Search results for: cost-based structural optimization
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 7144

Search results for: cost-based structural optimization

5734 Optimization of Temperature for Crystal Violet Dye Adsorption Using Castor Leaf Powder by Response Surface Methodology

Authors: Vipan Kumar Sohpal

Abstract:

Temperature effect on the adsorption of crystal violet dye (CVD) was investigated using a castor leaf powder (CLP) that was prepared from the mature leaves of castor trees, through chemical reaction. The optimum values of pH (8), adsorbent dose (10g/L), initial dye concentration (10g/L), time (2hrs), and stirrer speed (120 rpm) were fixed to investigate the influence of temperature on adsorption capacity, percentage of removal of dye and free energy. A central composite design (CCD) was successfully employed for experimental design and analysis of the results. The combined effect of temperature, absorbance, and concentration on the dye adsorption was studied and optimized using response surface methodology. The optimum values of adsorption capacity, percentage of removal of dye and free energy were found to be 0.965(mg/g), 93.38 %, -8202.7(J/mol) at temperature 55.97 °C having desirability > 90% for removal of crystal violet dye respectively. The experimental values were in good agreement with predicted values.

Keywords: crystal violet dye, CVD, castor leaf powder, CLP, response surface methodology, temperature, optimization

Procedia PDF Downloads 114
5733 Optimal Scheduling of Trains in Complex National Scale Railway Networks

Authors: Sanat Ramesh, Tarun Dutt, Abhilasha Aswal, Anushka Chandrababu, G. N. Srinivasa Prasanna

Abstract:

Optimal Schedule Generation for a large national railway network operating thousands of passenger trains with tens of thousands of kilometers of track is a grand computational challenge in itself. We present heuristics based on a Mixed Integer Program (MIP) formulation for local optimization. These methods provide flexibility in scheduling new trains with varying speed and delays and improve utilization of infrastructure. We propose methods that provide a robust solution with hundreds of trains being scheduled over a portion of the railway network without significant increases in delay. We also provide techniques to validate the nominal schedules thus generated over global correlated variations in travel times thereby enabling us to detect conflicts arising due to delays. Our validation results which assume only the support of the arrival and departure time distributions takes an order of few minutes for a portion of the network and is computationally efficient to handle the entire network.

Keywords: mixed integer programming, optimization, railway network, train scheduling

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5732 Optimization of 3D Printing Parameters Using Machine Learning to Enhance Mechanical Properties in Fused Deposition Modeling (FDM) Technology

Authors: Darwin Junnior Sabino Diego, Brando Burgos Guerrero, Diego Arroyo Villanueva

Abstract:

Additive manufacturing, commonly known as 3D printing, has revolutionized modern manufacturing by enabling the agile creation of complex objects. However, challenges persist in the consistency and quality of printed parts, particularly in their mechanical properties. This study focuses on addressing these challenges through the optimization of printing parameters in FDM technology, using Machine Learning techniques. Our aim is to improve the mechanical properties of printed objects by optimizing parameters such as speed, temperature, and orientation. We implement a methodology that combines experimental data collection with Machine Learning algorithms to identify relationships between printing parameters and mechanical properties. The results demonstrate the potential of this methodology to enhance the quality and consistency of 3D printed products, with significant applications across various industrial fields. This research not only advances understanding of additive manufacturing but also opens new avenues for practical implementation in industrial settings.

Keywords: 3D printing, additive manufacturing, machine learning, mechanical properties

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5731 Multi-Objective Optimization (Pareto Sets) and Multi-Response Optimization (Desirability Function) of Microencapsulation of Emamectin

Authors: Victoria Molina, Wendy Franco, Sergio Benavides, José M. Troncoso, Ricardo Luna, Jose R. PéRez-Correa

Abstract:

Emamectin Benzoate (EB) is a crystal antiparasitic that belongs to the avermectin family. It is one of the most common treatments used in Chile to control Caligus rogercresseyi in Atlantic salmon. However, the sea lice acquired resistance to EB when it is exposed at sublethal EB doses. The low solubility rate of EB and its degradation at the acidic pH in the fish digestive tract are the causes of the slow absorption of EB in the intestine. To protect EB from degradation and enhance its absorption, specific microencapsulation technologies must be developed. Amorphous Solid Dispersion techniques such as Spray Drying (SD) and Ionic Gelation (IG) seem adequate for this purpose. Recently, Soluplus® (SOL) has been used to increase the solubility rate of several drugs with similar characteristics than EB. In addition, alginate (ALG) is a widely used polymer in IG for biomedical applications. Regardless of the encapsulation technique, the quality of the obtained microparticles is evaluated with the following responses, yield (Y%), encapsulation efficiency (EE%) and loading capacity (LC%). In addition, it is important to know the percentage of EB released from the microparticles in gastric (GD%) and intestinal (ID%) digestions. In this work, we microencapsulated EB with SOL (EB-SD) and with ALG (EB-IG) using SD and IG, respectively. Quality microencapsulation responses and in vitro gastric and intestinal digestions at pH 3.35 and 7.8, respectively, were obtained. A central composite design was used to find the optimum microencapsulation variables (amount of EB, amount of polymer and feed flow). In each formulation, the behavior of these variables was predicted with statistical models. Then, the response surface methodology was used to find the best combination of the factors that allowed a lower EB release in gastric conditions, while permitting a major release at intestinal digestion. Two approaches were used to determine this. The desirability approach (DA) and multi-objective optimization (MOO) with multi-criteria decision making (MCDM). Both microencapsulation techniques allowed to maintain the integrity of EB in acid pH, given the small amount of EB released in gastric medium, while EB-IG microparticles showed greater EB release at intestinal digestion. For EB-SD, optimal conditions obtained with MOO plus MCDM yielded a good compromise among the microencapsulation responses. In addition, using these conditions, it is possible to reduce microparticles costs due to the reduction of 60% of BE regard the optimal BE proposed by (DA). For EB-GI, the optimization techniques used (DA and MOO) yielded solutions with different advantages and limitations. Applying DA costs can be reduced 21%, while Y, GD and ID showed 9.5%, 84.8% and 2.6% lower values than the best condition. In turn, MOO yielded better microencapsulation responses, but at a higher cost. Overall, EB-SD with operating conditions selected by MOO seems the best option, since a good compromise between costs and encapsulation responses was obtained.

Keywords: microencapsulation, multiple decision-making criteria, multi-objective optimization, Soluplus®

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5730 Resistivity Tomography Optimization Based on Parallel Electrode Linear Back Projection Algorithm

Authors: Yiwei Huang, Chunyu Zhao, Jingjing Ding

Abstract:

Electrical Resistivity Tomography has been widely used in the medicine and the geology, such as the imaging of the lung impedance and the analysis of the soil impedance, etc. Linear Back Projection is the core algorithm of Electrical Resistivity Tomography, but the traditional Linear Back Projection can not make full use of the information of the electric field. In this paper, an imaging method of Parallel Electrode Linear Back Projection for Electrical Resistivity Tomography is proposed, which generates the electric field distribution that is not linearly related to the traditional Linear Back Projection, captures the new information and improves the imaging accuracy without increasing the number of electrodes by changing the connection mode of the electrodes. The simulation results show that the accuracy of the image obtained by the inverse operation obtained by the Parallel Electrode Linear Back Projection can be improved by about 20%.

Keywords: electrical resistivity tomography, finite element simulation, image optimization, parallel electrode linear back projection

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5729 Active-Material Variation Analysis of a Lithium-Ion Battery

Authors: Muhammad Husnat Khalid, Stephan Bihn, Dirk Uwe Sauer, Nisai Fuengwarodsakul

Abstract:

To combat the effects of climate change, lithium-ion batteries are getting a lot of attention for energy storage. However, due to its diverse range of applications extending from small electronics equipment to energy storage systems, its output requirements, as well as limitations, vary significantly. Many efforts are underway to increase the power and energy output of the cells without any significant compromise on their size and weight. In this paper, different active materials are explored for an existing cell Kokam that initially has graphite as anode and NCO as cathode material. The Pareto front optimization tool is then utilized to pick a cell that gives the optimum results in terms of energy, power, or both. The parameter variation of the cells is done in the MATLAB application ISEA Cell and Pack Database (ICPD) created by the Institute of Power Electronics and Electrical Drives (ISEA) RWTH Aachen, University that creates the physical-chemical model of the existing cells.

Keywords: battery storage system, lithium-ion battery, active material variation, cell design optimization

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5728 Monitoring a Membrane Structure Using Non-Destructive Testing

Authors: Gokhan Kilic, Pelin Celik

Abstract:

Structural health monitoring (SHM) is widely used in evaluating the state and health of membrane structures. In the past, in order to collect data and send it to a data collection unit on membrane structures, wire sensors had to be put as part of the SHM process. However, this study recommends using wireless sensors instead of traditional wire ones to construct an economical, useful, and easy-to-install membrane structure health monitoring system. Every wireless sensor uses a software translation program that is connected to the monitoring server. Operational neural networks (ONNs) have recently been developed to solve the shortcomings of convolutional neural networks (CNNs), such as the network's resemblance to the linear neuron model. The results of using ONNs for monitoring to evaluate the structural health of a membrane are presented in this work.

Keywords: wireless sensor network, non-destructive testing, operational neural networks, membrane structures, dynamic monitoring

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5727 Full-Potential Investigation of the Electronic and Magnetic Properties of CdCoTe and CdMnTe Diluted Magnetic Semiconductors

Authors: A.Zitouni, S.Bentata, B.Bouadjemi, T.Lantri, W. Benstaali, Z.Aziz, S.Cherid

Abstract:

We investigate the structural, electronic and magnetic properties of the diluted magnetic semiconductors (DMSs) CdCoTe and CdMnTe in the zinc blende phase with 25% of Co and Mn. The calculations are performed by the recent ab initio full potential augmented plane waves (FP_L/APW) method within the spin polarized density-functional theory (DFT) and the generalized gradient approximation GGA. Structural properties are determined from the total energy calculations and we found that these compounds are stable in the ferromagnetic phase. We discuss the electronic structures, total and partial densities of states and total magnetic moments. The calculated densities of states presented in this study identify the half-metallic of CdCoTe and CdMnTe.

Keywords: electronic structure, half-metallic, magnetic moment, total and partial densities of states

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5726 Hope as a Predictor for Complicated Grief and Anxiety: A Bayesian Structural Equational Modeling Study

Authors: Bo Yan, Amy Y. M. Chow

Abstract:

Bereavement is recognized as a universal challenging experience. It is important to gather research evidence on protective factors in bereavement. Hope is considered as one of the protective factors in previous coping studies. The present study aims to add knowledge by investigating hope at the first month after death to predict psychological symptoms altogether including complicated grief (CG), anxiety, and depressive symptoms at the seventh month. The data were collected via one-on-one interview survey in a longitudinal project with Hong Kong hospice users (sample size 105). Most participants were at their middle age (49-year-old on average), female (72%), with no religious affiliation (58%). Bayesian Structural Equation Modeling (BSEM) analysis was conducted on the longitudinal dataset. The BSEM findings show that hope at the first month of bereavement negatively predicts both CG and anxiety symptoms at the seventh month but not for depressive symptoms. Age and gender are controlled in the model. The overall model fit is good. The current study findings suggest assessing hope at the first month of bereavement. Hope at the first month after the loss is identified as an excellent predictor for complicated grief and anxiety symptoms at the seventh month. The result from this sample is clear, so it encourages cross-cultural research on replicated modeling and development of further clinical application. Particularly, practical consideration for early intervention to increase the level of hope has the potential to reduce the psychological symptoms and thus to improve the bereaved persons’ wellbeing in the long run.

Keywords: anxiety, complicated grief, depressive symptoms, hope, structural equational modeling

Procedia PDF Downloads 186
5725 Load Management Using Multiple Sequential Load Shaping Techniques

Authors: Amira M. Attia, Karim H. Youssef, Nabil H. Abbasi

Abstract:

Demand Side Management (DSM) is an essential characteristic of current and future smart grid systems. As one of DSM functions, load management aims to control customers’ total electric consumption and utility’s load factor by using various load shaping techniques. However, applying load shaping techniques such as load shifting, peak clipping, or strategic conservation individually does not provide the desired level of improvement for load factor increment and/or customer’s bill reduction. In this paper, two load shaping techniques will be simulated as constrained optimization problems. The purpose is to reflect the application of combined load shifting and strategic conservation model together at the same time, and the application of combined load shifting and peak clipping model as well. The problem will be formulated and solved by using disciplined convex programming (CVX) based MATLAB® R2013b. Simulation results will be evaluated and compared for studying the most impactful multi-techniques model in improving load curve.

Keywords: convex programing, demand side management, load shaping, multiple, building energy optimization

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5724 Optimal Allocation of PHEV Parking Lots to Minimize Dstribution System Losses

Authors: Mohsen Mazidi, Ali Abbaspour, Mahmud Fotuhi-Firuzabad, Mohamamd Rastegar

Abstract:

To tackle the air pollution issues, Plug-in Hybrid Electric Vehicles (PHEVs) are proposed as an appropriate solution. Charging a large amount of PHEV batteries, if not controlled, would have negative impacts on the distribution system. The control process of charging of these vehicles can be centralized in parking lots that may provide a chance for better coordination than the individual charging in houses. In this paper, an optimization-based approach is proposed to determine the optimum PHEV parking capacities in candidate nodes of the distribution system. In so doing, a profile for charging and discharging of PHEVs is developed in order to flatten the network load profile. Then, this profile is used in solving an optimization problem to minimize the distribution system losses. The outputs of the proposed method are the proper place for PHEV parking lots and optimum capacity for each parking. The application of the proposed method on the IEEE-34 node test feeder verifies the effectiveness of the method.

Keywords: loss, plug-in hybrid electric vehicle (PHEV), PHEV parking lot, V2G

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5723 Optimization of Ultrasound Assisted Extraction of Polysaccharides from Plant Waste Materials: Selected Model Material is Hazelnut Skin

Authors: T. Yılmaz, Ş. Tavman

Abstract:

In this study, optimization of ultrasound assisted extraction (UAE) of hemicellulose based polysaccharides from plant waste material has been studied. Selected material is hazelnut skin. Extraction variables for the operation are extraction time, amplitude and application temperature. Optimum conditions have been evaluated depending on responses such as amount of wet crude polysaccharide, total carbohydrate content and dried sample. Pretreated hazelnut skin powders were used for the experiments. 10 grams of samples were suspended in 100 ml water in a jacketed vessel with additional magnetic stirring. Mixture was sonicated by immersing ultrasonic probe processor. After the extraction procedures, ethanol soluble and insoluble sides were separated for further examinations. The obtained experimental data were analyzed by analysis of variance (ANOVA). Second order polynomial models were developed using multiple regression analysis. The individual and interactive effects of applied variables were evaluated by Box Behnken Design. The models developed from the experimental design were predictive and good fit with the experimental data with high correlation coefficient value (R2 more than 0.95). Extracted polysaccharides from hazelnut skin are assumed to be pectic polysaccharides according to the literature survey of Fourier Transform Spectrometry (FTIR) analysis results. No more change can be observed between spectrums of different sonication times. Application of UAE at optimized condition has an important effect on extraction of hemicellulose from plant material by satisfying partial hydrolysis to break the bounds with other components in plant cell wall material. This effect can be summarized by varied intensity of microjets and microstreaming at varied sonication conditions.

Keywords: hazelnut skin, optimization, polysaccharide, ultrasound assisted extraction

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5722 Easymodel: Web-based Bioinformatics Software for Protein Modeling Based on Modeller

Authors: Alireza Dantism

Abstract:

Presently, describing the function of a protein sequence is one of the most common problems in biology. Usually, this problem can be facilitated by studying the three-dimensional structure of proteins. In the absence of a protein structure, comparative modeling often provides a useful three-dimensional model of the protein that is dependent on at least one known protein structure. Comparative modeling predicts the three-dimensional structure of a given protein sequence (target) mainly based on its alignment with one or more proteins of known structure (templates). Comparative modeling consists of four main steps 1. Similarity between the target sequence and at least one known template structure 2. Alignment of target sequence and template(s) 3. Build a model based on alignment with the selected template(s). 4. Prediction of model errors 5. Optimization of the built model There are many computer programs and web servers that automate the comparative modeling process. One of the most important advantages of these servers is that it makes comparative modeling available to both experts and non-experts, and they can easily do their own modeling without the need for programming knowledge, but some other experts prefer using programming knowledge and do their modeling manually because by doing this they can maximize the accuracy of their modeling. In this study, a web-based tool has been designed to predict the tertiary structure of proteins using PHP and Python programming languages. This tool is called EasyModel. EasyModel can receive, according to the user's inputs, the desired unknown sequence (which we know as the target) in this study, the protein sequence file (template), etc., which also has a percentage of similarity with the primary sequence, and its third structure Predict the unknown sequence and present the results in the form of graphs and constructed protein files.

Keywords: structural bioinformatics, protein tertiary structure prediction, modeling, comparative modeling, modeller

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5721 A Deterministic Approach for Solving the Hull and White Interest Rate Model with Jump Process

Authors: Hong-Ming Chen

Abstract:

This work considers the resolution of the Hull and White interest rate model with the jump process. A deterministic process is adopted to model the random behavior of interest rate variation as deterministic perturbations, which is depending on the time t. The Brownian motion and jumps uncertainty are denoted as the integral functions piecewise constant function w(t) and point function θ(t). It shows that the interest rate function and the yield function of the Hull and White interest rate model with jump process can be obtained by solving a nonlinear semi-infinite programming problem. A relaxed cutting plane algorithm is then proposed for solving the resulting optimization problem. The method is calibrated for the U.S. treasury securities at 3-month data and is used to analyze several effects on interest rate prices, including interest rate variability, and the negative correlation between stock returns and interest rates. The numerical results illustrate that our approach essentially generates the yield functions with minimal fitting errors and small oscillation.

Keywords: optimization, interest rate model, jump process, deterministic

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5720 A Practical Survey on Zero-Shot Prompt Design for In-Context Learning

Authors: Yinheng Li

Abstract:

The remarkable advancements in large language models (LLMs) have brought about significant improvements in natural language processing tasks. This paper presents a comprehensive review of in-context learning techniques, focusing on different types of prompts, including discrete, continuous, few-shot, and zero-shot, and their impact on LLM performance. We explore various approaches to prompt design, such as manual design, optimization algorithms, and evaluation methods, to optimize LLM performance across diverse tasks. Our review covers key research studies in prompt engineering, discussing their methodologies and contributions to the field. We also delve into the challenges faced in evaluating prompt performance, given the absence of a single ”best” prompt and the importance of considering multiple metrics. In conclusion, the paper highlights the critical role of prompt design in harnessing the full potential of LLMs and provides insights into the combination of manual design, optimization techniques, and rigorous evaluation for more effective and efficient use of LLMs in various Natural Language Processing (NLP) tasks.

Keywords: in-context learning, prompt engineering, zero-shot learning, large language models

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5719 Estimation of Fourier Coefficients of Flux Density for Surface Mounted Permanent Magnet (SMPM) Generators by Direct Search Optimization

Authors: Ramakrishna Rao Mamidi

Abstract:

It is essential for Surface Mounted Permanent Magnet (SMPM) generators to determine the performance prediction and analyze the magnet’s air gap flux density wave shape. The flux density wave shape is neither a pure sine wave or square wave nor a combination. This is due to the variation of air gap reluctance between the stator and permanent magnets. The stator slot openings and the number of slots make the wave shape highly complicated. To reduce the complexity of analysis, approximations are made to the wave shape using Fourier analysis. In contrast to the traditional integration method, the Fourier coefficients, an and bn, are obtained by direct search method optimization. The wave shape with optimized coefficients gives a wave shape close to the desired wave shape. Harmonics amplitudes are worked out and compared with initial values. It can be concluded that the direct search method can be used for estimating Fourier coefficients for irregular wave shapes.

Keywords: direct search, flux plot, fourier analysis, permanent magnets

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5718 Optimization of Ultrasonic Assisted Extraction of Antioxidants and Phenolic Compounds from Coleus Using Response Surface Methodology

Authors: Reihaneh Ahmadzadeh Ghavidel

Abstract:

Free radicals such as reactive oxygen species (ROS) have detrimental effects on human health through several mechanisms. On the other hand, antioxidant molecules reduce free radical generation in biologic systems. Synthetic antioxidants, which are used in food industry, have also negative impact on human health. Therefore recognition of natural antioxidants such as anthocyanins can solve these problems simultaneously. Coleus (Solenostemon scutellarioides) with red leaves is a rich source of anthocyanins compounds. In this study we evaluated the effect of time (10, 20 and 30 min) and temperature (40, 50 and 60° C) on optimization of anthocyanin extraction using surface response method. In addition, the study was aimed to determine maximum extraction for anthocyanin from coleus plant using ultrasound method. The results indicated that the optimum conditions for extraction were 39.84 min at 69.25° C. At this point, total compounds were achieved 3.7451 mg 100 ml⁻¹. Furthermore, under optimum conditions, anthocyanin concentration, extraction efficiency, ferric reducing ability, total phenolic compounds and EC50 were registered 3.221931, 6.692765, 223.062, 3355.605 and 2.614045, respectively.

Keywords: anthocyanin, antioxidant, coleus, extraction, sonication

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5717 Study of Complex (CO) 3Ti (PHND) and CpV (PHND) (PHND = Phénanthridine)

Authors: Akila Tayeb-Benmachiche, Saber-Mustapha Zendaoui, Salah-Eddine Bouaoud, Bachir Zouchoune

Abstract:

The variation of the metal coordination site in π-coordinated polycyclic aromatic hydrocarbons (PAH) corresponds to the haptotropic rearrangement or haptotropic migration in which the metal fragment MLn is considered as the moveable moiety that is shifted between two rings of polycyclic or heteropolycyclic ligands. These structural characteristics and dynamical properties give to this category of transition metal complexes a considerable interest. We have investigated the coordination and the haptotropic shifts of (CO)3Ti and CpV moieties over the phenanthridine aromatic system and according to the metal atom nature. The optimization of (CO)3Ti(PHND) and CpV(PHND), using the Amsterdam Density Functional (ADF) program, without a symmetrical restriction of geometry gives an η6 coordination mode of the C6 and C5N rings, which in turn give rise to a six low-lying deficient 16-MVE of each (CO)3Ti(PHND) and CpV(PHND) structure (three singlet and three triplet state structures for Ti complexes and three triplet and three quintet state structures for V complexes). Thus, the η6–η6 haptotropic migration of the metal fragment MLn from the terminal C6 ring to the central C5N ring has been achieved by a loss of energy. However, its η6–η6 haptotropic migration from central C5N ring to the terminal C6 rings has been accomplished by a gain of energy. These results show the capability of the phenanthridine ligand to adapt itself to the electronic demand of the metal in agreement with the nature of the metal–ligand bonding and demonstrate that this theoretical study can also be applied to large fused π-systems.

Keywords: electronic structure, bonding analysis, density functional theory, coordination chemistry haptotropic migration

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5716 Optimal Protection Coordination in Distribution Systems with Distributed Generations

Authors: Abdorreza Rabiee, Shahla Mohammad Hoseini Mirzaei

Abstract:

The advantages of distributed generations (DGs) based on renewable energy sources (RESs) leads to high penetration level of DGs in distribution network. With incorporation of DGs in distribution systems, the system reliability and security, as well as voltage profile, is improved. However, the protection of such systems is still challenging. In this paper, at first, the related papers are reviewed and then a practical scheme is proposed for coordination of OCRs in distribution system with DGs. The coordination problem is formulated as a nonlinear programming (NLP) optimization problem with the object function of minimizing total operating time of OCRs. The proposed method is studied based on a simple test system. The optimization problem is solved by General Algebraic Modeling System (GAMS) to calculate the optimal time dial setting (TDS) and also pickup current setting of OCRs. The results show the effectiveness of the proposed method and its applicability.

Keywords: distributed generation, DG, distribution network, over current relay, OCR, protection coordination, pickup current, time dial setting, TDS

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5715 An IM-COH Algorithm Neural Network Optimization with Cuckoo Search Algorithm for Time Series Samples

Authors: Wullapa Wongsinlatam

Abstract:

Back propagation algorithm (BP) is a widely used technique in artificial neural network and has been used as a tool for solving the time series problems, such as decreasing training time, maximizing the ability to fall into local minima, and optimizing sensitivity of the initial weights and bias. This paper proposes an improvement of a BP technique which is called IM-COH algorithm (IM-COH). By combining IM-COH algorithm with cuckoo search algorithm (CS), the result is cuckoo search improved control output hidden layer algorithm (CS-IM-COH). This new algorithm has a better ability in optimizing sensitivity of the initial weights and bias than the original BP algorithm. In this research, the algorithm of CS-IM-COH is compared with the original BP, the IM-COH, and the original BP with CS (CS-BP). Furthermore, the selected benchmarks, four time series samples, are shown in this research for illustration. The research shows that the CS-IM-COH algorithm give the best forecasting results compared with the selected samples.

Keywords: artificial neural networks, back propagation algorithm, time series, local minima problem, metaheuristic optimization

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5714 Elaboration and Investigation of the New Ecologically Clean Friction Composite Materials on the Basis of Nanoporous Raw Materials

Authors: Lia Gventsadze, Elguja Kutelia, David Gventsadze

Abstract:

The purpose of the article is to show the possibility for the development of a new generation, eco-friendly (asbestos free) nano-porous friction materials on the basis of Georgian raw materials, along with the determination of technological parameters for their production, as well as the optimization of tribological properties and the investigation of structural aspects of wear peculiarities of elaborated materials using the scanning electron microscopy (SEM) and Auger electron spectroscopy (AES) methods. The study investigated the tribological properties of the polymer friction materials on the basis of the phenol-formaldehyde resin using the porous diatomite filler modified by silane with the aim to improve the thermal stability, while the composition was modified by iron phosphate, technical carbon and basalt fibre. As a result of testing the stable values of friction factor (0.3-0,45) were reached, both in dry and wet friction conditions, the friction working parameters (friction factor and wear stability) remained stable up to 500 OC temperatures, the wear stability of gray cast-iron disk increased 3-4 times, the soundless operation of materials without squeaking were achieved. Herewith it was proved that small amount of ingredients (5-6) are enough to compose the nano-porous friction materials. The study explains the mechanism of the action of nano-porous composition base brake lining materials and its tribological efficiency on the basis of the triple phase model of the tribo-pair.

Keywords: brake lining, friction coefficient, wear, nanoporous composite, phenolic resin

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5713 Effect of Oxygen Ion Irradiation on the Structural, Spectral and Optical Properties of L-Arginine Acetate Single Crystals

Authors: N. Renuka, R. Ramesh Babu, N. Vijayan

Abstract:

Ion beams play a significant role in the process of tuning the properties of materials. Based on the radiation behavior, the engineering materials are categorized into two different types. The first one comprises organic solids which are sensitive to the energy deposited in their electronic system and the second one comprises metals which are insensitive to the energy deposited in their electronic system. However, exposure to swift heavy ions alters this general behavior. Depending on the mass, kinetic energy and nuclear charge, an ion can produce modifications within a thin surface layer or it can penetrate deeply to produce long and narrow distorted area along its path. When a high energetic ion beam impinges on a material, it causes two different types of changes in the material due to the columbic interaction between the target atom and the energetic ion beam: (i) inelastic collisions of the energetic ion with the atomic electrons of the material; and (ii) elastic scattering from the nuclei of the atoms of the material, which is extremely responsible for relocating the atoms of matter from their lattice position. The exposure of the heavy ions renders the material return to equilibrium state during which the material undergoes surface and bulk modifications which depends on the mass of the projectile ion, physical properties of the target material, its energy, and beam dimension. It is well established that electronic stopping power plays a major role in the defect creation mechanism provided it exceeds a threshold which strongly depends on the nature of the target material. There are reports available on heavy ion irradiation especially on crystalline materials to tune their physical and chemical properties. L-Arginine Acetate [LAA] is a potential semi-organic nonlinear optical crystal and its optical, mechanical and thermal properties have already been reported The main objective of the present work is to enhance or tune the structural and optical properties of LAA single crystals by heavy ion irradiation. In the present study, a potential nonlinear optical single crystal, L-arginine acetate (LAA) was grown by slow evaporation solution growth technique. The grown LAA single crystal was irradiated with oxygen ions at the dose rate of 600 krad and 1M rad in order to tune the structural and optical properties. The structural properties of pristine and oxygen ions irradiated LAA single crystals were studied using Powder X- ray diffraction and Fourier Transform Infrared spectral studies which reveal the structural changes that are generated due to irradiation. Optical behavior of pristine and oxygen ions irradiated crystals is studied by UV-Vis-NIR and photoluminescence analyses. From this investigation we can concluded that oxygen ions irradiation modifies the structural and optical properties of LAA single crystals.

Keywords: heavy ion irradiation, NLO single crystal, photoluminescence, X-ray diffractometer

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5712 The Mediatory Role of Innovation in the Link between Social and Financial Performance

Authors: Bita Mashayekhi, Amin Jahangard, Milad Samavat, Saeid Homayoun

Abstract:

In the modern competitive business environment, one cannot overstate the importance of corporate social responsibility. The controversial link between the social and financial performance of firms has become a topic of interest for scholars. Hence, this study examines the social and financial performance link by taking into account the mediating role of innovation performance. We conducted the Covariance-based Structural Equation Modeling (CB-SEM) method on an international sample of firms provided by the ASSET4 database. In this research, to explore the black box of the social and financial performance relationship, we first examined the effect of social performance separately on financial performance and innovation; then, we measured the mediation role of innovation in the social and financial performance link. While our results indicate the positive effect of social performance on financial performance and innovation, we cannot document the positive mediating role of innovation. This possibly relates to the long-term nature of benefits from investments in innovation.

Keywords: ESG, financial performance, innovation, social performance, structural equation modeling

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5711 Optimization of Stevia Concentration in Rasgulla (Sweet Syrup Cheese Ball) Based on Quality

Authors: Gurveer Kaur, T. K. Goswami

Abstract:

Rasgulla (a sweet syrup cheese ball), a sweet, spongy dessert represents traditional sweet dish of an Indian subcontinent prepared by chhana. 100 g of Rasgulla contains 186 calories, and so it is a driving force behind obesity and diabetes. To reduce Rasgulla’s energy value sucrose mainly should be minimized, so instead of sucrose, stevia (zero calories natural sweetener) is used to prepare Rasgulla. In this study three samples were prepared with sucrose to stevia ratio taking 100:0 (as control sample), (i) 50:50 (T1); (ii) 25:75 (T2), and (iii) 0:100 (T3) from 4% fat milk. It was found that as the sucrose concentration decreases the percentage of fat increase in the Rasgulla slightly. Sample T2 showed < 0.1% (±0.06) sucrose content. But there was no significant difference on protein and ash content of the samples. Whitening index was highest (78.0 ± 0.13) for T2 and lowest (65.7 ± 0.21) for the control sample since less sucrose in syrup reduces the browning of the sample (T2). Energy value per 100 g was calculated to be 50, 72, 98, and 184 calories for T3, T2, T1 and control samples, respectively. According to optimization study, the preferred (high quality) order of samples was as follows: T1 > T1 > control > T3. Low sugar content Rasgulla with acceptable quality can be prepared with 25:75 ratio of sucrose to stevia.

Keywords: composition, rasgulla, sensory, stevia

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5710 Theoretical and Experimental Study of Iron Oxide Thin Film

Authors: Fahima Djefaflia, M. Loutfi Benkhedir

Abstract:

The aim of this work was to development and characterisation of iron oxide thin films by spray pyrolysis technique. Influences of deposition parameters pile temperature on structural and optical properties have been studied Thin films are analysed by various techniques of materials. The structural characterization of films by analysis of spectra of X-ray diffraction showed that the films prepared at T=350,400,450 are crystalline and amorphous at T=300C. For particular condition, two phases hematiteFe2O3 and magnetite Fe3O4 have been observed.The UV-Visible spectrophotometer of this films confirms that it is possible to obtain films with a transmittance of about 15-30% in the visible range. In addition, this analysis allowed us to determine the optical gap and disorder of films. We conclude that the increase in temperature is accompanied by a reduction in the optical gap with increasing in disorder. An ab initio calculation for this phase shows that the results are in good agreement with the experimental results.

Keywords: spray pyrolysis technique, iron oxide, ab initio calculation, optical properties

Procedia PDF Downloads 542
5709 Key Frame Based Video Summarization via Dependency Optimization

Authors: Janya Sainui

Abstract:

As a rapid growth of digital videos and data communications, video summarization that provides a shorter version of the video for fast video browsing and retrieval is necessary. Key frame extraction is one of the mechanisms to generate video summary. In general, the extracted key frames should both represent the entire video content and contain minimum redundancy. However, most of the existing approaches heuristically select key frames; hence, the selected key frames may not be the most different frames and/or not cover the entire content of a video. In this paper, we propose a method of video summarization which provides the reasonable objective functions for selecting key frames. In particular, we apply a statistical dependency measure called quadratic mutual informaion as our objective functions for maximizing the coverage of the entire video content as well as minimizing the redundancy among selected key frames. The proposed key frame extraction algorithm finds key frames as an optimization problem. Through experiments, we demonstrate the success of the proposed video summarization approach that produces video summary with better coverage of the entire video content while less redundancy among key frames comparing to the state-of-the-art approaches.

Keywords: video summarization, key frame extraction, dependency measure, quadratic mutual information

Procedia PDF Downloads 254
5708 Unveiling the Domino Effect: Barriers and Strategies in the Adoption of Telecommuting as a Post-Pandemic Workspace

Authors: Divnesh Lingam, Devi Rengamani Seenivasagam, Prashant Chand, Caleb Yee, John Chief, Rajeshkannan Ananthanarayanan

Abstract:

Telecommuting Post-Pandemic: Barriers, Solutions, and Strategies. Amidst the COVID-19 outbreak in 2020, remote work emerged as a vital business continuity measure. This study investigates telecommuting’s modern work model, exploring its benefits and obstacles. Utilizing Interpretive Structural Modelling uncovers barriers hindering telecommuting adoption. A validated set of thirteen barriers is examined through departmental surveys, revealing interrelationships. The resulting model highlights interactions and dependencies, forming a foundational framework. By addressing dominant barriers, a domino effect on subservient barriers is demonstrated. This research fosters further exploration, proposing management strategies for successful telecommuting adoption and reshaping the traditional workspace.

Keywords: barriers, interpretive structural modelling, post-pandemic, telecommuting

Procedia PDF Downloads 74
5707 Kinematic Optimization of Energy Extraction Performances for Flapping Airfoil by Using Radial Basis Function Method and Genetic Algorithm

Authors: M. Maatar, M. Mekadem, M. Medale, B. Hadjed, B. Imine

Abstract:

In this paper, numerical simulations have been carried out to study the performances of a flapping wing used as an energy collector. Metamodeling and genetic algorithms are used to detect the optimal configuration, improving power coefficient and/or efficiency. Radial basis functions and genetic algorithms have been applied to solve this problem. Three optimization factors are controlled, namely dimensionless heave amplitude h₀, pitch amplitude θ₀ and flapping frequency f. ANSYS FLUENT software has been used to solve the principal equations at a Reynolds number of 1100, while the heave and pitch motion of a NACA0015 airfoil has been realized using a developed function (UDF). The results reveal an average power coefficient and efficiency of 0.78 and 0.338 with an inexpensive low-fidelity model and a total relative error of 4.1% versus the simulation. The performances of the simulated optimum RBF-NSGA-II have been improved by 1.2% compared with the validated model.

Keywords: numerical simulation, flapping wing, energy extraction, power coefficient, efficiency, RBF, NSGA-II

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5706 Modern Well Logs Technology to Improve Geological Model for Libyan Deep Sand Stone Reservoir

Authors: Tarek S. Duzan, Fisal Ben Ammer, Mohamed Sula

Abstract:

In some places within Sirt Basin-Libya, it has been noticed that seismic data below pre-upper cretaceous unconformity (PUK) is hopeless to resolve the large-scale structural features and is unable to fully determine reservoir delineation. Seismic artifacts (multiples) are observed in the reservoir zone (Nubian Formation) below PUK, which complicate the process of seismic interpretation. The nature of the unconformity and the structures below are still ambiguous and not fully understood which generates a significant gap in characterizing the geometry of the reservoir, the uncertainty accompanied with lack of reliable seismic data creates difficulties in building a robust geological model. High resolution dipmeter is highly useful in steeply dipping zones. This paper uses FMl and OBMl borehole images (dipmeter) to analyze the structures below the PUK unconformity from two wells drilled recently in the North Gialo field (a mature reservoir). In addition, borehole images introduce new evidences that the PUK unconformity is angular and the bedding planes within the Nubian formation (below PUK) are significantly titled. Structural dips extracted from high resolution borehole images are used to construct a new geological model by the utilization of latest software technology. Therefore, it is important to use the advance well logs technology such as FMI-HD for any future drilling and up-date the existing model in order to minimize the structural uncertainty.

Keywords: FMI (formation micro imager), OBMI (oil base mud imager), UBI (ultra sonic borehole imager), nub sandstone reservoir in North gialo

Procedia PDF Downloads 304
5705 Production Line Layout Planning Based on Complexity Measurement

Authors: Guoliang Fan, Aiping Li, Nan Xie, Liyun Xu, Xuemei Liu

Abstract:

Mass customization production increases the difficulty of the production line layout planning. The material distribution process for variety of parts is very complex, which greatly increases the cost of material handling and logistics. In response to this problem, this paper presents an approach of production line layout planning based on complexity measurement. Firstly, by analyzing the influencing factors of equipment layout, the complexity model of production line is established by using information entropy theory. Then, the cost of the part logistics is derived considering different variety of parts. Furthermore, the function of optimization including two objectives of the lowest cost, and the least configuration complexity is built. Finally, the validity of the function is verified in a case study. The results show that the proposed approach may find the layout scheme with the lowest logistics cost and the least complexity. Optimized production line layout planning can effectively improve production efficiency and equipment utilization with lowest cost and complexity.

Keywords: production line, layout planning, complexity measurement, optimization, mass customization

Procedia PDF Downloads 375