Search results for: multi objectives multidisciplinary optimization

Authors: Geetanjali Panda, Suvrakanti Chakraborty

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In this paper, Newton-like descent methods are proposed for unconstrained optimization problems, which use q-derivatives of the gradient of an objective function. First, a local scheme is developed with alternative sufficient optimality condition, and then the method is extended to a global scheme. Moreover, a variant of practical Newton scheme is also developed introducing a real sequence. Global convergence of these schemes is proved under some mild conditions. Numerical experiments and graphical illustrations are provided. Finally, the performance profiles on a test set show that the proposed schemes are competitive to the existing first-order schemes for optimization problems.

Keywords: Descent algorithm, line search method, q calculus, Quasi Newton method

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Authors: Sofiane Bououden, Ilyes Boulkaibet

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In terms of security of the information signal, the meta-heuristic Penguins Search Optimization Algorithm (PeSOA) is applied to synchronize chaotic encryption communications in the case of sensitive dependence on initial conditions in chaotic generator oscillator. The objective of this paper is the use of the PeSOA algorithm to exploring search space with random and iterative processes for synchronization of symmetric keys in both transmission and reception. Simulation results show the effectiveness of the PeSOA algorithm in generating symmetric keys of the encryption process and synchronizing.

Keywords: meta-heuristic, PeSOA, chaotic systems, encryption, synchronization optimization

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Authors: Kyung-Jin You, Kiwon Rhee, Marc H. Schieber, Nitish V. Thakor, Hyun-Chool Shin

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It remains unknown whether M1 neurons encode multi-finger movements independently or as a certain neural network of single finger movements although multi-finger movements are physically a combination of single finger movements. We present an evidence of correlation between single and multi-finger movements and also attempt a challenging task of semi-blind decoding of neural data with minimum training of the neural decoder. Data were collected from 115 task-related neurons in M1 of a trained rhesus monkey performing flexion and extension of each finger and the wrist (12 single and 6 two-finger-movements). By exploiting correlation of temporal firing pattern between movements, we found that correlation coefficient for physically related movements pairs is greater than others; neurons tuned to single finger movements increased their firing rate when multi-finger commands were instructed. According to this knowledge, neural semi-blind decoding is done by choosing the greatest and the second greatest likelihood for canonical candidates. We achieved a decoding accuracy about 60% for multiple finger movement without corresponding training data set. this results suggest that only with the neural activities on single finger movements can be exploited to control dexterous multi-fingered neuroprosthetics.

Keywords: finger movement, neural activity, blind decoding, M1

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Authors: Phawin Sangsuvan, Chutimet Srinilta

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This Paper presents the applications of Particle Swarm Optimization (PSO) Method for Thai optical character recognition (OCR). OCR consists of the pre-processing, character recognition and post-processing. Before enter into recognition process. The Character must be “Prepped” by pre-processing process. The PSO is an optimization method that belongs to the swarm intelligence family based on the imitation of social behavior patterns of animals. Route of each particle is determined by an individual data among neighborhood particles. The interaction of the particles with neighbors is the advantage of Particle Swarm to determine the best solution. So PSO is interested by a lot of researchers in many difficult problems including character recognition. As the previous this research used a Projection Histogram to extract printed digits features and defined the simple Fitness Function for PSO. The results reveal that PSO gives 67.73% for testing dataset. So in the future there can be explored enhancement the better performance of PSO with improve the Fitness Function.

Keywords: character recognition, histogram projection, particle swarm optimization, pattern recognition techniques

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Authors: Justie Su-Tzu Juan, Ming-Jheng Li, Ching-Fen Lee, Ruei-Yu Wu

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A secret image sharing scheme is a way to protect images. The main idea is dispersing the secret image into numerous shadow images. A secret image sharing scheme can withstand the impersonal attack and achieve the highly practical property of multiuse  is more practical. Therefore, this paper proposes a verifiable and detectable secret image-sharing scheme called VDGMSISS to solve the impersonal attack and to achieve some properties such as encrypting multi-secret images at one time and multi-use. Moreover, our scheme can also be used for any genera access structure.

Keywords: multi-secret image sharing scheme, verifiable, de-tectable, general access structure

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Authors: B. Sellami, Y. Laskri, 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, a new family of conjugate gradient method is proposed for unconstrained optimization. This method includes the already existing two practical nonlinear conjugate gradient methods, which produces a descent search direction at every iteration and converges globally provided that the line search satisfies the Wolfe conditions. The numerical experiments are done to test the efficiency of the new method, which implies the new method is promising. In addition the methods related to this family are uniformly discussed.

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

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Authors: Mohammed Affanuddin H. Siddique, Jayesh S. Shukla, Chetan B. Meshram

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The neural networks are one of the power tools of machine learning. After the invention of perceptron in early 1980's, the neural networks and its application have grown rapidly. Neural networks are a technique originally developed for pattern investigation. The structure of a neural network consists of neurons connected through synapse. Here, we have investigated the different algorithms and cost function reduction techniques for optimization of vertical axis wind turbine (VAWT) rotor blades. The aerodynamic force coefficients corresponding to the airfoils are stored in a database along with the airfoil coordinates. A forward propagation neural network is created with the input as aerodynamic coefficients and output as the airfoil co-ordinates. In the proposed algorithm, the hidden layer is incorporated into cost function having linear and non-linear error terms. In this article, it is observed that the ANNs (Artificial Neural Network) can be used for the VAWT’s optimization.

Keywords: VAWT, ANN, optimization, inverse design

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Authors: Nur Azzammudin Rahmat, Ismail Musirin, Ahmad Farid Abidin

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Economic load dispatch is performed by the utilities in order to determine the best generation level at the most feasible operating cost. In order to guarantee satisfying energy delivery to the consumer, a precise calculation of generation level is required. In order to achieve accurate and practical solution, several considerations such as prohibited operating zones, valve-point effect and ramp-rate limit need to be taken into account. However, these considerations cause the optimization to become complex and difficult to solve. This research focuses on the valve-point effect that causes ripple in the fuel-cost curve. This paper also proposes Differential Evolution Immunized Ant Colony Optimization (DEIANT) in solving economic load dispatch problem with valve-point effect. Comparative studies involving DEIANT, EP and ACO are conducted on IEEE 30-Bus RTS for performance assessments. Results indicate that DEIANT is superior to the other compared methods in terms of calculating lower operating cost and power loss.

Keywords: ant colony optimization (ACO), differential evolution (DE), differential evolution immunized ant colony optimization (DEIANT), economic load dispatch (ELD)

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Authors: Saria Abed, Tahar Khir, Ammar Ben Brahim

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A thermo-exergy optimization of a gas turbine cycle with two different regenerator designs is established. A comparison was made between the performance of the two regenerators and their roles in improving the cycle efficiencies. The effect of operational parameters (the pressure ratio of the compressor, the ambient temperature, excess of air, geometric parameters of the regenerators, etc.) on thermal efficiencies, the exergy efficiencies, and irreversibilities were studied using thermal balances and quantitative exegetic equilibrium for each component and for the whole system. The results are given graphically by using the EES software, and an appropriate discussion and conclusion was made.

Keywords: exergy efficiency, gas turbine, heat transfer, irreversibility, optimization, regenerator, thermal efficiency

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Authors: Antonio Marco Miotti, Antonella Ruffatto, Giampaola Basso, Antonio Madia, Giulia Zavatta, Emanuela Salvatico, Emanuela Zilli

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A National Action Plan to fight antimicrobial resistance was launched in Italy in 2017. In order to reduce inappropriate exposure to antibiotics and infections from multi-drug resistant bacteria, it is essential to set up a structured system of surveillance and monitoring of the implementation of National Action Plan standards, including antimicrobial consumption, with a special focus on quinolones, third generation cephalosporins and carbapenems. A quantitative estimate of antibiotic consumption (defined daily dose - DDD - consumption per 100 days of hospitalization) has been provided by the Pharmaceutical Service to the Hospital of Cittadella, ULSS 6 Euganea – Health Trust (District of Padua) for the years 2019 (before the pandemic), 2020 and 2021 for all classes of antibiotics. Multidisciplinary meetings have been organized monthly by the local Antimicrobial Stewardship Group. Between 2019 and 2021, an increase in the consumption of carbapenems in the Intensive Care Unit (from 12.2 to 18.2 DDD, + 49.2%) and a decrease in Medical wards (from 5.3 to 2.6 DDD, - 50.9%) was reported; a decrease in the consumption of quinolones in Intensive Care Unit (from 17.2 to 10.8 DDD, - 37.2%), Medical wards (from 10.5 to 6.6 DDD, - 37.1%) and Surgical wards (from 10.2 to 9.3 DDD, - 8.8%) was highlighted; an increase in the consumption of third generation cephalosporins in Medical wards (from 18.1 to 22.6 DDD, + 24,1%) was reported. Finally, after an increase in the consumption of macrolides between 2020 and 2019, in 2021, a decrease was reported in the Intensive Care Unit (DDD: 8.0 in 2019, 18.0 in 2020, 6.4 in 2021) and Medical wards (DDD: 9.0 in 2019, 13.7 in 2020, 10.9 in 2021). Constant monitoring of antimicrobial consumption and timely identifying of warning situations that may need a specific intervention are the cornerstone of Antimicrobial Stewardship programs, together with analysing data on bacterial resistance rates and infections from multi-drug resistant bacteria.

Keywords: carbapenems, quinolones, antimicrobial, stewardship

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Authors: Ehsan Abdolzadeh, Sanaz Nouri, Siamak Khalaj

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Today WSNs have many applications in different fields like the environment, military operations, discoveries, monitoring operations, and so on. Coverage size and energy consumption are the important challenges that these networks need to face. This paper tries to solve the problem of coverage with a requirement of k-coverage and minimum energy consumption. In order to minimize energy consumption, visual sensor networks have been used that observe and process just those targets that are located in their view direction. As a result, sensor rotations have decreased, and subsequently, energy consumption has been minimized. To solve the problem of coverage particle swarm optimization, coverage optimization has been able to ensure coverage requirement together with minimizing sensor rotations while meeting the problem requirement of k≤14. So energy consumption has decreased, and this could extend the sensors’ lifetime subsequently.

Keywords: K coverage, particle union optimization algorithm, wireless sensor networks, visual sensor networks

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Authors: H. E. Keshta, A. A. Ali

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Three phase grid-tied inverters are widely employed in micro-grids (MGs) as interphase between DC and AC systems. These inverters are usually controlled through standard decoupled d–q vector control strategy based on proportional integral (PI) controllers. Recently, advanced meta-heuristic optimization techniques have been used instead of deterministic methods to obtain optimum PI controller parameters. This paper provides a comparative study between the performance of the global Porcellio Scaber algorithm (GPSA) based PI controller and Manta Ray foraging optimization (MRFO) based PI controller.

Keywords: micro-grids, optimization techniques, grid-tied inverter control, PI controller

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Authors: Bashir Ahmad Amiri, Nsenda Lukumwena

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The developing economies are experiencing an unprecedented rate of urbanization, mainly the urbanization of poverty which is leading to sprawling of slums and informal settlement. Kabul, being the capital and primate city of Afghanistan is grossly encountered to the informal settlement where the majority of the people consider to be informal. Despite all efforts to upgrade and minimize the growth of these settlements, they are growing rapidly. Various interventions have been taken by the government and some international organizations from physical upgrading to urban renewal, but none of them have succeeded to solve the issue of informal settlement. The magnitude of the urbanization and the complexity of informal settlement in Kabul city, and the institutional and capital constraint of the government calls for integration and optimization of currently practiced strategies. This paper provides an overview of informal settlement formation and the conventional upgrading strategies in Kabul city to identify the dominant/successful practices and rationalize the conventional upgrading modes. For this purpose, Hothkhel has been selected as the case study, since it represents the same situation of major informal settlements of the city. Considering the existing potential and features of the Hothkhel and proposed land use by master plan this paper intends to find a suitable upgrading mode for the study area and finally to scale up the model for the city level upgrading. The result highlights that the informal settlements of Kabul city have high (re)development capacity for accepting the additional room without converting the available agricultural area to built-up. The result also indicates that the integrated multi-sector upgrading has the scale-up potential to increase the reach of beneficiaries and to ensure an inclusive and efficient urbanization.

Keywords: informal settlement, upgrading strategies, Kabul city, urban expansion, integrated multi-sector, scale-up

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Authors: Ahmed Machmoum, Malika El Kyal

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We consider iterative parallel multi-splitting method for differential algebraic equations. The main feature of the proposed idea is to use the asynchronous form. We prove that the multi-splitting technique can effectively accelerate the convergent performance of the iterative process. The main characteristic of an asynchronous mode is that the local algorithm not have to wait at predetermined messages to become available. We allow some processors to communicate more frequently than others, and we allow the communication delays tobe substantial and unpredictable. Note that synchronous algorithms in the computer science sense are particular cases of our formulation of asynchronous one.

Keywords: computer, multi-splitting methods, asynchronous mode, differential algebraic systems

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Authors: M. I. Abdelhamid, A. O. Ghallab, R. S. Ettouney, M. A. El-Rifai

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An optimization scheme based on COM server is suggested for communication between Genetic Algorithm (GA) toolbox of MATLAB and Aspen HYSYS. The structure and details of the proposed framework are discussed. The power of the developed scheme is illustrated by its application to the optimization of a recently developed natural gas liquefaction process in which Aspen HYSYS was used for minimization of the power consumption by optimizing the values of five operating variables. In this work, optimization by coupling between the GA in MATLAB and Aspen HYSYS model of the same process using the same five decision variables enabled improvements in power consumption by 3.3%, when 77% of the natural gas feed is liquefied. Also on inclusion of the flow rates of both nitrogen and carbon dioxide refrigerants as two additional decision variables, the power consumption decreased by 6.5% for a 78% liquefaction of the natural gas feed.

Keywords: stranded gas liquefaction, genetic algorithm, COM server, single nitrogen expansion, carbon dioxide pre-cooling

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Authors: Prakash Kattire, Rahul Pathare, Nilesh Tawde

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A canopy is an overhead roof structure generally used at the entrance of a building to provide shelter from rain and sun and may also be used for decorative purposes. In this paper, the canopy structure to cover the conveyor line has been studied. Existing most of the canopy structures are made of steel and glass, which makes a heavier structure, so the purpose of this study is to weight and cost optimization of the canopy. To achieve this goal, the materials of construction considered are Polyvinyl chloride (PVC) natural composite, Fiber Reinforced Plastic (FRP), and Structural steel Fe250. Designing and modeling were done in Solid works, whereas Altair Inspire software was used for the optimization of the structure. Through this study, it was found that there is a total 10% weight reduction in the structure with sufficient reserve for structural strength.

Keywords: canopy, composite, FRP, PVC

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Authors: Un-Hwan Park, Jun-Hyeok Heo, In-Sung Lee, Seong-Jin Cho, Tae-Hyeon Oh, Dae-Kyu Park

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Sound absorption coefficient is considered important when designing because noise affects emotion quality of car. It is designed with lots of experiment tunings in the field because it is unreliable to predict it for multi-layer material. In this paper, we present the design of sound absorption for automotive interior material with multiple layers using estimation software of sound absorption coefficient for reverberation chamber. Additionally, we introduce the method for estimation of physical properties required to predict sound absorption coefficient of car interior materials with multiple layers too. It is calculated by inverse algorithm. It is very economical to get information about physical properties without expensive equipment. Correlation test is carried out to ensure reliability for accuracy. The data to be used for the correlation is sound absorption coefficient measured in the reverberation chamber. In this way, it is considered economical and efficient to design automotive interior materials. And design optimization for sound absorption coefficient is also easy to implement when it is designed.

Keywords: sound absorption coefficient, optimization design, inverse algorithm, automotive interior material, multiple layers nonwoven, scaled reverberation chamber, sound impedance tubes

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Authors: Sai Siddharth S., Prasanna Kumar G. M., Alagarsamy R.

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This research introduces an alternative approach to urban road maintenance by utilizing Blended Wing Body (BWB) design and Vertical Takeoff and Landing (VTOL) drones. The integration of this aerospace innovation, combining blended wing efficiency with VTOL maneuverability, aims to optimize fuel consumption and explore versatile applications in solving urban problems. A few problems are discussed along with optimization of the design and comparative study with other drone configurations.

Keywords: design optimization, CFD, CAD, VTOL, blended wing body

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Authors: Supriya Chatla, Anjana Male, Srikala Kamireddy

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L-asparaginase (E.C.3.5.1.1) is an anti-cancer enzyme that has been purified and characterized for decades to study and evaluate its anti-carcinogenic activity against Hodgkin’s lymphoma. The present investigation deals with screening, isolation and optimization of L-asparaginase giving fungal strain of soil samples from different areas of AP, India. L-Aspariginase activity was estimated on the basis of the pink color surrounding the growing colony. A total of 132 colonies were screened and isolated from different samples. Based on the zone diameter, L-asparaginase activity is determined, L- asparaginase activity is optimized at 28oc and Immobilized Aspariginase had more potency than the free enzymes.

Keywords: aspariginase, anticancer enzyme, Isolation, optimization

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Authors: Kristina Pflug, Markus Busch

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Being able to predict polymer properties and processing behavior based on the applied operating reaction conditions in one of the key challenges in modern polymer reaction engineering. Especially, for cost-intensive processes such as the high-pressure polymerization of low-density polyethylene (LDPE) with high safety-requirements, the need for simulation-based process optimization and product design is high. A multi-scale modelling approach was set-up and validated via a series of high-pressure mini-plant autoclave reactor experiments. The approach starts with the numerical modelling of the complex reaction network of the LDPE polymerization taking into consideration the actual reaction conditions. While this gives average product properties, the complex polymeric microstructure including random short- and long-chain branching is calculated via a hybrid Monte Carlo-approach. Finally, the processing behavior of LDPE -its melt flow behavior- is determined in dependence of the previously determined polymeric microstructure using the branch on branch algorithm for randomly branched polymer systems. All three steps of the multi-scale modelling approach can be independently validated against analytical data. A triple-detector GPC containing an IR, viscosimetry and multi-angle light scattering detector is applied. It serves to determine molecular weight distributions as well as chain-length dependent short- and long-chain branching frequencies. 13C-NMR measurements give average branching frequencies, and rheological measurements in shear and extension serve to characterize the polymeric flow behavior. The accordance of experimental and modelled results was found to be extraordinary, especially taking into consideration that the applied multi-scale modelling approach does not contain parameter fitting of the data. This validates the suggested approach and proves its universality at the same time. In the next step, the modelling approach can be applied to other reactor types, such as tubular reactors or industrial scale. Moreover, sensitivity analysis for systematically varying process conditions is easily feasible. The developed multi-scale modelling approach finally gives the opportunity to predict and design LDPE processing behavior simply based on process conditions such as feed streams and inlet temperatures and pressures.

Keywords: low-density polyethylene, multi-scale modelling, polymer properties, reaction engineering, rheology

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Authors: Byeong-Sam Kim, Kyeongwoo Park

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In this study, induced structural optimization is performed to compare the trade-off between wing weight and induced drag for wing panel extensions, construction of wing panel and winglets. The aerostructural optimization problem consists of parameters with strength condition, and two maneuver conditions using residual stresses in panel production. The results of kinematic motion analysis presented a homogenization based theory for 3D beams and 3D shells for wing panel. This theory uses a kinematic description of the beam based on normalized displacement moments. The displacement of the wing is a significant design consideration as large deflections lead to large stresses and increased fatigue of components cause residual stresses. The stresses in the wing panel are small compared to the yield stress of aluminum alloy. This study describes the implementation of a large wing panel, aerostructural analysis and structural parameters optimization framework that couples a three-dimensional panel method.

Keywords: wing panel, aerostructural optimization, FEM, structural analysis

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Authors: Meziane Rachid, Boufala Seddik, Hamzi Amar, Amara Mohamed

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Today’s energy industry seeks maximum benefit with maximum reliability. In order to achieve this goal, design engineers depend on reliability optimization techniques. This work uses a harmony search algorithm (HS) meta-heuristic optimization method to solve the problem of wind-Solar-Gas power systems design optimization. We consider the case where redundant electrical components are chosen to achieve a desirable level of reliability. The electrical power components of the system are characterized by their cost, capacity and reliability. The reliability is considered in this work as the ability to satisfy the consumer demand which is represented as a piecewise cumulative load curve. This definition of the reliability index is widely used for power systems. The proposed meta-heuristic seeks for the optimal design of series-parallel power systems in which a multiple choice of wind generators, transformers and lines are allowed from a list of product available in the market. Our approach has the advantage to allow electrical power components with different parameters to be allocated in electrical power systems. To allow fast reliability estimation, a universal moment generating function (UMGF) method is applied. A computer program has been developed to implement the UMGF and the HS algorithm. An illustrative example is presented.

Keywords: reliability optimization, harmony search optimization (HSA), universal generating function (UMGF)

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Authors: Tomas Barnak, Libor Matejka

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The aim of this study is to create a standard application using multi-criteria evaluation in the field of forensic engineering. This situation can occur in the professional assessment in several cases such as when it is necessary to consider more criteria variant of the structural subsystems, more variants according to several criteria based on a court claim, which requires expert advice. A problematic situation arises when it is necessary to clearly determine the ranking of the options according to established criteria, and reduce subjective evaluation. For the procurement in the field of construction which is based on the prepared text of the law not only economic criteria but also technical, technological and environmental criteria will be determined. This fact substantially changes the style of evaluation of individual bids. For the above-mentioned needs of procurement, the unification of expert’s decisions and the use of multi-criteria assessment seem to be a reasonable option. In the case of experimental verification when using multi-criteria evaluation of alternatives construction subsystem the economic, technical, technological and environmental criteria will be compared. The core of the solution is to compare a selected number of set criteria, application methods and evaluation weighting based on the weighted values assigned to each of the criteria to use multi-criteria evaluation methods. The sequence of individual variations is determined by the evaluation of the importance of the values of corresponding criteria concerning expertise in the problematic of outside wall constructional subsystems.

Keywords: criteria, expertise, multi-criteria evaluation, outside wall subsystems

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Authors: Mert Turanli, Hakan Temeltas

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In this paper, we present an adaptive controller for decentralized coordination problem of multiple non-holonomic agents. The performance of the presented Multi-Agent Bounded Gain Forgetting (BGF) Composite Adaptive controller is compared against the tracking error criterion with a Feedback Linearization controller. By using the method, the sensor nodes move and reconfigure themselves in a coordinated way in response to a sensed environment. The multi-agent coordination is achieved through Centroidal Voronoi Tessellations and Coverage Control. Also, a consensus protocol is used for synchronization of the parameter vectors. The two controllers are given with their Lyapunov stability analysis and their stability is verified with simulation results. The simulations are carried out in MATLAB and ROS environments. Better performance is obtained with BGF Adaptive Controller.

Keywords: adaptive control, centroidal voronoi tessellations, composite adaptation, coordination, multi robots

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Authors: A. Peniak, J. Makarovič, P. Rafajdus, P. Dúbravka

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The purpose of this work is to optimize a Switched Reluctance Motor (SRM) for an automotive application, specifically for a fully electric car. A new optimization approach is proposed. This unique approach transforms automotive customer requirements into an optimization problem, based on sound knowledge of a SRM theory. The approach combines an analytical and a finite element analysis of the motor to quantify static nonlinear and dynamic performance parameters, as phase currents and motor torque maps, an output power and power losses in order to find the optimal motor as close to the reality as possible, within reasonable time. The new approach yields the optimal motor which is competitive with other types of already proposed motors for automotive applications. This distinctive approach can also be used to optimize other types of electrical motors, when parts specifically related to the SRM are adjusted accordingly.

Keywords: automotive, drive system, electric car, finite element method, hybrid car, optimization, switched reluctance motor

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Authors: Yassir Abdelrazig, Ren Moses

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Roadway planning and design is a very complex process involving five key phases before a project is completed; planning, project development, final design, right-of-way, and construction. The planning phase for a new roadway transportation project is a very critical phase as it greatly affects all latter phases of the project. A location study is usually performed during the preliminary planning phase in a new roadway project. The objective of the location study is to develop alignment alternatives that are cost efficient considering land acquisition and construction costs. This paper describes a methodology to develop optimal preliminary roadway alignments utilizing spatial-data. Four optimization criteria are taken into consideration; roadway length, land cost, land slope, and environmental impacts. The basic concept of the methodology is to convert the proposed project area into a grid, which represents the search space for an optimal alignment. The aforementioned optimization criteria are represented in each of the grid’s cells. A spatial-data optimization technique is utilized to find the optimal alignment in the search space based on the four optimization criteria. Two case studies for new roadway projects in Duval County in the State of Florida are presented to illustrate the methodology. The optimization output alignments are compared to the proposed Florida Department of Transportation (FDOT) alignments. The comparison is based on right-of-way costs for the alignments. For both case studies, the right-of-way costs for the developed optimal alignments were found to be significantly lower than the FDOT alignments.

Keywords: gemoetric design, optimization, planning, roadway planning, roadway design

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Authors: S. H. Lee, M. J. Park, O. M. Kwon

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In this paper, reliable consensus of multi-agent systems with sampled-data is investigated. By using a suitable Lyapunov-Krasovskii functional and some techniques such as Wirtinger Inequality, Schur Complement and Kronecker Product, the results of this systems are obtained by solving a set of Linear Matrix Inequalities(LMIs). One numerical example is included to show the effectiveness of the proposed criteria.

Keywords: multi-agent, linear matrix inequalities (LMIs), kronecker product, sampled-data, Lyapunov method

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Authors: Ahmed Madian, Muaz Aljarhi

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Coordinate Rotation Digital Computer (CORDIC) is a unique digital computing unit intended for the computation of mathematical operations and functions. This paper presents a multi-CORDIC processor that integrates different CORDIC architectures on a single FPGA chip and allows the user to select the CORDIC architecture to proceed with based on what he wants to calculate and his/her needs. Synthesis show that radix 2 CORDIC has the lowest clock delay, radix 8 CORDIC has the highest LUT usage and lowest register usage while Hybrid Radix 4 CORDIC had the highest clock delay.

Keywords: multi, CORDIC, FPGA, processor

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Authors: Yasmin A. M. Ferreira, Ana C. K. Pelissari, Sofia De C. F. Vicente, Raquel M. Da S. Campos, Deborah C. L. Masquio, Lian Tock, Lila M. Oyama, Flavia C. Corgosinho, Valter T. Boldarine, Ana R. Dâmaso

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The prevalence of overweight and obesity is growing around the world and currently considered a global epidemic. Food and nutrition are essential requirements for promoting health and protecting non-communicable chronic diseases, such as obesity and cardiovascular disease. Specific dietary components may modulate the inflammation and oxidative stress in obese individuals. Few studies have investigated the dietary Inflammation Factor Rating (IFR) in obese adolescents. The IFR was developed to characterize an individual´s diet on anti- to pro-inflammatory score. This evaluation contributes to investigate the effects of inflammatory diet in metabolic profile in several individual conditions. Objectives: The present study aims to investigate the effects of a multidisciplinary weight loss therapy on inflammation factor rating and cardiometabolic risk in obese adolescents. Methods: A total of 26 volunteers (14-19 y.o) were recruited and submitted to 20 weeks interdisciplinary therapy allied to health education website- Ciclo do Emagrecimento®, including clinical, nutritional, psychological counseling and exercise training. The body weight was monitored weekly by self-report and photo. The adolescents answered a test to evaluate the knowledge of the topics covered in the videos. A 24h dietary record was applied at the baseline and after 20 weeks to assess the food intake and to calculate IFR. A negative IFR suggests that diet may have inflammatory effects and a positive IFR indicates an anti-inflammatory effect. Statistical analysis was performed using the program STATISTICA version 12.5 for Windows. The adopted significant value was α ≤ 5 %. Data normality was verified with the Kolmogorov Smirnov test. Data were expressed as mean±SD values. To analyze the effects of intervention it was applied test t. Pearson´s correlations test was performed. Results: After 20 weeks of treatment, body mass index (BMI), body weight, body fat (kg and %), abdominal and waist circumferences decreased significantly. The mean of high-density lipoprotein cholesterol (HDL-c) increased after the therapy. Moreover, it was found an improvement of inflammation factor rating from -427,27±322,47 to -297,15±240,01, suggesting beneficial effects of nutritional counselling. Considering the correlations analysis, it was found that pro-inflammatory diet is associated with increase in the BMI, very low-density lipoprotein cholesterol (VLDL), triglycerides, insulin and insulin resistance index (HOMA-IR); while an anti-inflammatory diet is associated with improvement of HDL-c and insulin sensitivity Check index (QUICKI). Conclusion: The 20-week blended multidisciplinary therapy was effective to reduce body weight, anthropometric circumferences and improve inflammatory markers in obese adolescents. In addition, our results showed that an increase in inflammatory profile diet is associated with cardiometabolic parameters, suggesting the relevance to stimulate anti-inflammatory diet habits as an effective strategy to treat and control of obesity and related comorbidities. Financial Support: FAPESP (2017/07372-1) and CNPq (409943/2016-9)

Keywords: cardiometabolic risk, inflammatory diet, multidisciplinary therapy, obesity

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Authors: Paffrath Meinhard, Zhou Yayun, Guo Yiqing, Ertl Harald

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Winding geometry design is an important part of power transformer electrical design. Conventionally, the winding geometry is designed manually, which is a time-consuming job because it involves many iteration steps in order to meet all cost, manufacturing and electrical requirements. Here a method is presented which automatically generates the winding geometry for given user parameters and allows the user to interactively set and change parameters. To achieve this goal, the winding problem is transferred to a mixed integer nonlinear optimization problem. The relevant geometrical design parameters are defined as optimization variables. The cost and other requirements are modeled as constraints. For the solution, a stochastic ant colony optimization algorithm is applied. It is well-known, that an optimizer can get stuck in a local minimum. For the winding problem, we present efficient strategies to come out of local minima, furthermore a reduced variable search range helps to accelerate the solution process. Numerical examples show that the optimization result is delivered within seconds such that the user can interactively change the variable search area and constraints to improve the design.

Keywords: ant colony optimization, mixed integer nonlinear programming, power transformer, winding design

Procedia PDF Downloads 364