Search results for: nonsmooth optimization
1523 A High-Level Co-Evolutionary Hybrid Algorithm for the Multi-Objective Job Shop Scheduling Problem
Authors: Aydin Teymourifar, Gurkan Ozturk
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In this paper, a hybrid distributed algorithm has been suggested for the multi-objective job shop scheduling problem. Many new approaches are used at design steps of the distributed algorithm. Co-evolutionary structure of the algorithm and competition between different communicated hybrid algorithms, which are executed simultaneously, causes to efficient search. Using several machines for distributing the algorithms, at the iteration and solution levels, increases computational speed. The proposed algorithm is able to find the Pareto solutions of the big problems in shorter time than other algorithm in the literature. Apache Spark and Hadoop platforms have been used for the distribution of the algorithm. The suggested algorithm and implementations have been compared with results of the successful algorithms in the literature. Results prove the efficiency and high speed of the algorithm.Keywords: distributed algorithms, Apache Spark, Hadoop, job shop scheduling, multi-objective optimization
Procedia PDF Downloads 3561522 Effective Scheduling of Hybrid Reconfigurable Microgrids Considering High Penetration of Renewable Sources
Authors: Abdollah Kavousi Fard
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This paper addresses the optimal scheduling of hybrid reconfigurable microgrids considering hybrid electric vehicle charging demands. A stochastic framework based on unscented transform to model the high uncertainties of renewable energy sources including wind turbine and photovoltaic panels, as well as the hybrid electric vehicles’ charging demand. In order to get to the optimal scheduling, the network reconfiguration is employed as an effective tool for changing the power supply path and avoiding possible congestions. The simulation results are analyzed and discussed in three different scenarios including coordinated, uncoordinated and smart charging demand of hybrid electric vehicles. A typical grid-connected microgrid is employed to show the satisfying performance of the proposed method.Keywords: microgrid, renewable energy sources, reconfiguration, optimization
Procedia PDF Downloads 2621521 Numerical Modeling for Water Engineering and Obstacle Theory
Authors: Mounir Adal, Baalal Azeddine, Afifi Moulay Larbi
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Numerical analysis is a branch of mathematics devoted to the development of iterative matrix calculation techniques. We are searching for operations optimization as objective to calculate and solve systems of equations of order n with time and energy saving for computers that are conducted to calculate and analyze big data by solving matrix equations. Furthermore, this scientific discipline is producing results with a margin of error of approximation called rates. Thus, the results obtained from the numerical analysis techniques that are held on computer software such as MATLAB or Simulink offers a preliminary diagnosis of the situation of the environment or space targets. By this we can offer technical procedures needed for engineering or scientific studies exploitable by engineers for water.Keywords: numerical analysis methods, obstacles solving, engineering, simulation, numerical modeling, iteration, computer, MATLAB, water, underground, velocity
Procedia PDF Downloads 4541520 Motion Estimator Architecture with Optimized Number of Processing Elements for High Efficiency Video Coding
Authors: Seongsoo Lee
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Motion estimation occupies the heaviest computation in HEVC (high efficiency video coding). Many fast algorithms such as TZS (test zone search) have been proposed to reduce the computation. Still the huge computation of the motion estimation is a critical issue in the implementation of HEVC video codec. In this paper, motion estimator architecture with optimized number of PEs (processing element) is presented by exploiting early termination. It also reduces hardware size by exploiting parallel processing. The presented motion estimator architecture has 8 PEs, and it can efficiently perform TZS with very high utilization of PEs.Keywords: motion estimation, test zone search, high efficiency video coding, processing element, optimization
Procedia PDF Downloads 3531519 A Comparative Study on a Tilt-Integral-Derivative Controller with Proportional-Integral-Derivative Controller for a Pacemaker
Authors: Aysan Esgandanian, Sabalan Daneshvar
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The study is done to determine the comparison between proportional-integral-derivative controller (PID controller) and tilt-integral-derivative (TID controller) for cardiac pacemaker systems, which can automatically control the heart rate to accurately track a desired preset profile. The controller offers good adaption of heart to the physiological needs of the patient. The parameters of the both controllers are tuned by particle swarm optimization (PSO) algorithm which uses the integral of time square error as a fitness function to be minimized. Simulation results are performed on the developed cardiovascular system of humans and results demonstrate that the TID controller produces superior control performance than PID controllers. In this paper, all simulations were performed in Matlab.Keywords: integral of time square error, pacemaker systems, proportional-integral-derivative controller, PSO algorithm, tilt-integral-derivative controller
Procedia PDF Downloads 4551518 Logistics Hub Location and Scheduling Model for Urban Last-Mile Deliveries
Authors: Anastasios Charisis, Evangelos Kaisar, Steven Spana, Lili Du
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Logistics play a vital role in the prosperity of today’s cities, but current urban logistics practices are proving problematic, causing negative effects such as traffic congestion and environmental impacts. This paper proposes an alternative urban logistics system, leasing hubs inside cities for designated time intervals, and using handcarts for last-mile deliveries. A mathematical model for selecting the locations of hubs and allocating customers, while also scheduling the optimal times during the day for leasing hubs is developed. The proposed model is compared to current delivery methods requiring door-to-door truck deliveries. It is shown that truck traveled distances decrease by more than 60%. In addition, analysis shows that in certain conditions the approach can be economically competitive and successfully applied to address real problems.Keywords: hub location, last-mile, logistics, optimization
Procedia PDF Downloads 1811517 Field Saturation Flow Measurement Using Dynamic Passenger Car Unit under Mixed Traffic Condition
Authors: Ramesh Chandra Majhi
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Saturation flow is a very important input variable for the design of signalized intersections. Saturation flow measurement is well established for homogeneous traffic. However, saturation flow measurement and modeling is a challenging task in heterogeneous characterized by multiple vehicle types and non-lane based movement. Present study focuses on proposing a field procedure for Saturation flow measurement and the effect of typical mixed traffic behavior at the signal as far as non-lane based traffic movement is concerned. Data collected during peak and off-peak hour from five intersections with varying approach width is used for validating the saturation flow model. The insights from the study can be used for modeling saturation flow and delay at signalized intersection in heterogeneous traffic conditions.Keywords: optimization, passenger car unit, saturation flow, signalized intersection
Procedia PDF Downloads 3191516 Model Based Development of a Processing Map for Friction Stir Welding of AA7075
Authors: Elizabeth Hoyos, Hernán Alvarez, Diana Lopez, Yesid Montoya
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The main goal of this research relates to the modeling of FSW from a different or unusual perspective coming from mechanical engineering, particularly looking for a way to establish process windows by assessing soundness of the joints as a priority and with the added advantage of lower computational time. This paper presents the use of a previously developed model applied to specific aspects of soundness evaluation of AA7075 FSW welds. EMSO software (Environment for Modeling, Simulation, and Optimization) was used for simulation and an adapted CNC machine was used for actual welding. This model based approach showed good agreement with the experimental data, from which it is possible to set a window of operation for commercial aluminum alloy AA7075, all with low computational costs and employing simple quality indicators that can be used by non-specialized users in process modeling.Keywords: aluminum AA7075, friction stir welding, phenomenological based semiphysical model, processing map
Procedia PDF Downloads 2531515 Optimization of Waqf Land through Sukuk Al-Intifa’ to Build MSMEs in Indonesia
Authors: Khadijah Hasim, Achmad Fauzan Firdaus, Choirunnisa
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Waqf land which previously was idle assets can be built on top of a building that is a means for people to conduct business. Nadzir (waqf managers) lease of waqf lands it manages, the agreed rental fee, which is payable in the form of the building, not in cash. After standing building, the developer will lease to interested companies. Given the magnitude of the beginning funds needed, The company later issuing sukuk al-intifa on the trading floor. With this sukuk issuance, the company has sufficient capital to begin operations and pay obligations of the rental fee to the developer each year. Building that had stood trade area will be established (Micro, Small, Middle Entreprises) MSMEs. It is expected that through the sukuk al-intifa, can help to make waqf land previously unproductive due to lack of capital to be very beneficial and help awaken the people of Indonesian MSMEsKeywords: Sukuk Al-Intifa, MSMEs, waqf land, underlying asset
Procedia PDF Downloads 4621514 Studies on Optimization of Batch Biosorption of Cr (VI) and Cu (II) from Wastewater Using Bacillus subtilis
Authors: Narasimhulu Korrapati
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The objective of this present study is to optimize the process parameters for batch biosorption of Cr(VI) and Cu(II) ions by Bacillus subtilis using Response Surface Methodology (RSM). Batch biosorption studies were conducted under optimum pH, temperature, biomass concentration and contact time for the removal of Cr(VI) and Cu(II) ions using Bacillus subtilis. From the studies it is noticed that the maximum biosorption of Cr(VI) and Cu(II) was by Bacillus subtilis at optimum conditions of contact time of 30 minutes, pH of 4.0, biomass concentration of 2.0 mg/mL, the temperature of 32°C in batch biosorption studies. Predicted percent biosorption of the selected heavy metal ions by the design expert software is in agreement with experimental results of percent biosorption. The percent biosorption of Cr(VI) and Cu(II) in batch studies is 80% and 78.4%, respectively.Keywords: heavy metal ions, response surface methodology, biosorption, wastewater
Procedia PDF Downloads 2631513 Optimization of the Energy Management for a Solar System of an Agricultural Greenhouse
Authors: Nora Arbaoui, Rachid Tadili, Ilham Ihoume
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To improve the climatic conditions and increase production in the greenhouse during the winter season under the Mediterranean climate, this thesis project proposes a design of an integrated and autonomous solar system for heating, cooling, and conservation of production in an agricultural greenhouse. To study the effectiveness of this system, experiments are conducted in two similar agricultural greenhouses oriented north-south. The first greenhouse is equipped with an active solar system integrated into the double glazing of the greenhouse’s roof, while the second greenhouse has no system, it serves as a controlled greenhouse for comparing thermal and agronomic performance The solar system allowed for an average increase in the indoor temperature of the experimental greenhouse of 6°C compared to the outdoor environment and 4°C compared to the control greenhouse. This improvement in temperature has a favorable effect on the plants' climate and subsequently positively affects their development, quality, and production.Keywords: solar system, agricultural greenhouse, heating, cooling, storage, drying
Procedia PDF Downloads 911512 Modelling the Indonesian Goverment Securities Yield Curve Using Nelson-Siegel-Svensson and Support Vector Regression
Authors: Jamilatuzzahro, Rezzy Eko Caraka
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The yield curve is the plot of the yield to maturity of zero-coupon bonds against maturity. In practice, the yield curve is not observed but must be extracted from observed bond prices for a set of (usually) incomplete maturities. There exist many methodologies and theory to analyze of yield curve. We use two methods (the Nelson-Siegel Method, the Svensson Method, and the SVR method) in order to construct and compare our zero-coupon yield curves. The objectives of this research were: (i) to study the adequacy of NSS model and SVR to Indonesian government bonds data, (ii) to choose the best optimization or estimation method for NSS model and SVR. To obtain that objective, this research was done by the following steps: data preparation, cleaning or filtering data, modeling, and model evaluation.Keywords: support vector regression, Nelson-Siegel-Svensson, yield curve, Indonesian government
Procedia PDF Downloads 2341511 A Heuristic Approach for the General Flowshop Scheduling Problem to Minimize the Makespan
Authors: Mohsen Ziaee
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Almost all existing researches on the flowshop scheduling problems focus on the permutation schedules and there is insufficient study dedicated to the general flowshop scheduling problems in the literature, since the modeling and solving of the general flowshop scheduling problems are more difficult than the permutation ones, especially for the large-size problem instances. This paper considers the general flowshop scheduling problem with the objective function of the makespan (F//Cmax). We first find the optimal solution of the problem by solving a mixed integer linear programming model. An efficient heuristic method is then presented to solve the problem. An ant colony optimization algorithm is also proposed for the problem. In order to evaluate the performance of the methods, computational experiments are designed and performed. Numerical results show that the heuristic algorithm can result in reasonable solutions with low computational effort and even achieve optimal solutions in some cases.Keywords: scheduling, general flow shop scheduling problem, makespan, heuristic
Procedia PDF Downloads 2001510 Discrete Breeding Swarm for Cost Minimization of Parallel Job Shop Scheduling Problem
Authors: Tarek Aboueldahab, Hanan Farag
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Parallel Job Shop Scheduling Problem (JSP) is a multi-objective and multi constrains NP- optimization problem. Traditional Artificial Intelligence techniques have been widely used; however, they could be trapped into the local minimum without reaching the optimum solution, so we propose a hybrid Artificial Intelligence model (AI) with Discrete Breeding Swarm (DBS) added to traditional Artificial Intelligence to avoid this trapping. This model is applied in the cost minimization of the Car Sequencing and Operator Allocation (CSOA) problem. The practical experiment shows that our model outperforms other techniques in cost minimization.Keywords: parallel job shop scheduling problem, artificial intelligence, discrete breeding swarm, car sequencing and operator allocation, cost minimization
Procedia PDF Downloads 1791509 Biogas Separation, Alcohol Amine Solutions
Authors: Jingxiao Liang, David Rooneyman
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Biogas, which is a valuable renewable energy source, can be produced by anaerobic fermentation of agricultural waste, manure, municipal waste, plant material, sewage, green waste, or food waste. It is composed of methane (CH4) and carbon dioxide (CO2) but also contains significant quantities of undesirable compounds such as hydrogen sulfide (H2S), ammonia (NH3), and siloxanes. Since typical raw biogas contains 25–45% CO2, The requirements for biogas quality depend on its further application. Before biogas is being used more efficiently, CO2 should be removed. One of the existing options for biogas separation technologies is based on chemical absorbents, in particular, mono-, di- and tri-alcohol amine solutions. Such amine solutions have been applied as highly efficient CO2 capturing agents. The benchmark in this experiment is N-methyldiethanolamine (MDEA) with piperazine (PZ) as an activator, from CO2 absorption Isotherm curve, optimization conditions are collected, such as activator percentage, temperature etc. This experiment makes new alcohol amines, which could have the same CO2 absorbing ability as activated MDEA, using glycidol as one of reactant, the result is quite satisfying.Keywords: biogas, CO2, MDEA, separation
Procedia PDF Downloads 6161508 Additive Manufacturing of Overhangs: From Temporary Supports to Self-Support
Authors: Paulo Mendonca, Nzar Faiq Naqeshbandi
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The objective of this study is to propose an interactive design environment that outlines the underlying computational framework to reach self-supporting overhangs. The research demonstrates the digital printability of overhangs taking into consideration factors related to the geometry design, the material used, the applied support, and the printing set-up of slicing and the extruder inclination. Parametric design tools can contribute to the design phase, form-finding, and stability optimization of self-supporting structures while printing in order to hold the components in place until they are sufficiently advanced to support themselves. The challenge is to ensure the stability of the printed parts in the critical inclinations during the whole fabrication process. Facilitating the identification of parameterization will allow to predict and optimize the process. Later, in the light of the previous findings, some guidelines of simulations and physical tests are given to be conducted for estimating the structural and functional performance.Keywords: additive manufacturing, overhangs, self-support overhangs, printability, parametric tools
Procedia PDF Downloads 1141507 An Efficient Algorithm for Global Alignment of Protein-Protein Interaction Networks
Authors: Duc Dong Do, Ngoc Ha Tran, Thanh Hai Dang, Cao Cuong Dang, Xuan Huan Hoang
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Global aligning two protein-protein interaction networks is an essentially important task in bioinformatics/computational biology field of study. It is a challenging and widely studied research topic in recent years. Accurately aligned networks allow us to identify functional modules of proteins and/ororthologous proteins from which unknown functions of a protein can be inferred. We here introduce a novel efficient heuristic global network alignment algorithm called FASTAn, including two phases: the first to construct an initial alignment and the second to improve such alignment by exerting a local optimization repeated procedure. The experimental results demonstrated that FASTAn outperformed the state-of-the-art global network alignment algorithm namely SPINAL in terms of both commonly used objective scores and the run-time.Keywords: FASTAn, Heuristic algorithm, biological network alignment, protein-protein interaction networks
Procedia PDF Downloads 5941506 Scheduling Tasks in Embedded Systems Based on NoC Architecture
Authors: D. Dorota
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This paper presents a method to generate and schedule task in the architecture of embedded systems based on the simulated annealing. This method takes into account the attribute of divisibility of tasks. A proposal represents the process in the form of trees. Despite the fact that the architecture of Network-on-Chip (NoC) is an interesting alternative to a bus architecture based on multi-processors systems, it requires a lot of work that ensures the optimization of communication. This paper proposes an effective approach to generate dedicated NoC topology solving communication problems. Network NoC is generated taking into account the energy consumption and resource issues. Ultimately generated is minimal, dedicated NoC topology. The proposed solution is assumed to be a simple router design and the minimum number of lines.Keywords: Network-on-Chip, NoC-based embedded systems, scheduling task in embedded systems, simulated annealing
Procedia PDF Downloads 3651505 Axial Flux Permanent Magnet Motor Design and Optimization by Using Artificial Neural Networks
Authors: Tugce Talay, Kadir Erkan
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In this study, the necessary steps for the design of axial flow permanent magnet motors are shown. The design and analysis of the engine were carried out based on ANSYS Maxwell program. The design parameters of the ANSYS Maxwell program and the artificial neural network system were established in MATLAB and the most efficient design parameters were found with the trained neural network. The results of the Maxwell program and the results of the artificial neural networks are compared and optimal working design parameters are found. The most efficient design parameters were submitted to the ANSYS Maxwell 3D design and the cogging torque was examined and design studies were carried out to reduce the cogging torque.Keywords: AFPM, ANSYS Maxwell, cogging torque, design optimisation, efficiency, NNTOOL
Procedia PDF Downloads 2081504 Modeling the Compound Interest Dynamics Using Fractional Differential Equations
Authors: Muath Awadalla, Maen Awadallah
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Banking sector covers different activities including lending money to customers. However, it is commonly known that customers pay money they have borrowed including an added amount called interest. Compound interest rate is an approach used in determining the interest to be paid. The instant compounded amount to be paid by a debtor is obtained through a differential equation whose main parameters are the rate and the time. The rate used by banks in a country is often defined by the government of the said country. In Switzerland, for instance, a negative rate was once applied. In this work, a new approach of modeling the compound interest is proposed using Hadamard fractional derivative. As a result, it appears that depending on the fraction value used in derivative the amount to be paid by a debtor might either be higher or lesser than the amount determined using the classical approach.Keywords: compound interest, fractional differential equation, hadamard fractional derivative, optimization
Procedia PDF Downloads 1191503 Dynamics Behavior of DFIG Wind Energy Conversion System Incase Dip Voltage
Authors: N. Zerzouri, N. Benalia, N. Bensiali
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During recent years wind turbine technology has undergone rapid developments. Growth in size and the optimization of wind turbines has enabled wind energy to become increasingly competitive with conventional energy sources. As a result today’s wind turbines participate actively in the power production of several countries around the world. These developments raise a number of challenges to be dealt with now and in the future. The penetration of wind energy in the grid raises questions about the compatibility of the wind turbine power production with the grid. In particular, the contribution to grid stability, power quality and behavior during fault situations plays therefore as important a role as the reliability. In the present work, we addressed two fault situations that have shown their influence on the generator and the behavior of the wind over the defects which are briefly discussed based on simulation results.Keywords: doubly fed induction generator (DFIG), wind energy, grid fault, electrical engineering
Procedia PDF Downloads 4631502 Effect of Blade Layout on Unidirectional Rotation of a Vertical-Axis Rotor in Waves
Authors: Yingchen Yang
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Ocean waves are a rich renewable energy source that is nearly untapped to date, even though many wave energy conversion (WEC) technologies are currently under development. The present work discusses a vertical-axis WEC rotor for power generation. The rotor was specially designed to allow easy rearrangement of the same blades to achieve different rotor configurations and result in different wave-rotor interaction behaviors. These rotor configurations were tested in a wave tank under various wave conditions. The testing results indicate that all the rotor configurations perform unidirectional rotation about the vertical axis in waves, but the response characteristics are somewhat different. The rotor's unidirectional rotation about its vertical axis is essential in wave energy harvesting since it makes the rotor respond well in a wide range of the wave frequency and in any wave propagation directions. Result comparison among different configurations leads to a preferred rotor design for further hydrodynamic optimization.Keywords: unidirectional rotation, vertical axis rotor, wave energy conversion, wave-rotor interaction
Procedia PDF Downloads 1671501 High Strength Steel Thin-Walled Cold-Formed Profiles Manufactured for Automated Rack Supported Warehouses
Authors: A. Natali, F. V. Lippi, F. Morelli, W. Salvatore, J. H. M. De Paula Filho, P. Pol
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Automated Rack Supported Warehouses (ARSWs) are storage buildings whose load-bearing structure is made of the same steel racks where goods are stocked. These racks are made of cold formed elements, and the main supporting structure is repeated several times along the length of the building, resulting in a huge quantity of steel. The possibility of using high strength steel to manufacture the traditional cold-formed profiles used for ARSWs is numerically investigated, with the aim of reducing the necessary steel quantity but guaranteeing optimal structural performance levels.Keywords: steel racks, automated rack supported warehouse, thin-walled cold-formed elements, high strength steel, structural optimization
Procedia PDF Downloads 1461500 Impact of Population Size on Symmetric Travelling Salesman Problem Efficiency
Authors: Wafa' Alsharafat, Suhila Farhan Abu-Owida
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Genetic algorithm (GA) is a powerful evolutionary searching technique that is used successfully to solve and optimize problems in different research areas. Genetic Algorithm (GA) considered as one of optimization methods used to solve Travel salesman Problem (TSP). The feasibility of GA in finding a TSP solution is dependent on GA operators; encoding method, population size, termination criteria, in general. In specific, crossover and its probability play a significant role in finding possible solutions for Symmetric TSP (STSP). In addition, the crossover should be determined and enhanced in term reaching optimal or at least near optimal. In this paper, we spot the light on using a modified crossover method called modified sequential constructive crossover and its impact on reaching optimal solution. To justify the relevance of a parameter value in solving the TSP, a set comparative analysis conducted on different crossover methods values.Keywords: genetic algorithm, crossover, mutation, TSP
Procedia PDF Downloads 2121499 Improved Artificial Bee Colony Algorithm for Non-Convex Economic Power Dispatch Problem
Authors: Badr M. Alshammari, T. Guesmi
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This study presents a modified version of the artificial bee colony (ABC) algorithm by including a local search technique for solving the non-convex economic power dispatch problem. The local search step is incorporated at the end of each iteration. Total system losses, valve-point loading effects and prohibited operating zones have been incorporated in the problem formulation. Thus, the problem becomes highly nonlinear and with discontinuous objective function. The proposed technique is validated using an IEEE benchmark system with ten thermal units. Simulation results demonstrate that the proposed optimization algorithm has better convergence characteristics in comparison with the original ABC algorithm.Keywords: economic power dispatch, artificial bee colony, valve-point loading effects, prohibited operating zones
Procedia PDF Downloads 2491498 Dynamic Analysis of Offshore 2-HUS/U Parallel Platform
Authors: Xie Kefeng, Zhang He
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For the stability and control demand of offshore small floating platform, a 2-HUS/U parallel mechanism was presented as offshore platform. Inverse kinematics was obtained by institutional constraint equation, and the dynamic model of offshore 2-HUS/U parallel platform was derived based on rigid body’s Lagrangian method. The equivalent moment of inertia, damping and driving force/torque variation of offshore 2-HUS/U parallel platform were analyzed. A numerical example shows that, for parallel platform of given motion, system’s equivalent inertia changes 1.25 times maximally. During the movement of platform, they change dramatically with the system configuration and have coupling characteristics. The maximum equivalent drive torque is 800 N. At the same time, the curve of platform’s driving force/torque is smooth and has good sine features. The control system needs to be adjusted according to kinetic equation during stability and control and it provides a basis for the optimization of control system.Keywords: 2-HUS/U platform, dynamics, Lagrange, parallel platform
Procedia PDF Downloads 3371497 Formulation and Evaluation of Dispersible Tablet of Furosemide for Pediatric Use
Authors: O. Benaziz, A. Dorbane, S. Djeraba
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The objective of this work is to formulate a dry dispersible form of furosemide in the context of pediatric dose adjustment. To achieve this, we have produced a set of formulas that will be tested in process and after compression. The formula with the best results will be improved to optimize the final shape of the product. Furosemide is the most widely used pediatric diuretic because of its low toxicity. The manufacturing process was chosen taking into account all the data relating to the active ingredient and the excipients used and complying with the specifications and requirements of dispersible tablets. The process used to prepare these tablets was wet granulation. Different excipients were used: lactose, maize starch, magnesium stearate and two superdisintegrants. The mode of incorporation of super-disintegrant changes with each formula. The use of super-disintegrant in the formula allowed optimization of the disintegration time. Prepared tablets were evaluated for weight, content uniformity, hardness, disintegration time, friability and in vitro dissolution test.Keywords: formulation, dispersible tablets, wet granulation, superdisintegrants, disintegration
Procedia PDF Downloads 3371496 Molecular Dynamics Simulation of Realistic Biochar Models with Controlled Microporosity
Authors: Audrey Ngambia, Ondrej Masek, Valentina Erastova
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Biochar is an amorphous carbon-rich material generated from the pyrolysis of biomass with multifarious properties and functionality. Biochar has shown proven applications in the treatment of flue gas and organic and inorganic pollutants in soil and water/wastewater as a result of its multiple surface functional groups and porous structures. These properties have also shown potential in energy storage and carbon capture. The availability of diverse sources of biomass to produce biochar has increased interest in it as a sustainable and environmentally friendly material. The properties and porous structures of biochar vary depending on the type of biomass and high heat treatment temperature (HHT). Biochars produced at HHT between 400°C – 800°C generally have lower H/C and O/C ratios, higher porosities, larger pore sizes and higher surface areas with temperature. While all is known experimentally, there is little knowledge on the porous role structure and functional groups play on processes occurring at the atomistic scale, which are extremely important for the optimization of biochar for application, especially in the adsorption of gases. Atomistic simulations methods have shown the potential to generate such amorphous materials; however, most of the models available are composed of only carbon atoms or graphitic sheets, which are very dense or with simple slit pores, all of which ignore the important role of heteroatoms such as O, N, S and pore morphologies. Hence, developing realistic models that integrate these parameters are important to understand their role in governing adsorption mechanisms that will aid in guiding the design and optimization of biochar materials for target applications. In this work, molecular dynamics simulations in the isobaric ensemble are used to generate realistic biochar models taking into account experimentally determined H/C, O/C, N/C, aromaticity, micropore size range, micropore volumes and true densities of biochars. A pore generation approach was developed using virtual atoms, which is a Lennard-Jones sphere of varying van der Waals radius and softness. Its interaction via a soft-core potential with the biochar matrix allows the creation of pores with rough surfaces while varying the van der Waals radius parameters gives control to the pore-size distribution. We focused on microporosity, creating average pore sizes of 0.5 - 2 nm in diameter and pore volumes in the range of 0.05 – 1 cm3/g, which corresponds to experimental gas adsorption micropore sizes of amorphous porous biochars. Realistic biochar models with surface functionalities, micropore size distribution and pore morphologies were developed, and they could aid in the study of adsorption processes in confined micropores.Keywords: biochar, heteroatoms, micropore size, molecular dynamics simulations, surface functional groups, virtual atoms
Procedia PDF Downloads 621495 Adaptive Few-Shot Deep Metric Learning
Authors: Wentian Shi, Daming Shi, Maysam Orouskhani, Feng Tian
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Whereas currently the most prevalent deep learning methods require a large amount of data for training, few-shot learning tries to learn a model from limited data without extensive retraining. In this paper, we present a loss function based on triplet loss for solving few-shot problem using metric based learning. Instead of setting the margin distance in triplet loss as a constant number empirically, we propose an adaptive margin distance strategy to obtain the appropriate margin distance automatically. We implement the strategy in the deep siamese network for deep metric embedding, by utilizing an optimization approach by penalizing the worst case and rewarding the best. Our experiments on image recognition and co-segmentation model demonstrate that using our proposed triplet loss with adaptive margin distance can significantly improve the performance.Keywords: few-shot learning, triplet network, adaptive margin, deep learning
Procedia PDF Downloads 1591494 Machine Learning Approach for Lateralization of Temporal Lobe Epilepsy
Authors: Samira-Sadat JamaliDinan, Haidar Almohri, Mohammad-Reza Nazem-Zadeh
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Lateralization of temporal lobe epilepsy (TLE) is very important for positive surgical outcomes. We propose a machine learning framework to ultimately identify the epileptogenic hemisphere for temporal lobe epilepsy (TLE) cases using magnetoencephalography (MEG) coherence source imaging (CSI) and diffusion tensor imaging (DTI). Unlike most studies that use classification algorithms, we propose an effective clustering approach to distinguish between normal and TLE cases. We apply the famous Minkowski weighted K-Means (MWK-Means) technique as the clustering framework. To overcome the problem of poor initialization of K-Means, we use particle swarm optimization (PSO) to effectively select the initial centroids of clusters prior to applying MWK-Means. We demonstrate that compared to K-means and MWK-means independently, this approach is able to improve the result of a benchmark data set.Keywords: temporal lobe epilepsy, machine learning, clustering, magnetoencephalography
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