Search results for: functional zoning optimization and upgrading

Authors: Inayat Ur Rehman, Georgia Sakellari

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Cloud computing has evolved into a vital technology for businesses, offering scalability, flexibility, and cost-effectiveness. However, maintaining high availability and optimal performance in the cloud is crucial for reliable services. This paper explores the significance of cloud monitoring and performance optimization in sustaining the high availability of cloud-based systems. It discusses diverse monitoring tools, techniques, and best practices for continually assessing the health and performance of cloud resources. The paper also delves into performance optimization strategies, including resource allocation, load balancing, and auto-scaling, to ensure efficient resource utilization and responsiveness. Addressing potential challenges in cloud monitoring and optimization, the paper offers insights into data security and privacy considerations. Through this thorough analysis, the paper aims to underscore the importance of cloud monitoring and performance optimization for ensuring a seamless and highly available cloud computing environment.

Keywords: cloud computing, cloud monitoring, performance optimization, high availability, scalability, resource allocation, load balancing, auto-scaling, data security, data privacy

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Authors: Ayudhia P. Gusti, Semin

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It is known that total operating cost of a vessel is dominated by the cost of fuel consumption. How to reduce the fuel cost of ship so that the operational costs of fuel can be minimized is the question that arises. As the basis of these kinds of problem, sailing speed determination is an important factor to be considered by a shipping company. Optimal speed determination will give a significant influence on the route and berth schedule of ships, which also affect vessel operating costs. The purpose of this paper is to clarify some important issues about ship speed optimization. Sailing speed, displacement, sailing time, and specific fuel consumption were obtained from shipping log data to be further analyzed for modeling the speed optimization. The presented speed optimization model is expected to affect the fuel consumption and to reduce the cost of fuel consumption.

Keywords: maritime transportation, reducing fuel, shipping log data, speed optimization

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Authors: Taisir Eldos, Aws Kanan, Waleed Nazih, Ahmad Khatatbih

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Chemical Reaction Optimization (CRO) is an optimization metaheuristic inspired by the nature of chemical reactions as a natural process of transforming the substances from unstable to stable states. Starting with some unstable molecules with excessive energy, a sequence of interactions takes the set to a state of minimum energy. Researchers reported successful application of the algorithm in solving some engineering problems, like the quadratic assignment problem, with superior performance when compared with other optimization algorithms. We adapted this optimization algorithm to the Printed Circuit Board Drilling Problem (PCBDP) towards reducing the drilling time and hence improving the PCB manufacturing throughput. Although the PCBDP can be viewed as instance of the popular Traveling Salesman Problem (TSP), it has some characteristics that would require special attention to the transactions that explore the solution landscape. Experimental test results using the standard CROToolBox are not promising for practically sized problems, while it could find optimal solutions for artificial problems and small benchmarks as a proof of concept.

Keywords: evolutionary algorithms, chemical reaction optimization, traveling salesman, board drilling

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Authors: M. A. Lahmer, K. Guergouri

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The ferromagnetic properties of carbon-doped ZnO (ZnO:CO) and hydrogenated carbon-doped ZnO (ZnO:CO+H) are investigated using the density functional tight binding (DFTB) method. Our results reveal that CO-doped ZnO is a ferromagnetic material with a magnetic moment of 1.3 μB per carbon atom. The presence of hydrogen in the material in the form of CO-H complex decreases the total magnetism of the material without suppressing ferromagnetism. However, the system in this case becomes quickly antiferromagnetic when the C-C separation distance was increased.

Keywords: ZnO, carbon, hydrogen, ferromagnetism, density functional tight binding

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Authors: Ali Motalebi Saraji, Reza Zarei Lamuki

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Speed control and behavior improvement of permanent magnet synchronous motors (PMSM) that have reliable performance, low loss, and high power density, especially in industrial drives, are of great importance for researchers. Because of its importance in this paper, coefficients optimization of proportional-integrator-derivative fractional order controller is presented using Particle Swarm Optimization (PSO) algorithm in order to improve the behavior of PMSM in its speed control loop. This improvement is simulated in MATLAB software for the proposed optimized proportional-integrator-derivative fractional order controller with a Genetic algorithm and compared with a full order controller with a classic optimization method. Simulation results show the performance improvement of the proposed controller with respect to two other controllers in terms of rising time, overshoot, and settling time.

Keywords: speed control loop of permanent magnet synchronous motor, fractional and full order proportional-integrator-derivative controller, coefficients optimization, particle swarm optimization, improvement of behavior

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Authors: Mohammad Mehdi Mazarei, Ali Asghar Behroozpoor

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In this paper, we define an optimization problem corresponding to smooth and nonsmooth functions which its optimal solution is the first derivative of these functions in a domain. For this purpose, a linear programming problem corresponding to optimization problem is obtained. The optimal solution of this linear programming problem is the approximate generalized first derivative. In fact, we approximate generalized first derivative of nonsmooth functions as tailor series. We show the efficiency of our approach by some smooth and nonsmooth functions in some examples.

Keywords: general derivative, linear programming, optimization problem, smooth and nonsmooth functions

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Authors: Michal Kopcek, Tomas Skulavik, Michal Kebisek, Gabriela Krizanova

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The operation of nuclear power plants involves continuous monitoring of the environment in their area. This monitoring is performed using a complex data acquisition system, which collects status information about the system itself and values of many important physical variables e.g. temperature, humidity, dose rate etc. This paper describes a proposal and optimization of communication that takes place in teledosimetric system between the central control server responsible for the data processing and storing and the decentralized measuring stations, which are measuring the physical variables. Analyzes of ongoing communication were performed and consequently the optimization of the system architecture and communication was done.

Keywords: communication protocol, transmission optimization, data acquisition, system architecture

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Authors: Chandrashekara Krishnappa, Yogish Huchaiah

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The present work considers the importance of economic feasibility and financial viability of biodiesel production, and its use in the present context of prevailing Indian scenario. For this, costs involved in production of one litre of biodiesel from non-edible Jatropha and Pongamia oils Nano mix are considered. Biodiesel derived from the mix is blended with petrodiesel in various proportions and used in Compression Ignition (CI) Direct Injection (DI) engine. Performance and Emission characteristics were investigated. Optimization of the blends considering experimental results was carried out. To validate the experimental results and optimization, Multi-Functional Criteria Technique (MFCT) is used. Further, value additions in terms of INR due to increase in performance and reduction in emissions are investigated. Cost component of subsidy on petrodiesel is taken into consideration in the calculation of cost of one litre of it. Comparison of costs is with respect to the unit of power generated per litre of COME and petrodiesel. By the analysis it has been concluded that the amount saved with subsidy is INR 1.45 Lakh Crores per year and it is INR1.60 Lakh Crores per year without subsidy for petrodiesel.

Keywords: cap value addition, economic analysis, MFCT, NACOME, subsidy

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Authors: Filippo Ranalli, Forest Flager, Martin Fischer

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This paper presents a ground structure method to optimize the topology and discrete member sizing of steel frame structures in order to minimize total installed cost, including material, fabrication and erection components. The proposed method improves upon existing cost-based ground structure methods by incorporating constructability considerations well as satisfying both strength and serviceability constraints. The architecture for the method is a bi-level Multidisciplinary Feasible (MDF) architecture in which the discrete member sizing optimization is nested within the topology optimization process. For each structural topology generated, the sizing optimization process seek to find a set of discrete member sizes that result in the lowest total installed cost while satisfying strength (member utilization) and serviceability (node deflection and story drift) criteria. To accurately assess cost, the connection details for the structure are generated automatically using accurate site-specific cost information obtained directly from fabricators and erectors. Member continuity rules are also applied to each node in the structure to improve constructability. The proposed optimization method is benchmarked against conventional weight-based ground structure optimization methods resulting in an average cost savings of up to 30% with comparable computational efficiency.

Keywords: cost-based structural optimization, cost-based topology and sizing, optimization, steel frame ground structure optimization, multidisciplinary optimization of steel structures

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Authors: Yangming Zhu, Mingming Guo, Xiaozan Wang

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Introduction: The purpose of this study is to integrate functional training into physical education to test the effectiveness of functional training in improving the physical fitness (PF) and sport skills (SS) of female college students. Methods: A total of 54 female college students from East China Normal University were selected for this study (27 in the experimental group and 27 in the control group), and 13 weeks of the experimental intervention was conducted during the semester. During the experimental period, the experimental group was functionally trained for 1 hour per week. The control group performed one-hour weekly sports (such as basketball, football, etc.) as usual. Before and after the experiment, the national students' physical fitness test was used to test the PF of the experimental group and the control group, and the SS of the experimental group and the control group were tested before and after the intervention. Then using SPSS and Excel to organize and analyze the data. Results: The independent sample T-test showed that there was no significant difference in the PF and SS between the experimental group and the control group before the experiment (T PF=71.86, p PF> 0.05, Tₛₛ=82.41,pₛₛ > 0.05); After the experiment, the PF of the experimental group was significantly higher than that of the control group (T Improve=71.86, p Improve < 0.05); after the experiment, the SS of the experimental group was significantly higher than that of the control group (Tₛₛ = 1.31, pₛₛ <0.01) Conclusions: Integrating functional training into physical education can improve the PF of female college students. At the same time, the integration of functional training into physical education can also effectively improve the SS of female college students. Therefore, it is suggested that functional training be integrated into the daily physical education of female college students so as to improve their PF and SS.

Keywords: functional training, physical fitness, sport skills, female college students

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Authors: Khan Shahid, Shahid Zakia

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This article explores the fields of Theology and Islamic Philosophy in alignment with the SOUL (Sincere act, Optimization efforts, Ultimate goal, Law compliance) framework. It examines their historical development and demonstrates how embracing sincerity, optimization, ultimate goals, and law compliance enhances these disciplines within the Islamic context. By emphasizing the importance of Sincere acts, Optimization efforts, Ultimate goal, and Law compliance, this article provides a framework for enriching Theology and Islamic Philosophy.

Keywords: SOUL framework, Theology, Islamic Philosophy, Sincerity act, Optimization effort, Ultimate goal, Law compliance

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Authors: Mohammed Belloufi, Rachid Benzine, Badreddine Sellami

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Conjugate gradient methods is useful for solving large scale optimization problems in scientific and engineering computation, characterized by the simplicity of their iteration and their low memory requirements. It is well known that the search direction plays a main role in the line search method. In this paper, we propose a search direction with the Wolfe line search technique for solving unconstrained optimization problems. Under the above line searches and some assumptions, the global convergence properties of the given methods are discussed. Numerical results and comparisons with other CG methods are given.

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

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Authors: Preetham Shankapal, Jill King, Kori Murray, Corby Martin, Paula Giselman, Jason Hicks, Owen Carmicheal

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Activation of reward and satiety networks in the brain while processing palatable food cues, as well as functional connectivity during rest has been studied using functional Magnetic Resonance Imaging of the brain in various obesity phenotypes. However, functional connectivity within the reward and satiety network during food cue processing is understudied. 14 obese individuals underwent two fMRI scans during viewing of Macronutrient Picture System images. Each scan included two blocks of images of High Sugar/High Fat (HSHF), High Carbohydrate/High Fat (HCHF), Low Sugar/Low Fat (LSLF) and also non-food images. Seed voxels within seven food reward relevant ROIs: Insula, putamen and cingulate, precentral, parahippocampal, medial frontal and superior temporal gyri were isolated based on a prior meta-analysis. Beta series correlation for task-related functional connectivity between these seed voxels and the rest of the brain was computed. Voxel-level differences in functional connectivity were calculated between: first and the second scan; individuals who saw novel (N=7) vs. Repeated (N=7) images in the second scan; and between the HC/HF, HSHF blocks vs LSLF and non-food blocks. Computations and analysis showed that during food image viewing, reward network ROIs showed significant functional connectivity with each other and with other regions responsible for attentional and motor control, including inferior parietal lobe and precentral gyrus. These functional connectivity values were heightened among individuals who viewed novel HS/HF images in the second scan. In the second scan session, functional connectivity was reduced within the reward network but increased within attention, memory and recognition regions, suggesting habituation to reward properties and increased recollection of previously viewed images. In conclusion it can be inferred that Functional Connectivity within reward network and between reward and other brain regions, varies by important experimental conditions during food photography viewing, including habituation to shown foods.

Keywords: fMRI, functional connectivity, task-based, beta series correlation

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Authors: Akshay Paranjape, Nils Plettenberg, Robert Schmitt

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Producing faulty products can be costly for manufacturing companies and wastes resources. To reduce scrap rates in manufacturing, process parameters can be optimized using machine learning. Thus far, research mainly focused on optimizing specific processes using traditional algorithms. To develop a framework that enables real-time optimization based on a predictive model for an arbitrary production process, this study explores the application of reinforcement learning (RL) in this field. Based on a thorough review of literature about RL and process parameter optimization, a model based on maximum a posteriori policy optimization that can handle both numerical and categorical parameters is proposed. A case study compares the model to state–of–the–art traditional algorithms and shows that RL can find optima of similar quality while requiring significantly less time. These results are confirmed in a large-scale validation study on data sets from both production and other fields. Finally, multiple ways to improve the model are discussed.

Keywords: reinforcement learning, production process optimization, evolutionary algorithms, policy optimization, actor critic approach

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Authors: Rohit Mittal, Bright Keswani, Amit Mithal

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This paper provides a sense about the application of computational intelligence techniques used to develop computer games, especially car racing. For the deep sense and knowledge of artificial intelligence, this paper is divided into various sections that is optimization, imitation, innovation and combining approach of optimization and imitation. This paper is mainly concerned with combining approach which tells different aspects of using fitness measures and supervised learning techniques used to imitate aspects of behavior. The main achievement of this paper is based on modelling player behaviour and evolving new game content such as racing tracks as single car racing on single track.

Keywords: evolution algorithm, genetic, optimization, imitation, racing, innovation, gaming

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Authors: María Luisa Gonzalez-SanJose, Mihaela Mihnea, Vicente Gomez-Miguel

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The zoning methodology currently recommended by the OIVV as official methodology to carry out viticulture zoning studies and to define and delimit the ‘terroirs’ has been applied in this study. This methodology has been successfully applied on the most significant an important Spanish Oenological D.O. regions, such as Ribera de Duero, Rioja, Rueda and Toro, but also it have been applied around the world in Portugal, different countries of South America, and so on. This is a complex methodology that uses edaphoclimatic data but also other corresponding to vineyards and other soils’ uses The methodology is useful to determine Homogeneous Soil Units (HSU) to different scale depending on the interest of each study, and has been applied from viticulture regions to particular vineyards. It seems that this methodology is an appropriate method to delimit correctly the medium in order to enhance its uses and to obtain the best viticulture and oenological products. The present work is focused on the comparison of volatile composition of wines made from grapes grown in different HSU that coexist in a particular viticulture region of Castile-Lion cited near to Burgos. Three different HSU were selected for this study. They represented around of 50% of the global area of vineyards of the studied region. Five different vineyards on each HSU under study were chosen. To reduce variability factors, other criteria were also considered as grape variety, clone, rootstocks, vineyard’s age, training systems and cultural practices. This study was carried out during three consecutive years, then wine from three different vintage were made and analysed. Different red wines were made from grapes harvested in the different vineyards under study. Grapes were harvested to ‘Technological maturity’, which are correlated with adequate levels of sugar, acidity, phenolic content (nowadays named phenolic maturity), good sanitary stages and adequate levels of aroma precursors. Results of the volatile profile of the wines produced from grapes of each HSU showed significant differences among them pointing out a direct effect of the edaphoclimatic characteristic of each UHT on the composition of the grapes and then on the volatile composition of the wines. Variability induced by HSU co-existed with the well-known inter-annual variability correlated mainly with the specific climatic conditions of each vintage, however was most intense, so the wine of each HSU were perfectly differenced. A discriminant analysis allowed to define the volatiles with discriminant capacities which were 21 of the 74 volatiles analysed. Detected discriminant volatiles were chemical different, although .most of them were esters, followed by were superior alcohols and fatty acid of short chain. Only one lactone and two aldehydes were selected as discriminant variable, and no varietal aroma compounds were selected, which agree with the fact that all the wine were made from the same grape variety.

Keywords: viticulture zoning, terroir, wine, volatile profile

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Authors: Bara Yousef

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The development of independency and functional participation is an important therapeutic goal for many children with cerebral palsy,They was many therapeutic approach have been used for treatment those children like neurodevelopment treatment, balance training strengthening and stretching exercise. More recently, therapy for children with cerebral palsy has focused on achieving functional goals using task-oriented interventions and summer camping model, which focus on activities that relevant and meaningful to the child, to learn more efficient and effective motor skills. We explore the effectiveness of using functional rehabilitation comparing with regular rehabilitation among 40 Saudi children with cerebral palsy in pediatric unit at Sultan Bin Abdul Aziz Humanitarian City-Ksa ,where 20 children randomly assign in control group who received rehabilitation based on regular therapy approach and other 20 children assign on experiment group who received rehabilitation based on functional therapy approach with an average of 45min OT treatment and 45 min PT treatment- daily within a period of 6 week. Our finding reported that children in experiment group has improved in gross motor function with an average from 49.4 to 57.6 based on GMFM 66 as primary outcome measure and improved in WeeFIM with an average from 52 to 62 while children in control group has improved with an average from 48.4 to 53.7 in GMFM and from 53 to and 58 in WeeFIM. Consequently, there has been growing interest in determining the effects of functional training programs as promising approach for these children.

Keywords: Cerebral Palsy (CP), gross motor function measure (GMFM66), pediatric Functional Independent Measure (WeeFIM), rehabilitation, disability

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Authors: Tabiti S. Tabiti, A. M. Jinadu, Daramola Japheth

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Urban insecurity is among the challenges militating against sustainable urban governance; in the first place it distorts the peace of urban areas making them unsafe. On the other hand it hinders the effective performance of urban functions. Urban security challenges manifest in different forms such as, street violence, theft and robbery, accidents of different types kidnapping, killings etc.. Efforts to address urban security challenges in Nigeria have been concentrated in legislative, law enforcement and the use of community vigilante groups. However in this study, the place of physical planning strategy through effective neighbourhood renewal as practiced in Mokola is presented as an effective complementary approach for addressing urban insecurity. On this backdrop, the paper recommends the need for gradual rehabilitation of urban slum neighborhoods by the state government in collaboration with World Bank and other development financiers. The local governments should be made autonomy in Nigeria so as to make them more responsible to the people. Other recommendations suggested in the paper include creating enabling environment that will promote economic empowerment and public enlightment on personal and community sanitation. It is certain that if these recommendations are adopted the challenge of urban insecurity will reduce significantly in Nigerian cities.

Keywords: neighbourhood renewal, pilot project, slum upgrading, urban security

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Authors: N. A. Mokhtar, A. G. Hussin, Y. Z. Zubairi

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This paper proposes a new simultaneous simple linear functional relationship model by assuming equal error variances. We derive the maximum likelihood estimate of the parameters in the simultaneous model and the covariance. We show by simulation study the small bias values of the parameters suggest the suitability of the estimation method. As an illustration, the proposed simultaneous model is applied to real data of the wind direction and wave direction measured by two different instruments.

Keywords: simultaneous linear functional relationship model, Fisher information matrix, parameter estimation, circular variables

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Authors: Fawzi Srairi, Abderrahmane Dib

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Recently, the desire for a self-powered micro and nanodevices has attracted a great interest of using sustainable energy sources. Further, the ultimate goal of nanogenerator is to harvest energy from the ambient environment in which a self-powered device based on these generators is needed. With the development of nanogenerator-based circuits design and optimization, the building of new device simulator is necessary for the study and the synthesis of electromechanical parameters of this type of models. In the present article, both numerical modeling and optimization of piezoelectric nanogenerator based on zinc oxide have been carried out. They aim to improve the electromechanical performances, robustness, and synthesis process for nanogenerator. The proposed model has been developed for a systematic study of the nanowire morphology parameters in stretching mode. In addition, heuristic optimization technique, namely, particle swarm optimization has been implemented for an analytic modeling and an optimization of nanogenerator-based process in stretching mode. Moreover, the obtained results have been tested and compared with conventional model where a good agreement has been obtained for excitation mode. The developed nanogenerator model can be generalized, extended and integrated into simulators devices to study nanogenerator-based circuits.

Keywords: electrical potential, heuristic algorithms, numerical modeling, nanogenerator

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Authors: Reza Sirjani, Nobosse Tafem Bolan

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Many optimization techniques available in the literature have been developed in order to solve the problem of voltage stability enhancement in power systems. However, there are a number of drawbacks in the use of previous techniques aimed at determining the optimal location and size of reactive compensators in a network. In this paper, an Improved Cuckoo Search algorithm is applied as an appropriate optimization algorithm to determine the optimum location and size of a Static Var Compensator (SVC) in a transmission network. The main objectives are voltage stability improvement and total cost minimization. The results of the presented technique are then compared with other available optimization techniques.

Keywords: cuckoo search algorithm, optimization, power system, var compensators, voltage stability

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Authors: Olakunle Moses Makanjuola, Adebola Ajayi

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Noodles are made from unleavened dough, rolled flat and cut into shapes. The instant noodle market is growing fast in Asian countries and is gaining popularity in the western market. This project reports on the proximate functional and sensory evaluation of different brands of instant noodles in Nigeria. The comparisons were based on proximate functional and sensory evaluation of the product. The result obtained from the proximate analysis showed that sample QHR has the highest moisture content, sample BMG has the highest protein content, sample CPO has the highest fat content, sample. The obtained result from the functional properties showed that sample BMG (Dangote noodles) had the highest volume increase after cooking due to its high swelling capacity, high water absorption capacity and high hydration capacity. Sample sensory analysis of the noodles showed that all the samples are of significant difference (at P < 0.05) in terms of colour, texture, and aroma but there is no significant difference in terms of taste and overall acceptability. Sample QHR (Indomie noodles) is the most preferred by the panelists.

Keywords: proximate, functional, sensory evaluation, noodles

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Authors: Hugo d’Albert, Udo Lindemann

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The number of automotive electronic systems that allow realizing new functions, like driver assistance systems, has been increasing extremely in the last decade. Although they bring several benefits, their malfunctions can lead to severe consequences, such as personal injury of road users. Functional safety is an approach to identify these critical malfunctions and arrange technical systems that include only tolerable risk. This approach is– in comparison with other technical areas– relatively new in the automotive sector. For a long time, the automotive systems have based on mechanical components and approved principles, like robust design. With a growing number of electric and electronic components in the modern cars and realizing by software of the system functions, the need for new standards and methods to assure the functional safety has arisen. This paper described the current state of engineering for safety in automotive sector and discusses new directions to meet the challenges of the future.

Keywords: automotive systems, functional safety, quality engineering, quality management

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

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This paper deals with the Vehicle Routing Problem (VRP) with environmental considerations which is called Pollution Routing Problem (PRP). The objective is to minimize the operational and environmental costs. It consists of routing a number of vehicles to serve a set of customers, and determining fuel consumption, driver wages and their speed on each route segment, while respecting the capacity constraints and time windows. In this context, we presented an Ant Colony Optimization (ACO) approach, combined with a Speed Optimization Algorithm (SOA) to solve the PRP. The proposed solution method consists of two stages. Stage one is to solve a Vehicle Routing Problem with Time Window (VRPTW) using ACO and in the second stage a SOA is run on the resulting VRPTW solutions. Given a vehicle route, the SOA consists of finding the optimal speed on each arc of the route in order to minimize an objective function comprising fuel consumption costs and driver wages. The proposed algorithm tested on benchmark problem, the preliminary results show that the proposed algorithm is able to provide good solutions.

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

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

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This paper investigates stability problem for linear systems of neutral type with time-varying delay. By constructing various Lyapunov-Krasovskii functional, and utilizing some mathematical techniques, the sufficient stability conditions for the systems are established in terms of linear matrix inequalities (LMIs), which can be easily solved by various effective optimization algorithms. Finally, some illustrative examples are given to show the effectiveness of the proposed criterion.

Keywords: neutral systems, time-delay, stability, Lyapnov method, LMI

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Authors: Harald Lang, Michael Bader, A. Buchroithner

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Holistic methods covering the development process as a whole – e.g. systems engineering – have established themselves in product design. However, technical product optimization, representing improvements in efficiency and/or minimization of loss, usually applies to single components of a system. A holistic approach is being defined based on a hierarchical point of view of systems engineering. This is subsequently presented using the example of an electromechanical flywheel energy storage system for automotive applications.

Keywords: design, product development, product optimization, systems engineering

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Authors: Kawser Ahmed, K. Bousson, Milca F. Coelho

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4D flight trajectory optimization is one of the key ingredients to improve flight efficiency and to enhance the air traffic capacity in the current air traffic management (ATM). The present paper explores the iterative dynamic programming (IDP) as a potential numerical optimization method for 4D flight trajectory optimization. IDP is an iterative version of the Dynamic programming (DP) method. Due to the numerical framework, DP is very suitable to deal with nonlinear discrete dynamic systems. The 4D waypoint representation of the flight trajectory is similar to the discretization by a grid system; thus DP is a natural method to deal with the 4D flight trajectory optimization. However, the computational time and space complexity demanded by the DP is enormous due to the immense number of grid points required to find the optimum, which prevents the use of the DP in many practical high dimension problems. On the other hand, the IDP has shown potentials to deal successfully with high dimension optimal control problems even with a few numbers of grid points at each stage, which reduces the computational effort over the traditional DP approach. Although the IDP has been applied successfully in chemical engineering problems, IDP is yet to be validated in 4D flight trajectory optimization problems. In this paper, the IDP has been successfully used to generate minimum length 4D optimal trajectory avoiding any obstacle in its path, such as a no-fly zone or residential areas when flying in low altitude to reduce noise pollution.

Keywords: 4D waypoint navigation, iterative dynamic programming, obstacle avoidance, trajectory optimization

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Authors: M. Dezvarei, S. Morovati

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In recent years, increasing usage of electrical energy provides a widespread field for investigating new methods to produce clean electricity with high reliability and cost management. Fuel cells are new clean generations to make electricity and thermal energy together with high performance and no environmental pollution. According to the expansion of fuel cell usage in different industrial networks, the identification and optimization of its parameters is really significant. This paper presents optimization of a proton exchange membrane fuel cell (PEMFC) parameters based on modified particle swarm optimization with real valued mutation (RVM) and clonal algorithms. Mathematical equations of this type of fuel cell are presented as the main model structure in the optimization process. Optimized parameters based on clonal and RVM algorithms are compared with the desired values in the presence and absence of measurement noise. This paper shows that these methods can improve the performance of traditional optimization methods. Simulation results are employed to analyze and compare the performance of these methodologies in order to optimize the proton exchange membrane fuel cell parameters.

Keywords: clonal algorithm, proton exchange membrane fuel cell (PEMFC), particle swarm optimization (PSO), real-valued mutation (RVM)

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Authors: Ernesto Linan, Linda Cruz, Lucero Becerra

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In this paper, a new hybridized algorithm based on Chemical Reaction Optimization and Simulated Annealing is proposed to solve the alignment sequence Problem. The Chemical Reaction Optimization is a population-based meta-heuristic algorithm based on the principles of a chemical reaction. Simulated Annealing is applied to solve a large number of combinatorial optimization problems of general-purpose. In this paper, we propose hybridization between Chemical Reaction Optimization algorithm and Simulated Annealing in order to solve the Sequence Alignment Problem. An initial population of molecules is defined at beginning of the proposed algorithm, where each molecule represents a sequence alignment problem. In order to simulate inter-molecule collisions, the process of Chemical Reaction is placed inside the Metropolis Cycle at certain values of temperature. Inside this cycle, change of molecules is done due to collisions; some molecules are accepted by applying Boltzmann probability. The results with the hybrid scheme are better than the results obtained separately.

Keywords: chemical reaction optimization, sequence alignment problem, simulated annealing algorithm, metaheuristics

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Authors: Khaled M. El Naggar

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This paper introduces a digital method for fault section identification in transmission lines. The method uses digital set of the measured short circuit current to locate faults in electrical power systems. The digitized current is used to construct a set of overdetermined system of equations. The problem is then constructed and solved using the proposed digital optimization technique to find the fault distance. The proposed optimization methodology is an application of simulated annealing optimization technique. The method is tested using practical case study to evaluate the proposed method. The accurate results obtained show that the algorithm can be used as a powerful tool in the area of power system protection.

Keywords: optimization, estimation, faults, measurement, high voltage, simulated annealing

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