Search results for: protocol optimization

Authors: Brahim Berbaoui

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In this paper, a new particle swarm optimization (PSO) based method is proposed for the implantation of optimal harmonic power flow in power systems. In this algorithm approach, proportional integral controller for reference compensating currents of active power filter is performed in order to minimize the total harmonic distortion (THD). The simulation results show that the new control method using PSO approach is not only easy to be implanted, but also very effective in reducing the unwanted harmonics and compensating reactive power. The studies carried out have been accomplished using the MATLAB Simulink Power System Toolbox.

Keywords: shunt active power filter, power quality, current control, proportional integral controller, particle swarm optimization

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Authors: Chungkuk Jin, Moo-Hyun Kim, HeonYong Kang

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A surface riding (SR) wave energy converter (WEC) is designed and its feasibility and performance are numerically simulated by the author-developed floater-mooring-magnet-electromagnetics fully-coupled dynamic analysis computer program. The biggest advantage of the SR-WEC is that the performance is equally effective even in low sea states and its structural robustness is greatly improved by simply riding along the wave surface compared to other existing WECs. By the numerical simulations and actuator testing, it is clearly demonstrated that the concept works and through the optimization process, its efficiency can be improved.

Keywords: computer simulation, electromagnetics fully-coupled dynamics, floater-mooring-magnet, optimization, performance evaluation, surface riding, WEC

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Authors: Deepak K. Gupta, T. R. Ravindran

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Holographic Optical Tweezers (HOTs) in general use iterative algorithms such as weighted Gerchberg-Saxton (WGS) to generate multiple traps, which produce traps with 99% uniformity theoretically. But in experiments, it is the phase response of the spatial light modulator (SLM) which ultimately determines the efficiency, uniformity, and quality of the trap spots. In general, SLMs show a nonlinear phase response behavior, and they may even have asymmetric phase modulation depth before and after π. This affects the resolution with which the gray levels are addressed before and after π, leading to a degraded trap performance. We present a method to optimize the SLM for a linear phase response behavior along with a symmetric phase modulation depth around π. Further, we optimize the SLM for its varying phase response over different spatial regions by optimizing the brightness/contrast and gamma of the hologram in different subsections. We show the effect of the optimization on an array of trap spots resulting in improved efficiency and uniformity. We also calculate the spot sharpness metric and trap performance metric and show a tightly focused spot with reduced aberration. The trap performance is compared by calculating the trap stiffness of a trapped particle in a given trap spot before and after aberration correction. The trap stiffness is found to improve by 200% after the optimization.

Keywords: spatial light modulator, optical trapping, aberration, phase modulation

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Authors: Seyedmilad Kazemisangdehi, Seyedmehdi Kazemisangdehi

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Flux switching permanent magnet machines are considered for wide range of applications because of their outstanding merits including high torque/power densities, high efficiency, simple and robust rotor structure. Therefore, several topologies have been proposed like the PM exited flux switching machine, hybrid excited flux switching type, and so on. Recently, a novel laminated segmented rotor flux switching permanent magnet machine was introduced. It features flux barriers on rotor structure to enhance the performances of machine including torque ripple reduction and also torque and efficiency improvements at the same time. This is while, the design of barriers was not optimized by the authors. Therefore, in this paper three coefficients regarding the position of the barriers are considered for optimization. The effect of each coefficient on the performance of this machine is investigated by finite element method and finally an optimized design of flux barriers based on these three coefficients is proposed from different points of view including electromagnetic torque maximization and cogging torque/torque ripple minimization. At optimum design from maximum developed torque aspect, this machine generates 0.65 Nm torque higher than that of the not-optimized design with an almost 0.4 % improvement in efficiency.

Keywords: finite element analysis, FSPM, laminated segmented rotor flux switching permanent magnet machine, optimization

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Authors: M. M. Othman, Walid El-Khattam, Y. G. Hegazy, A. Y. Abdelaziz

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This paper presents a method for finding the optimal location and capacity of dispatchable DGs connected to the distribution feeders for optimal planning for a specified power loss without violating the system practical constraints. The distributed generation units in the proposed algorithm is modeled as voltage controlled node with the flexibility to be converted to constant power node in case of reactive power limit violation. The proposed algorithm is implemented in MATLAB and tested on the IEEE 37-nodes feeder. The results that are validated by comparing it with results obtained from other competing methods show the effectiveness, accuracy and speed of the proposed method.

Keywords: distributed generators, firefly technique, optimization, power loss

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Authors: Tarek Aboueldahab, Amin Mohamed Nassar

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Wind energy is a fluctuating energy source unlike conventional power plants, thus, it is necessary to accurately predict short term wind speed to integrate wind energy in the electricity supply structure. To do so, we present a hybrid artificial intelligence model of short term wind speed prediction based on passive aggregation of the particle swarm optimization and neural networks. As a result, improvement of the prediction accuracy is obviously obtained compared to the standard artificial intelligence method.

Keywords: artificial intelligence, neural networks, particle swarm optimization, passive aggregation, wind speed prediction

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Authors: Adeyemi Isaac Sanusi, Gueguim E. B. Kana

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Nanoparticles have received attention of the scientific community due to their biotechnological potentials. They exhibit advantageous size, shape and concentration-dependent catalytic, stabilizing, immunoassays and immobilization properties. This study investigates the impact of metallic oxide nanoparticles (NPs) on ethanol production by Saccharomyces cerevisiae BY4743. Nine different nanoparticles were synthesized using precipitation method and microwave treatment. The nanoparticles synthesized were characterized by Fourier Transform Infra-Red spectroscopy (FTIR), scanning electron microscopy (SEM) and transmission electron microscopy (TEM). Fermentation processes were carried out at varied NPs concentrations (0 – 0.08 wt%). Highest ethanol concentrations were achieved after 24 h using Cobalt NPs (5.07 g/l), Copper NPs (4.86 g/l) and Manganese NPs (4.74 g/l) at 0.01 wt% NPs concentrations, which represent 13%, 8.7% and 5.4% increase respectively over the control (4.47 g/l). The lowest ethanol concentration (0.17 g/l) was obtained when 0.08 wt% of Silver NPs was used. And lower ethanol concentrations were observed at higher NPs concentration. Ethanol concentration decrease after 24 h for all the processes. In all set up with NPs, the pH was observed to be stable and the stability was directly proportional to nanoparticles concentrations. These findings suggest that the presence of some of the NPs in the bioprocesses has catalytic and pH stabilizing potential. Ethanol production by Saccharomyces cerevisiae BY4743 was enhanced in the presence of Cobalt NPs, Copper NPs and Manganese NPs. Optimization study using response surface methodology (RSM) will further elucidate the impact of these nanoparticles on bioethanol production.

Keywords: agitation, bioethanol, nanoparticles concentration, optimization, pH value

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Authors: M. Moradi Dalini, M. R. Talebi

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This research revolves around a technical method according to combines econometric and multiobjective programming to select and obtain optimal solutions to management problems. It is taken for a generation that; it is important to analyze which combination of values of the explanatory variables -in an econometric method- would point to the simultaneous achievement of the best values of the response variables. In this case, if a certain degree of conflict is viewed among the response variables, we suggest a multiobjective method in order to the results obtained from a regression analysis. In fact, with the use of a multiobjective method, we will have the best decision about the conflicting relationship between the response variables and the optimal solution. The combined multiobjective programming and econometrics benefit is an assessment of a balanced “optimal” situation among them because a find of information can hardly be extracted just by econometric techniques.

Keywords: econometrics, multiobjective optimization, management problem, optimization

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Authors: Elisenda Camprecios, Alicia Macarrila, Montse Albiol, Neus Garriga Garriga

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The loss of a child during pregnancy, or shortly after birth, is not a common occurrence, but it is a prevalent fact in our society. When this loss happens, life and death walk together. The grief that parents experience following a perinatal loss is a devastating experience. Professionals are aware that the quality of care offered during this first period is crucial to support the families experiencing a perinatal loss and meet their needs. However, it is not always easy for the health care professionals to know what to say and what to do in these difficult circumstances. Given the complexity of the Health, painful process that a family must face when is affected by such loss, we believe that the creation of a protocol that pays special attention to the emotional needs of those couples can be a very valuable tool for the professionals. The short documentary named ‘When the illusion vanished’ was created as part of the material of this protocol, which focuses on the emotional needs of the families who have suffered a perinatal loss. This video is designed to see what impact has a perinatal death and to raise awareness among professionals working in this field. The methodology is based on interviews with couples who have experienced perinatal death and to professionals who accompany families suffering from perinatal loss. The use of sensitive and empathized words, being encouraged to express feelings, respect the time, appropriate training for the professionals are some of the issues reflected in this documentary. We believe that this video has contributed to help health care professionals to empathize and understand the need to be able to accompany these families with the appropriate care, respectful, empathetic attitude and professionalism so that they can start the path to a ‘healthy’ mourning.

Keywords: neonatal loss, midwifery, perinatal bereavement, perinatal loss

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Authors: S. Mohamed, D. Gonzalez, C. Sayada, P. Halfon

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Drug resistance mutations are routinely detected using standard Sanger sequencing, which does not detect minor variants with a frequency below 20%. The impact of detecting minor variants generated by ultra-deep sequencing (UDS) on HIV drug-resistance (DR) interpretations has not yet been studied. Fifty HIV-1 patients who experienced virological failure were included in this retrospective study. The HIV-1 UDS protocol allowed the detection and quantification of HIV-1 protease and reverse transcriptase variants related to genotypes A, B, C, E, F, and G. DeepChek®-HIV simplified DR interpretation software was used to compare Sanger sequencing and UDS. The total time required for the UDS protocol was found to be approximately three times longer than Sanger sequencing with equivalent reagent costs. UDS detected all of the mutations found by population sequencing and identified additional resistance variants in all patients. An analysis of DR revealed a total of 643 and 224 clinically relevant mutations by UDS and Sanger sequencing, respectively. Three resistance mutations with > 20% prevalence were detected solely by UDS: A98S (23%), E138A (21%) and V179I (25%). A significant difference in the DR interpretations for 19 antiretroviral drugs was observed between the UDS and Sanger sequencing methods. Y181C and T215Y were the most frequent mutations associated with interpretation differences. A combination of UDS and DeepChek® software for the interpretation of DR results would help clinicians provide suitable treatments. A cut-off of 1% allowed a better characterisation of the viral population by identifying additional resistance mutations and improving the DR interpretation.

Keywords: HIV-1, ultra-deep sequencing, Sanger sequencing, drug resistance

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Authors: E. Karacabey, Ş. G. Özçelik, M. S. Turan, C. Baltacıoğlu, E. Küçüköner

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Changes in textural properties of any food material during processing is significant for further consumer’s evaluation and directly affects their decisions. Thus any food material should be considered in terms of textural properties after any process. In the present study zucchini slices were partially predried to control and reduce the product’s final oil content. A conventional oven was used for partially dehydration of zucchini slices. Following frying was carried in an industrial fryer having temperature controller. This study was based on the effect of this predrying process on textural properties of fried zucchini slices. Texture profile analysis was performed. Hardness, elasticity, chewiness, cohesiveness were studied texture parameters of fried zucchini slices. Temperature and weight loss were monitored parameters of predrying process, whereas, in frying, oil temperature and process time were controlled. Optimization of two successive processes was done by response surface methodology being one of the common used statistical process optimization tools. Models developed for each texture parameters displayed high success to predict their values as a function of studied processes’ conditions. Process optimization was performed according to target values for each property determined for directly fried zucchini slices taking the highest score from sensory evaluation. Results indicated that textural properties of predried and then fried zucchini slices could be controlled by well-established equations. This is thought to be significant for fried stuff related food industry, where controlling of sensorial properties are crucial to lead consumer’s perception and texture related ones are leaders. This project (113R015) has been supported by TUBITAK.

Keywords: optimization, response surface methodology, texture profile analysis, conventional oven, modelling

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Authors: Nicholas Burica, Nina Selak

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The ADHCAT (Automated Distribution Hosting Capacity Assessment Tool) was designed to run Hosting Capacity Analysis on the ComEd system via a stochastic DER (Distributed Energy Resource) placement on multiple power flow simulations against a set of violation criteria. The violation criteria in the initial version of the tool captured a limited amount of issues that individual departments design against for DER interconnections. Enhancements were made to the tool to further align with individual department violation and operation criteria, as well as the addition of new modules for use for future load profile analysis. A reporting engine was created for future analytical use based on the simulations and observations in the tool.

Keywords: distributed energy resources, hosting capacity, interconnect, voltage optimization

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Authors: K. Aravinth, C. T. Vignesh

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The usage of pulse tube cryocoolers is significantly increased mainly due to the advantage of the absence of moving parts. The underlying idea of this project is to optimize the design of pulse tube, regenerator, a resonator in cryocooler and analyzing the thermo-acoustic oscillations with respect to the design parameters. Computational Fluid Dynamic (CFD) model with time-dependent validation is done to predict its performance. The continuity, momentum, and energy equations are solved for various porous media regions. The effect of changing the geometries and orientation will be validated and investigated in performance. The pressure, temperature and velocity fields in the regenerator and pulse tube are evaluated. This optimized design performance results will be compared with the existing pulse tube cryocooler design. The sinusoidal behavior of cryocooler in acoustic streaming patterns in pulse tube cryocooler will also be evaluated.

Keywords: acoustics, cryogenics, design, optimization

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Authors: Sanjay Kumar Parjapati, Ajai Jain

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This paper presents optimization of makespan for ‘n’ jobs and ‘m’ machines flexible job shop scheduling problem with sequence dependent setup time using genetic algorithm (GA) approach. A restart scheme has also been applied to prevent the premature convergence. Two case studies are taken into consideration. Results are obtained by considering crossover probability (pc = 0.85) and mutation probability (pm = 0.15). Five simulation runs for each case study are taken and minimum value among them is taken as optimal makespan. Results indicate that optimal makespan can be achieved with more than one sequence of jobs in a production order.

Keywords: flexible job shop, genetic algorithm, makespan, sequence dependent setup times

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Authors: Hugo Reis, Isabel Rabiais

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The main purpose of the present study is to understand the nurse’s responsibility in preventing the septic shock in an oncological patient with febrile neutropenia submitted to chemotherapy. In order to do it, an integrative review of literature has been conducted. In the research done in many databases, it was concluded that only 7 out of 5202 articles compiled the entire inclusion standard present in the strict protocol of research, being this made up by all different methodologies. On the research done in the 7 articles it has resulted 8 text macro-units associated to different nursing interventions: ‘Health Education’; ‘Prophylactic Therapy Administration’; ‘Scales Utilization’; ‘Patient Evaluation’; ‘Environment Control’; ‘Performance of Diagnostic Auxiliary Exams’; ‘Protocol Enforcement/Procedure Guidelines’; ‘Antibiotic Therapy Administration’. Concerning the prevalence/result’s division there can be identified many conclusions: the macro-units ‘Patient Evaluation’, ‘Performance of Diagnostic Auxiliary Exams’, and ‘Antibiotic Therapy Administration’ present themselves to be the most prevalent in the research – 6 in 7 occurrences (approximately 85.7%). Next, the macro-unit ‘Protocol Enforcement/Procedure Guidelines’ presents itself as an important expression unit – being part of 5 out of the 7 analyzed studies (approximately 71.4%). The macro-unit ‘Health Education’, seems to be in the same way, an important expression unit – 4 out of the 7 (or approximately 57%). The macro-unit ‘Scales Utilization’, represents a minor part in the research done – it’s in only 2 out of the 7 cases (approximately 28.6%). On the other hand, the macro-units ‘Prophylactic Therapy Administration’ and ‘Environment Control’ are the two categories with fewer results in the research - 1 out of the 7 cases, the same as approximately 14.3% of the research results. Every research done to the macro-unit ‘Antibiotic Therapy Administration’ agreed to refer that the intervention should be strictly done, in a period of time less than one hour after diagnosing the fever, with the purpose of controlling the quick spread of infection – minimizing its seriousness. Identifying these interventions contributes, concluding that, to adopt strategies in order to prevent the phenomenon that represents a daily scenario responsible for the cost´s increase in health institutions, being at the same time responsible for the high morbidity rates and mortality increase associated with this specific group of patients.

Keywords: febrile neutropenia, oncology nursing, patient, septic shock

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Authors: M. M. Nor, H. I. Sheikh, M. F. H. Hassan, S. Mokhtar, A. Suganthi, A. Fadhlina

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Black grass jelly (BGJ) is a popular black jelly used in preparing various drinks and desserts. Food industries often use preservatives to maintain the physicochemical properties of foods, such as color and texture. These preservatives (e.g., phosphoric acid) are linked with deleterious health effects such as kidney disease. Using gelling agents, carrageenan, and gelatin to make BGJ could improve its physiochemical and textural properties. This study was designed to optimize BGJ-selected physicochemical and textural properties using carrageenan and gelatin. Various black grass jelly formulations (BGJF) were designed using an I-optimal mixture design in Design Expert® software. Data from commercial BGJ were used as a reference during the optimization process. The combination of carrageenan and gelatin added to the formulations was up to 14.38g (~5%), respectively. The results showed that adding 2.5g carrageenan and 2.5g gelatin at approximately 5g (~5%) effectively maintained most of the physiochemical properties with an overall desirability function of 0.81. This formulation was selected as the optimum black grass jelly formulation (OBGJF). The leaching properties and floating duration were measured on the OBGJF and commercial grass jelly for 20 min and 40 min, respectively. The results indicated that OBGJF showed significantly (p<0.0001) lower leaching rate and floating time (p<0.05). Hence, further optimization is needed to increase the floating duration of carrageenan and gelatin-based BGJ.

Keywords: cincau, Mesona chinensis, black grass jelly, carrageenan, gelatin

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Authors: Pin-Ling Yin, Dung-Ying Lin

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Satellites play an important role in our daily lives, from monitoring the Earth's environment and providing real-time disaster imagery to predicting extreme weather events. As technology advances and demands increase, the tasks undertaken by satellites have become increasingly complex, with more stringent resource management requirements. A common challenge in satellite mission scheduling is the limited availability of resources, including onboard memory, ground station accessibility, and satellite power. In this context, efficiently scheduling and managing the increasingly complex satellite missions under constrained resources has become a critical issue that needs to be addressed. The core of Satellite Onboard Activity Planning (SOAP) lies in optimizing the scheduling of the received tasks, arranging them on a timeline to form an executable onboard mission plan. This study aims to develop an optimization model that considers the various constraints involved in satellite mission scheduling, such as the non-overlapping execution periods for certain types of tasks, the requirement that tasks must fall within the contact range of specified types of ground stations during their execution, onboard memory capacity limits, and the collaborative constraints between different types of tasks. Specifically, this research constructs a mixed-integer programming mathematical model and solves it with a commercial optimization package. Simultaneously, as the problem size increases, the problem becomes more difficult to solve. Therefore, in this study, a heuristic algorithm has been developed to address the challenges of using commercial optimization package as the scale increases. The goal is to effectively plan satellite missions, maximizing the total number of executable tasks while considering task priorities and ensuring that tasks can be completed as early as possible without violating feasibility constraints. To verify the feasibility and effectiveness of the algorithm, test instances of various sizes were generated, and the results were validated through feedback from on-site users and compared against solutions obtained from a commercial optimization package. Numerical results show that the algorithm performs well under various scenarios, consistently meeting user requirements. The satellite mission scheduling algorithm proposed in this study can be flexibly extended to different types of satellite mission demands, achieving optimal resource allocation and enhancing the efficiency and effectiveness of satellite mission execution.

Keywords: mixed-integer programming, meta-heuristics, optimization, resource management, satellite mission scheduling

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Authors: Jiin Jeong, Taekwang Kim, Kwang Ryel Ryu

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The target microgrid in this paper is isolated from the large central power system and is assumed to consist of wind generators, photovoltaic power generators, an energy storage system (ESS), a diesel power generator, the community load, and a dump load. The operation of such a microgrid can be hazardous because of the uncertain prediction of power supply and demand and especially due to the high fluctuation of the output from the wind generators. In this paper, we propose an iterative replanning method for determining the appropriate level of diesel generation and the charging/discharging cycles of the ESS for the upcoming one-hour horizon. To cope with the uncertainty of the estimation of supply and demand, the one-hour plan is built repeatedly in the regular interval of one minute by rolling the one-hour horizon. Since the plan should be built with a sufficiently large safe margin to avoid any possible black-out, some energy waste through the dump load is inevitable. In our approach, the level of safe margin is optimized through learning from the past experience. The simulation experiments show that our method combined with the margin optimization can reduce the dump load compared to the method without such optimization.

Keywords: microgrid, operation planning, power efficiency optimization, supply and demand prediction

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Authors: B. Marasović, S. Pivac, S. V. Vukasović

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Constructing a portfolio of investments is one of the most significant financial decisions facing individuals and institutions. In accordance with the modern portfolio theory maximization of return at minimal risk should be the investment goal of any successful investor. In addition, the costs incurred when setting up a new portfolio or rebalancing an existing portfolio must be included in any realistic analysis. In this paper rebalancing an investment portfolio in the presence of transaction costs on the Croatian capital market is analyzed. The model applied in the paper is an extension of the standard portfolio mean-variance optimization model in which transaction costs are incurred to rebalance an investment portfolio. This model allows different costs for different securities, and different costs for buying and selling. In order to find efficient portfolio, using this model, first, the solution of quadratic programming problem of similar size to the Markowitz model, and then the solution of a linear programming problem have to be found. Furthermore, in the paper the impact of transaction costs on the efficient frontier is investigated. Moreover, it is shown that global minimum variance portfolio on the efficient frontier always has the same level of the risk regardless of the amount of transaction costs. Although efficient frontier position depends of both transaction costs amount and initial portfolio it can be concluded that extreme right portfolio on the efficient frontier always contains only one stock with the highest expected return and the highest risk.

Keywords: Croatian capital market, Markowitz model, fractional quadratic programming, portfolio optimization, transaction costs

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Authors: Xhaklina Cani, Ilirjan Malollari, Ismet Beqiraj, Lorina Lici

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Oil characterization is an essential step in the design, simulation, and optimization of refining facilities. To achieve optimal crude selection and processing decisions, a refiner must have exact information refer to crude oil quality. This includes crude oil TBP-curve as the main data for correct operation of refinery crude oil atmospheric distillation plants. Crude oil is typically characterized based on a distillation assay. This procedure is reasonably well-defined and is based on the representation of the mixture of actual components that boil within a boiling point interval by hypothetical components that boil at the average boiling temperature of the interval. The crude oil assay typically includes TBP distillation according to ASTM D-2892, which can characterize this part of oil that boils up to 400 C atmospheric equivalent boiling point. To model the yield curves obtained by physical distillation is necessary to compare the differences between the modelling and the experimental data. Most commercial use a different number of components and pseudo-components to represent crude oil. Laboratory tests include distillations, vapor pressures, flash points, pour points, cetane numbers, octane numbers, densities, and viscosities. The aim of the study is the drawing of true boiling curves for different crude oil resources in Albania and to compare the differences between the modeling and the experimental data for optimal characterization of crude oil.

Keywords: TBP distillation curves, crude oil, optimization, simulation

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Authors: Jan Busch, Peter Nyhuis

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Considering the challenges of short product life cycles and growing variant diversity, cost minimization and manufacturing flexibility increasingly gain importance to maintain a competitive edge in today’s global and dynamic markets. In this context, an aerodynamic part feeding system for high-speed industrial assembly applications has been developed at the Institute of Production Systems and Logistics (IFA), Leibniz Universitaet Hannover. The aerodynamic part feeding system outperforms conventional systems with respect to its process safety, reliability, and operating speed. In this paper, a multi-objective optimisation of the aerodynamic feeding system regarding the orientation rate, the feeding velocity and the required nozzle pressure is presented.

Keywords: aerodynamic feeding system, genetic algorithm, multi-objective optimization, workpiece orientation

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Authors: Pavel Shcherban, Viktoria Ivanova, Alexander Neprokin, Vladislav Golovanov

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Currently, LLC «Lukoil-Kaliningradmorneft» is implementing a comprehensive program for the development of offshore fields of the Kaliningrad region. This is largely associated with the depletion of the resource base of land in the region, as well as the positive results of geological investigation surrounding the Baltic Sea area and the data on the volume of hydrocarbon recovery from a single offshore field are working on the Kaliningrad region – D-6 «Kravtsovskoye».The article analyzes the main stages of the LLC «Lukoil-Kaliningradmorneft»’s development program for the development of the hydrocarbon resources of the region's shelf and suggests an optimization algorithm that allows managing a multi-criteria process of development of shelf deposits. The algorithm is formed on the basis of the problem of sequential decision making, which is a section of dynamic programming. Application of the algorithm during the consolidation of the initial data, the elaboration of project documentation, the further exploration and development of offshore fields will allow to optimize the complex of technical and technological solutions and increase the economic efficiency of the field development project implemented by LLC «Lukoil-Kaliningradmorneft».

Keywords: offshore fields of hydrocarbons of the Baltic Sea, development of offshore oil and gas fields, optimization of the field development scheme, solution of multicriteria tasks in oil and gas complex, quality management in oil and gas complex

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Authors: Francesca Schiavello

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This work aims to create a hybrid algorithm, combining Quantum Approximate Optimization Algorithm (QAOA) with an Evolutionary Algorithm (EA) in the place of traditional gradient based optimization processes. QAOA’s were first introduced in 2014, where, at the time, their algorithm performed better than the traditional best known classical algorithm for Max-cut graphs. Whilst classical algorithms have improved since then and have returned to being faster and more efficient, this was a huge milestone for quantum computing, and their work is often used as a benchmarking tool and a foundational tool to explore variants of QAOA’s. This, alongside with other famous algorithms like Grover’s or Shor’s, highlights to the world the potential that quantum computing holds. It also presents the reality of a real quantum advantage where, if the hardware continues to improve, this could constitute a revolutionary era. Given that the hardware is not there yet, many scientists are working on the software side of things in the hopes of future progress. Some of the major limitations holding back quantum computing are the quality of qubits and the noisy interference they generate in creating solutions, the barren plateaus that effectively hinder the optimization search in the latent space, and the availability of number of qubits limiting the scale of the problem that can be solved. These three issues are intertwined and are part of the motivation for using EAs in this work. Firstly, EAs are not based on gradient or linear optimization methods for the search in the latent space, and because of their freedom from gradients, they should suffer less from barren plateaus. Secondly, given that this algorithm performs a search in the solution space through a population of solutions, it can also be parallelized to speed up the search and optimization problem. The evaluation of the cost function, like in many other algorithms, is notoriously slow, and the ability to parallelize it can drastically improve the competitiveness of QAOA’s with respect to purely classical algorithms. Thirdly, because of the nature and structure of EA’s, solutions can be carried forward in time, making them more robust to noise and uncertainty. Preliminary results show that the EA algorithm attached to QAOA can perform on par with the traditional QAOA with a Cobyla optimizer, which is a linear based method, and in some instances, it can even create a better Max-Cut. Whilst the final objective of the work is to create an algorithm that can consistently beat the original QAOA, or its variants, due to either speedups or quality of the solution, this initial result is promising and show the potential of EAs in this field. Further tests need to be performed on an array of different graphs with the parallelization aspect of the work commencing in October 2023 and tests on real hardware scheduled for early 2024.

Keywords: evolutionary algorithm, max cut, parallel simulation, quantum optimization

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Authors: Reza Babajanivalashedi, Stefania Lo Feudo, Jean-Luc Dion

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Liquid sloshing is a crucial problem for the dynamic of moving containers in the packaging industries. Sloshing issues have been so far mainly modeled within the framework of fluid dynamics or by using equivalent mechanical models with different kinds of movements and shapes of containers. Nevertheless, these approaches do not allow to determinate the shape of the free surface of the liquid in case of the irregular shape of the moving containers, so that experimental measurements may be required. If there is too much slosh in the moving tank, the liquid can be splashed out on the packages. So, the free surface oscillation must be controlled/reduced to eliminate the splashing. The purpose of this research is to propose an optimization algorithm for finding an optimum command law to reduce surface elevation. In the first step, the free surface of the liquid is simulated based on the separation variable and weak formulation models. Then Genetic and Gradient algorithms are developed for finding the optimum command law. The optimum command law is compared with existing command laws, and the results show that there is a significant difference in surface oscillation between optimum and existing command laws. This algorithm is applicable for different varieties of bottles in case of using the camera for detecting the liquid elevation, and it can produce new command laws for different kinds of tanks to reduce the surface oscillation and remove the splashing phenomenon.

Keywords: sloshing phenomenon, separation variables, weak formulation, optimization algorithm, command law

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Authors: Isabel Moscol, Carlos J. Díaz, Ciro Rodríguez

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Hip replacement becomes necessary when a person suffers severe pain or considerable functional limitations and the best option to enhance their quality of life is through the replacement of the damaged joint. One of the main components in femoral prostheses is the stem which distributes the loads from the joint to the proximal femur. To preserve more bone stock and avoid weakening of the diaphysis, a short starting stem was selected, generated from the intramedullary morphology of the patient's femur. It ensures the implantability of the design and leads to geometric delimitation for personalized optimization with machine learning (ML) and metaheuristic algorithms. The present study attempts to design a cementless short stem to make the strain deviation before and after implantation close to zero, promoting its fixation and durability. Regression models developed to estimate the percentage change of maximum principal stresses were used as objective optimization functions by the metaheuristic algorithm. The latter evaluated different geometries of the short stem with the modification of certain parameters in oblique sections from the osteotomy plane. The optimized geometry reached a global stress shielding (SS) of 18.37% with a determination factor (R²) of 0.667. The predicted results favour implantability integration in the short stem optimization to effectively reduce SS in the proximal femur.

Keywords: machine learning techniques, metaheuristic algorithms, short-stem design, stress shielding, hip replacement

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Authors: Om Prakash Bharti, Aanchal Verma, R. K. Saket

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The Doubly-Fed Induction Generator (DFIG) is suggested for Wind Energy Conversion System (WECS) to extract wind power. DFIG is preferably employed due to its robustness towards variable wind and rotor speed. DFIG has the adaptable property because the system parameters are smoothly dealt with, including real power, reactive power, DC-link voltage, and the transient and dynamic responses, which are needed to analyze constantly. The analysis becomes more prominent during any unusual condition in the electrical power system. Hence, the study and improvement in the system parameters and transient response performance of DFIG are required to be accomplished using some controlling techniques. For fulfilling the task, the present work implements and compares the optimization methods for the design of the DFIG controller for WECS. The bio-inspired optimization techniques are applied to get the optimal controller design parameters for DFIG-based WECS. The optimized DFIG controllers are then used to retrieve the transient response performance of the six-order DFIG model with a step input. The results using MATLAB/Simulink show the betterment of the Firefly algorithm (FFA) over other control techniques when compared with the other controller design methods.

Keywords: doubly-fed induction generator, wind turbine, wind energy conversion system, induction generator, transfer function, proportional, integral, derivatives

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Authors: Daniyar Seitenov, Nazim Mir-Nasiri

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Optimization of horizontal axis semi-exposed wind turbine has been performed using a shield protection that automatically protects the generator shaft at extreme wind speeds from over speeding, mechanical damage and continues generating electricity during the high wind speed conditions. A semi-exposed to wind generator has been designed and its structure has been described in this paper. The simplified point-force dynamic load model on the blades has been derived for normal and extreme wind conditions with and without shield involvement. Numerical simulation has been conducted at different values of wind speed to study the efficiency of shield application. The obtained results show that the maximum power generated by the wind turbine with shield does not exceed approximately the rated value of the generator, where shield serves as an automatic break for extreme wind speed values of 15 m/sec and above. Meantime the wind turbine without shield produced a power that is much larger than the rated value. The optimized horizontal axis semi-exposed wind turbine with shield protection is suitable for low and medium power generation when installed on the roofs of high rise buildings for harvesting wind energy. Wind shield works automatically with no power consumption. The structure of the generator with the protection, math simulation of kinematics and dynamics of power generation has been described in details in this paper.

Keywords: renewable energy, wind turbine, wind turbine optimization, high wind speed

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Authors: Pankaj Chandna, Dinesh Kumar

Abstract:

The present work analyses different parameters of end milling to minimize the surface roughness for AISI D2 steel. D2 Steel is generally used for stamping or forming dies, punches, forming rolls, knives, slitters, shear blades, tools, scrap choppers, tyre shredders etc. Surface roughness is one of the main indices that determines the quality of machined products and is influenced by various cutting parameters. In machining operations, achieving desired surface quality by optimization of machining parameters, is a challenging job. In case of mating components the surface roughness become more essential and is influenced by the cutting parameters, because, these quality structures are highly correlated and are expected to be influenced directly or indirectly by the direct effect of process parameters or their interactive effects (i.e. on process environment). In this work, the effects of selected process parameters on surface roughness and subsequent setting of parameters with the levels have been accomplished by Taguchi’s parameter design approach. The experiments have been performed as per the combination of levels of different process parameters suggested by L9 orthogonal array. Experimental investigation of the end milling of AISI D2 steel with carbide tool by varying feed, speed and depth of cut and the surface roughness has been measured using surface roughness tester. Analyses of variance have been performed for mean and signal-to-noise ratio to estimate the contribution of the different process parameters on the process.

Keywords: D2 steel, orthogonal array, optimization, surface roughness, Taguchi methodology

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Authors: Balakumar Pitchai, Xiang Llan Ang, Sunil Prajapati, Varatharajan Rajavel, Sundram Karupiah, Mohd Baidi Bahari

Abstract:

The study examined the pretreatment and post-treatment effects of low-doses of fenofibrate and rosuvastatin in gentamicin-induced acute nephrotoxicity in rats. Gentamicin (100 mg/kg/day, i.p.) was administered to rats for 8 days. In the pretreatment protocol, low-dose fenofibrate (30 mg/kg/day, p.o.) or low-dose rosuvastatin (2 mg/kg/day, p.o.) treatments were started a day before the administration of gentamicin and continued for 8 days. In the post-treatment protocol, rats administered gentamicin were treated with low-dose fenofibrate (30 mg/kg/day, p.o.) or low-dose rosuvastatin (2 mg/kg/day, p.o.) for 6 days after the completion of 8 days protocol of gentamicin administration. Gentamicin-associated acute nephrotoxicity in rats was assessed in terms of biochemical analysis and renal histopathological studies. Gentamicin-administered rats showed marked renal functional changes as assessed in terms of a significant increase in serum creatinine and urea levels as compared to normal rats. The renal dysfunction noted in gentamicin administered rats was accompanied with elevated serum uric acid level as compared to normal rats while there was no significant change in lipid profile. Low-dose fenofibrate pretreatment in gentamicin-administered rats afforded a significant renal functional improvements and renoprotection while its post-treatment showed no significant renoprotection. On the other hand, pretreatment with low-dose rosuvastatin partially reduced gentamicin-induced increase in serum creatinine level, but its post-treatment did not afford renal functional improvements in gentamicin-administered rats. However, all pre and post-treatments with low-doses of fenofibrate or rosuvastatin significantly reduced the elevated serum uric acid concentration in gentamicin-administered rats. Renal histopathological analysis showed a discernible incidence of acute tubular necrosis in gentamicin-administered rats which were markedly reduced by low-dose fenofibrate or low-dose rosuvastatin pretreatments; but, not by their post-treatments. In conclusion, low-dose fenofibrate pretreatment considerably prevented gentamicin-induced acute tubular necrosis and renal functional abnormalities in rats while its post-treatment resulted in no significant renoprotective action. In spite of effective prevention of gentamicin-induced acute tubular necrosis, the pretreatment with low-dose rosuvastatin had only a partial and fractional protection on renal functional abnormalities. The post-treatment with low-dose rosuvastatin was ineffective in affording a renoprotection in gentamicin-administered rats.

Keywords: gentamicin-nephrotoxicity, low-dose fenofibrate, low-dose rosuvastatin, renoprotection

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Authors: Andy Ho

Abstract:

Breast cancer is a common cancer in Australia. Early diagnosis is crucial for improving patient outcomes, as later-stage detection correlates with poorer prognoses. While multiparametric MRI offers superior sensitivity in detecting invasive and high-grade breast cancers compared to conventional mammography, its extended scan duration and high costs limit widespread application. As a result, full protocol MRI screening is typically reserved for patients at elevated risk. Recent advancements in imaging technology have facilitated the development of Abbreviated MRI protocols, which dramatically reduce scan times (<10 minutes compared to >30 minutes for full protocol). The potential for Abbreviated MRI to offer a more time- and cost-efficient alternative has implications for improving patient accessibility, reducing appointment durations, and enhancing compliance—especially relevant for individuals requiring regular annual screening over several decades. The purpose of this study is to assess the diagnostic efficacy of Abbreviated MRI for breast cancer screening among high-risk patients at the Royal Prince Alfred Hospital (RPA). This study aims to determine the sensitivity, specificity, and inter-reader variability of Abbreviated MRI protocols when interpreted by subspecialty-trained Breast Radiologists. A systematic review of the RPA’s electronic Picture Archive and Communication System identified high-risk patients, defined by Australian ‘Medicare Benefits Schedule’ criteria, who underwent Breast MRI from 2021 to 2022. Eligible participants included asymptomatic patients under 50 years old and referred by the High-Risk Clinic due to a high-risk genetic profile or relevant familial history. The MRIs were anonymized, randomized, and interpreted by four Breast Radiologists, each independently completing standardized proforma evaluations. Radiological findings were compared against histopathology as the gold standard or follow-up imaging if biopsies were unavailable. Statistical metrics, including sensitivity, specificity, and inter-reader variability, were assessed. The Fleiss-Kappa analysis demonstrated a fair inter-reader agreement (kappa = 0.25; 95% CI: 0.19–0.32; p < 0.0001). The sensitivity for detecting malignancies was 0.72, with a specificity of 0.92. For benign lesions, sensitivity and specificity were 0.844 and 0.73, respectively. These findings underline the potential of Abbreviated MRI as a reliable screening tool for malignancies with significant specificity, though reduced sensitivity highlights the importance of robust radiologist training and consistent evaluation standards. Abbreviated MRI protocols exhibit promise as a viable screening option for high-risk patients, combining reduced scan times and acceptable diagnostic accuracy. Further work to refine interpretation practices and optimize training is essential to maximize the protocol’s utility in routine clinical screening and facilitate broader accessibility.

Keywords: abbreviated, breast, cancer, MRI

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