the issues relating to the the implementation of sovereignty over natural resources to the exploitation of the forest in Indonesia. It is a normative research and the methodology employed in this research is library research. While the approaches employed in the research are conceptual approach., statutory approach, and comparative approach. The research finds that the implementation of sovereignty over natural resources principle in the exploitation of the forest in Indonesia is limited by other principles of international environmental law, such as sustainable development principle, intergenerational principle and common concern principle which have been adopted in the government policy and various regulations regarding the exploitation of the forest in Indonesia.

Keywords: Environmental damage, negative impacts, pollution, the sovereignty over natural resources

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Authors: Shunichi Ohmori, Sirawadee Arunyanart, Kazuho Yoshimoto

Abstract:

We consider a periodic review inventory control problem of minimizing production cost, inventory cost, and lost-sales under demand uncertainty, in which product demands are not specified exactly and it is only known to belong to a given uncertainty set, yet the constraints must hold for possible values of the data from the uncertainty set. We propose a robust optimization formulation for obtaining lowest cost possible and guaranteeing the feasibility with respect to range of order quantity and inventory level under demand uncertainty. Our formulation is based on the adaptive robust counterpart, which suppose order quantity is affine function of past demands. We derive certainty equivalent problem via second-order cone programming, which gives 'not too pessimistic' worst-case.

Keywords: robust optimization, inventory control, supply chain managment, second-order programming

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Authors: Ticiane Rossi, Maurício C. Araújo, José O. Brito, Harold S. Freeman

Abstract:

Natural dyes are gaining interest due their expected low risk to human health and to the environment. In this study, the wash fastness of a natural coloring matter from the liquid waste produced in the steam treatment of eucalyptus wood in textile fabrics was investigated. Specifically, eucalyptus wood extract was used to dye cotton, nylon and wool in an exhaust dyeing process without the addition of the traditional mordanting agents and then submitted to wash fastness analysis. The resulting dyed fabrics were evaluated for color fastness. It was found that wash fastness of dyed fabrics was very good to cotton and excellent to nylon and wool.

Keywords: eucalyptus, natural dye, textile fibers, wash fastness

Procedia PDF Downloads 600