Optimization Approach Research Articles

Prediction intervals for carbon dioxide emissions in china by extreme learning machine ensemble based on particle swarm optimization

<p>The emission of carbon dioxide is the major cause of the greenhouse effect, which has a negative impact on human survival and sustainable economic development; therefore, it is very significant for discovering the underlying influential factors of carbon dioxide emissions. In this paper, an extreme learning machine ensemble based on particle swarm optimization approach(PSO-ELMEnsemble) are applied to predict the emission of carbon dioxide, which provide estimated values as well as the corresponding reliability. In addition, the particle swarm optimization approach is used to optimize the connection weights of extreme learning machine. The performance of the proposed PSO-ELMEnsemble is experimentally validated by carbon dioxide emissions data during the period 1978-2016 by using state-of-the-art comparative method, where the proposed approach outperforms the others in achieving the best trade-off between accuracy and simplicity.</p>

Granular Skeleton Optimisation and the Influence of the Cement Paste Content in Bio-Based Oyster Shell Mortar with 100% Aggregate Replacement

The purpose of this paper is to propose a methodology to optimise the granular skeleton assembly of cementitious materials containing non-spherical aggregates. The method is general and can be applied to any granular skeleton whatever the aggregate shape, size, or composition because it is simply based on the direct minimisation of the intergranular porosity to consequently increase the skeleton’s compactness. Based on an experimental design approach, this method was applied to and validated for bio-based oyster shell (OS) mortar with 100% aggregate replacement. First, the best combination of seven crushed oyster shell particle classes was determined and compared with a standardised sand skeleton (0/4 mm) and three other non-optimised OS gradings in terms of intergranular porosity. In particular, it is shown that simply mimicking a reference grading curve initially designed for spherical particles with non-spherical particles led to poor performances. Then, different mortars were cast with the standardised sand skeleton, the optimised OS grading, and the three other non-optimised OS gradings by keeping the water-to-cement ratio (0.5), the aggregate bulk volume, and the cement paste content constant. Mechanical tests in compression confirmed the higher performance of the optimised OS mortar, validating the global optimisation approach. However, the high elongation of the oyster shell aggregates led to high skeleton intergranular porosities—even after optimisation—and the cement paste content needed to be adapted. For a given granular skeleton and for a constant aggregate bulk volume, the increase of the cement paste content led to an increase of both the filling ratio and the mechanical properties (compressive and flexural strengths). Finally, it is shown that the proposed skeleton optimisation and a cement paste content adjustment allowed recovering good mechanical properties for an oyster shell mortar with 100% aggregate replacement, especially in flexural tension.

Research on Lighting Schemes for College Gymnasiums Based on Dynamic Light Environment Simulation

The purpose of this study is to explore and optimize natural lighting schemes for college gymnasiums through dynamic light environment simulation. The study used Daysim software, combined with Rhino & Grasshopper for modeling and parameter optimization, to evaluate different lighting schemes through a multi-objective optimization approach. The results show that the effective indoor illuminance of the top lighting scheme at DA300lx, UDI100-2000lx, aDGP(0.4), DA580lx, and UDI300-890lx are 91.50%, 88.44%, 90.58\%, 92.56%, and 52.89%, respectively, which show good lighting effects. The side lighting scheme also shows excellent lighting performance in different configurations. In addition, the side + top synergistic light harvesting scheme achieved efficient light environment utilization while ensuring visual comfort. This study suggests that the top and side synergistic lighting scheme can effectively enhance the natural lighting effect of the gymnasium. This study provides a scientific basis for the lighting design of college gymnasiums and is of great significance in guiding the actual engineering design.

Study on the Vertical Stability of Drilling Wellbore under Optimized Constraints

With the development of coal resource extraction and wellbore construction proceeding towards deeper depths, the stability of drilling wellbore structures has become increasingly severe, even posing a barrier to the use of drilling method technology in deep wellbore construction. To address this issue, this study raised an optimized constraints method involving pre-throwing cement slurry to the bottom before wellbore decent, altering bottom constraints. Firstly, the critical depth and instability criterion of this optimized method was derived by catastrophe theory. Subsequently, the role of single-factor and multi-factor sensitivity analyses on critical depth was discussed. The engineering effects of optimized constraint methods were contrasted and examined in several drilling projects. Finally, the characteristic values of real engineering were computed using numerical techniques and ABAQUS2020 software, and the efficacy of optimization approaches was examined and validated. The results revealed that the critical depth increased by 41.39 ± 5%. The influence factors described in order of the degree were the counterweight water height, the elastic modulus, the thickness of the wellbore, and the self-weight of the wellbore, sequentially. The conclusion on structural stability between the numerical calculation solution and theoretical calculation solution was completely the same. The optimized constraints method can effectively improve the stability of the wellbore structure.

Improving the manufacturing of 3D printed insoles through a combined experimental and topology optimization approach

This study integrates additive manufacturing and advanced engineering to produce lightweight, mechanically suitable insoles. The research combines experimental data and computational techniques to enhance the manufacturing process. Through mechanical testing and computational homogenization, an alternative infill pattern is identified, allowing for faster printing. Topology optimization, based on Finite Element analysis, determines an optimal material distribution for the forefoot. Validation analyses confirm the structural performance of the optimized shape. Thanks to this procedure, a time reduction up to 50% can be expected. This approach allows for an efficient and sustainable alternative for the production of insoles.

A Road Map to the Structural Optimization of a Type-C Composite UAV

The present paper investigates the design process and the dimensioning of a tailless type-C composite sandwich unmanned aerial vehicle (UAV). The objective is to investigate an innovative aircraft configuration which exceeds the standard approach of ribs and spars and replaces them with a sandwich structure for future unmanned aerial systems. The necessity of carbon fiber-reinforced materials arose due to the weight constraint of a Class C UAV, i.e., the whole vehicle must be under 25 kg, which limits the mass of the structure to 9 kg. The structural design of composite structures differs from the one of traditional isotropic structures. The number of holes should be limited, as drilling down the composite aerostructure would conclude to the generation of delaminations. In addition, the joints between sections with different thicknesses could lead to stress concentrations and disbands. Therefore, the present report is crucial for the continuance of the present project as it has contributed both to the structural design and assessment of the UAV. This work focusses on the computation of loads, the process of structural sizing through a multi-disciplinary optimization approach, and the simulation-based structural proof. Particular attention is paid to the specifically developed semi-analytical method for predicting the aero-elastic load. Based on the detailed finite element model of the global structure, the applicability of the minimum number of bolts as a major structural joining variant is proven. The design process from single components to the assembly of the overall aircraft results in the realization of the demonstrator structure.

Insights and future research directions from a bibliometric mapping of studies in stope layout optimisation

ABSTRACT Stope layout optimisation is an important sub-problem of the generic underground mining optimisation problem that contributes towards optimal ore extraction. It is a growing research area as some surface mines transition from open-pit to underground mining. Several researchers acknowledge the complexity of optimising underground mine layouts because exact methods are limited in generating three-dimensional optimal solutions, hence the growing use of metaheuristic approaches to solve the problem in three dimensions. This paper presents a PRISMA-based bibliometric mapping of stope layout optimisation approaches using R-Biblioshiny and VOSviewer software, their concomitant limitations, and suggests potential future research directions in stope layout optimisation.

Iterative optimisation in dynamic environments via local pursuit

We discuss an iterative optimal control approach in which a multi-agent group of control systems discovers locally optimal trajectories in environments with time-varying terrain geometry and moving, deforming obstacles. Works in literature have addressed only special cases of this problem with time-invariant terrain geometry. One such bio-inspired optimal control approach, applicable in static environments, is ‘local pursuit’, a method that iteratively solves partially-constrained final state problems by having agents follow one another, each agent moving optimally towards its predecessor. We show that if, instead, agents evolve in their own time-delayed ‘copy’ of the environment and act based on the most recent time history of their predecessors local neighbourhoods, then the original method can be extended to the dynamic environments described above. Furthermore, we discuss the computational complexity of our approach and demonstrate its effectiveness and computational advantages in a series of simulations.

Family Centered Care: The Perspective of Nurses in the Neonatal Intensive Care Unit of Tamale Teaching Hospital, Ghana: A Qualitative Exploration

Background: Family-Centered Care is a care approach in which healthcare professionals collaborate with the patient's family to plan and make decisions regarding the patient's treatment. Family-Centered Care is widely acknowledged and documented as the optimal care approach for neonatal practice. Despite the growing use of this method, there is a lack of research on the perspectives of healthcare professionals and carers regarding Family-Centered Care. The study aimed to evaluate the viewpoints of nurses regarding FCC in the newborn critical care unit at the Tamale Teaching Hospital.
 Methodology: The study utilised an exploratory descriptive design employing a qualitative technique, in which focus group talks were held among participants. The material was transcribed and processed via thematic and content analysis techniques.
 Findings: Approximately majority of the participants demonstrated awareness of the idea of Family-Centered Care, which they elaborated upon through two main themes namely provision of care for both the patient and their family, and Involvement of relatives in the care of the patient.
 Recommendations: Majority of participants expressed that Family-Centered Care was not practiced in their unit. Nevertheless, all participants unanimously concurred that the approach had the potential to yield positive results in terms of patient care outcomes.

Comparison of scrotal and inguinal orchiopexy for palpable undescended testis: a meta-analysis of randomized controlled trials.

Scrotal and inguinal orchiopexy are two commonly used surgical approaches for palpable undescended testis (UDT), each with distinct advantages. However, the optimal approach remains a matter of debate, warranting a comprehensive meta-analysis of randomized controlled trials (RCTs) to guide clinical decision-making. A comprehensive literature search was conducted, adhering to PRISMA guidelines, to select RCTs comparing scrotal and inguinal orchiopexy for palpable UDT. Eight RCTs were selected for meta-analysis. Outcome measures included operative time, hospitalization duration, total complications, wound infection or dehiscence, testicular atrophy or hypotrophy, and testicular re-ascent rate. The evaluation of the study's quality was conducted by utilizing the revised Cochrane risk-of-bias tool. Scrotal orchiopexy showed significantly shorter operative time compared to the inguinal approach (WMD: -15.06min; 95% CI: -21.04 to -9.08). However, there was no significant difference in hospitalization duration (WMD: - 0.72days; 95% CI: - 1.89-0.45), total complications (OR: 1.08; 95% CI: 0.70-1.66), wound infection or dehiscence (OR: 0.73; 95% CI: 0.27-1.99), testicular atrophy or hypotrophy (OR: 1.03; 95% CI: 0.38-2.78), and testicular re-ascent (OR: 1.43; 95% CI: 0.67-3.06) between the two approaches. A small proportion of cases (7.3%) required conversion from scrotal to inguinal orchiopexy due to specific anatomical challenges. Both scrotal and inguinal orchiopexy are safe and effective for palpable UDT, with comparable outcomes in terms of hospitalization and complications. Scrotal orchiopexy offers the advantage of shorter operative time. Clinicians can use this evidence to make informed decisions on the surgical approach for palpable UDT.

Optimal Energy Storage Configuration of Prosumers with Uncertain Photovoltaic in the Presence of Customized Pricing-Based Demand Response

Setting an acceptable pricing strategy to attract prosumers to participate in demand response and orderly configure energy storage is a critical topic for virtual power plants (VPPs) in improving sustainable development. Based on this, this paper proposes a two-layer iterative optimization to develop a customized pricing-based demand response for energy storage with uncertain photovoltaic (PV) for prosumers. In the upper layer, the VPP formulates a customized price consisting of a two-part electricity price, on-grid electricity price and auxiliary service price according to the load characteristics of prosumers, so as to make the power supply and demand of prosumers more controllable. In the lower layer, prosumers adjust their energy storage configurations and energy consumption behavior according to the price signal, considering the uncertainty of PV. The research shows that the proposed optimization approach can encourages prosumers to configure energy storage, and explore user-side flexibility resources. The full utilization of energy storage has increased the PV output of the prosumers by 10%, and its benefits have also increased by 7%.

Flexible development and evaluation of machine‐learning‐supported optimal control and estimation methods via HILO‐MPC

AbstractModel‐based optimization approaches for monitoring and control, such as model predictive control and optimal state and parameter estimation, have been used successfully for decades in many engineering applications. Models describing the dynamics, constraints, and desired performance criteria are fundamental to model‐based approaches. Thanks to recent technological advancements in digitalization, machine‐learning methods such as deep learning, and computing power, there has been an increasing interest in using machine learning methods alongside model‐based approaches for control and estimation. The number of new methods and theoretical findings using machine learning for model‐based control and optimization is increasing rapidly. However, there are no easy‐to‐use, flexible, and freely available open‐source tools that support the development and straightforward solution to these problems. This article outlines the basic ideas and principles behind an easy‐to‐use Python toolbox that allows to solve machine‐learning‐supported optimization, model predictive control, and estimation problems quickly and efficiently. The toolbox leverages state‐of‐the‐art machine learning libraries to train components used to define the problem. Machine learning can be used for a broad spectrum of problems, ranging from model predictive control for stabilization, set point tracking, path following, and trajectory tracking to moving horizon estimation and Kalman filtering. For linear systems, it enables quick generation of code for embedded model predictive control applications. HILO‐MPC is flexible and adaptable, making it especially suitable for research and fundamental development tasks. Due to its simplicity and numerous already implemented examples, it is also a powerful teaching tool. The usability is underlined, presenting a series of application examples.

Quasi and metaheuristic optimization approach for service system with strategic policy and unreliable service

Quasi and metaheuristic optimization approach for service system with strategic policy and unreliable service

Application of Machine Learning Methods for Process Optimization in Electronic Packaging Processes

Epoxy resins are commonly used as encapsulation materials in electronic packaging processes. Fluctuations in the materials lead to both changes in processability and to varying quality. Ideally, these variations should be identified, and measures taken as quickly as possible to reduce scrap parts and thus costs. A promising optimization approach for encapsulation processes are machine learning models, which have already shown good results in quality predictions, especially for injection molding. Subsequent quality measurements are avoided with good quality prediction models. With this type of models, not only predictions can be made, but also optimal parameter combinations can be found. In this paper, models for predicting quality criteria warpage and residual enthalpy of the epoxy molding compound were set up, trained and validated. Time series of in-situ sensors were used, from which relevant features were extracted and which, together with machine parameters, provide a dataset for prediction. The most promising prediction models are random forest regression and gradient boosting regression. T hey predict warpage with an accuracy of 90% to 91% and the residual enthalpy with an accuracy of 95%. Subsequently, optimization models of the machine parameters were set up. All relevant target variables were considered in a cost function, through the minimization of which an optimal parameter set was found. The gradient boosted tree and Bayesian optimization were determined to be the most promising models, as they lead to the lowest values of the respective cost function.

PREPARATION AND JUSTIFICATION OF NANOFIBRES-LOADED MAFENIDE USING ELECTROSPINNING TECHNIQUE TO CONTROL RELEASE

Objective: The primary objective was to fabricate a novel drug delivery system capable of providing a controlled and prolonged release of antibiotics. Methods: The experimental design was formulated using Design-Expert® software (version 13), enabling systematic and efficient fabrication process optimization. The study involved the preparation of various nanofiber formulations with different ratios of the three polymers to assess their impact on drug release behavior. Mafenide, a widely used antibiotic, was chosen as the model drug for this investigation. The electrospinning process allowed for producing uniform and fine nanofibers with a high surface area, ensuring a large drug-loading capacity. The synthesized nanofibers were characterized using scanning electron microscopy (SEM) and Fourier transform infrared spectroscopy (FTIR) to evaluate their morphology, chemical interactions, and thermal properties. The drug release kinetics of the antibiotic-loaded nanofibers were studied under different physiological conditions to assess their sustained release behavior. Results: The final nanofiber formula was successfully prepared using the electrospinning technique. The Fourier Transform Infrared Spectroscopy (FTIR) analysis was achieved to confirm the possibility of chemical interaction and bond formation between mafenide and the polymers. Present. The SEM picture of the optimized nanofiber formula showed the homogeneity and excellent entanglement of the electrospun nanofibers at a resolution of 5 µm. PVA/chitosan/HPMC and mafenide pure drug have been successfully fabricated with sufficient strength to resist swelling after absorbing wound exudate. The polymer network becomes more compact when chitosan and Hydroxypropyl Methyl Cellulose (HPMC) are combined with polyvinyl alcohol (PVA), enabling regulated swelling during solvent ingress. The polymer composite's three-dimensional network influenced how quickly the medication was released from the matrix. Sample 2's polymer network traps the medication, gradually releasing after controlled swelling, resulting in a sustained release profile compared to blank sample according to the cumulative release (%) study of mafenide loaded nanofiber and mafenide drug blank sample. Conclusion: This research successfully demonstrated the fabrication of sustained-release antibiotic nanofibers using electrospinning and three biocompatible polymers. The systematic optimization approach using Design-Expert® software proved effective in tailoring the drug release behavior of nanofibers. The developed drug delivery system holds great promise for pharmaceutical applications, particularly in improving antibiotic therapies and patient care.

Barriers to adopting intracorporeal anastomosis in colorectal procedures amongst Australian general surgeons.

Minimally invasive colonic anastomosis can be performed intracorporeally or extracorporeally with laparoscopic or robotic assistance. In colorectal surgery, choosing the optimal approach is still controversial. Mainly, the debate involves balancing the potential benefits of intracorporeal anastomosis (ICA) with increased technical difficultly with the more straightforward and widely accepted extracorporeal anastomosis (ECA). Both techniques require different skill sets, and this study aims to identify barriers that prevent adoption of ICA. A 31-point questionnaire survey was distributed through the General Surgeons Australia (GSA) platform of active general surgeon in Australia. It was open for 2 months between July and August 2023. Statistical analysis was completed using descriptive analysis and logistic regression. Forty-three general surgeons completed the survey. ECA was the most performed and preferred surgical technique. It was identified that increased operative time is the biggest barrier to completing ICA followed by lack of training and no perceived benefit with ICA. Patient comorbidities did not result in choosing ICA over ECA; however, surgeons with less experience and volume in colorectal surgery were more likely complete ECA in operations with increased technical difficulty. Although ECA is the go-to technique for many Australian general surgeons, it is evident that they may be overlooking the benefits offered by ICA. Further training is required to improve operative times and confidence in the technique. Ongoing research, audits of existing techniques, and updated training will assist surgeons becoming acquainted with the latest evidence and to offer the best care to their patients.

Experimental validation of double-fed induction generator in oscillating water column using circulatory system-based optimization

Abstract This paper validates the optimal operation for a grid-connected double-fed induction generator (DFIG) in an oscillating water column power plant (OWCPP). This study presents a novel optimization technique called the circulatory system-based optimization (CSBO) approach to develop six adaptive fuzzy logic controllers (AFLCs) with 30 parameters and compare them to chaotic-billiards optimization (C-BO) and genetic algorithm (GA). The proposed controller is also compared with a proportional–integral differential (PID) controller based on a self-adaptive global-best harmony search (SGHS). CSBO-based AFLCs are fully investigated under different scenarios and experimented with using a real-time interface DSP1104. The results of using CSBO–AFLCs revealed a fast time response, fast convergence, less overshoot and minimal error compared with those achieved with C-BO–AFLC, SGHS–PID and GA–AFLC during different case studies. The CSBO-based AFLCs ensure maximum power from the DFIG in an OWCPP and enhance dynamic response with very low errors. The results show that the CSBO shows better power tracking by 25% as compared with C-BO, by 45% when compared with the GA and by 56% when compared with PID. Moreover, the integral absolute errors of six controllers are investigated to demonstrate the feasibility of CSBO–AFLC. The root mean square of the errors of six controllers using CSBO is improved by 68.27% when compared with GA, by 22.57% when compared with C-BO and by 38.42% when compared with PID. These indicators demonstrate the feasibility of CSBO when compared with other algorithms with the same OWCPP.

Reporting of core outcomes in gastric cancer surgery trials over the past 25 years (systematic review).

Gastric cancer, a leading cause of cancer-related mortality worldwide, has seen limited improvement in survival over the past 3 decades. Surgical resection is the cornerstone of curative management but the optimal approach remains unclear. Decision-making is hindered by inconsistent outcome reporting limiting data synthesis between trials. International consensus between healthcare professionals and patients has formed a core outcome set to be reported as a minimum. We appraised outcomes previously reported. Evidence Based Medicine Reviews, MEDLINE, EMBASE and CINAHL were searched for randomised controlled trials (RCTs) and systematic reviews of RCTs during years 1995-2021. We searched trial registries for protocols of ongoing and future trials. Ninety-nine articles from 64 studies and 69 trial protocols were included. No study reported all core outcomes: average reported per trial was 4 (interquartile range:2). 'Serious' adverse events were reported by 98%, completeness of tumour removal by 85% and surgery-related death by 74%. Outcomes important to patients were reported least: quality of life (22%) and nutritional effects (15%). Defining outcomes and time frames used was variable. Critically important outcomes are poorly reported in the literature and the status has not improved in future trials. Further work is required to improve uptake.

State of the Art: Pouch Surgery in the 21st Century.

An ileoanal pouch with IPAA is the preferred method to restore intestinal continuity in patients who require a total proctocolectomy. Pouch surgery has evolved during the past decades thanks to increased experience and research, changes in the medical management of patients who require an ileal pouch, and technological innovations. To review the main changes in pouch surgery over the past 2 decades, with a focus on staging, minimally invasive and transanal approaches, pouch design, and anastomotic configuration. The decision on the staging approach depends on the patient's conditions, their indication for surgery, and the risk of anastomotic leak. A minimally invasive approach should be performed whenever feasible, but open surgery still has a role in this technically demanding operation. Transanal IPAA may be performed in experienced centers and may reduce conversion to open surgery in the hostile pelvis. The J-pouch is the easiest, fastest, and most commonly performed design, but other designs may be used when a J-pouch is not feasible. A stapled anastomosis without mucosectomy can be safely performed in the majority of cases, with a low incidence of rectal cuff neoplasia and better functional outcomes than handsewn. Finally, Crohn's disease is not an absolute contraindication to an ileoanal pouch, but pouch failure may be higher compared to other indications. Many technical nuances contribute to the success of an ileoanal pouch. The current standard of care is a laparoscopic J-pouch with double-stapled anastomosis, but this should not be seen as a dogma, and the optimal approach and design should be tailored to each patient. See video from symposium.

Optimising laser-induced phased-arrays for defect detection in continuous inspections

This paper proposes a novel optimisation approach for laser induced phased-arrays for detection purposes in large area inspection. The optimisation aims to maximise the detection capability of a phased-array while minimising the inspection time. This is done by using a simulation ray-tracing model that evaluates multiple candidate configurations. The metrics that measure the detection performance for a target defect are the receiver operating characteristic curve and the signal-to-noise ratio. The inspection time is indirectly computed through the number of measurement points per unit length in a continuous inspection. This depends on the physical aperture and pitch of the phased-array and they are the quantities optimised. The optimisation and modelling approach are validated in an experimental case study for a side-drilled hole as target defect. Further recommendations about directional defects (e.g. cracks at different angles) are provided.