Adaptive Procedure Research Articles

Chemical reaction inspired approach for routing problems with hard time constraints

ABSTRACT One of the most common issues in logistics and transportation planning is the vehicle routing problem. The objective is to find minimum cost-vehicle routes for serving a set of dispersed customers with deterministic demands while satisfying some constraints. In this paper, we focus on two main constraints, which are vehicle capacity and time windows for customers. We propose to tackle this NP-hard problem with a bio-inspired approach based on a hybridization of Chemical Reaction Optimization and local search method. The solving process of our approach mimics the chemical reactions between molecules to attain their stability with lowest energy. For more diversification of the search space, we involved in the initialization stage a local search method based on greedy adaptive procedure. The performances of our hybrid approach are assessed on the base of various benchmark instances. Simulation results show the good performances and the efficiency of the proposed approach.

Adaptive impact analysis in flexible multibody systems based on hierarchically refined IGA models

Usually, detailed impact simulation models within flexible multibody systems have to be set up manually rather than being generated automatically. This is because the process requires prior knowledge of the time and location of the impact, as well as the element resolution within the contact area. If the penalty method is used to determine the occurring contact forces, the corresponding penalty factor also needs to be determined manually. This work, however, presents an adaptive algorithm to simulate impacts within flexible multibody systems fully automatically using reduced isogeometric analysis models, the floating frame of reference formulation, and quasistatic contact models for an efficient but still accurate simulation. The adaptive algorithm detects impacts in the system, determines the contact locations on the bodies, refines the contact area, and determines the penalty factor, and therefore automatically simulates impacts. The work shows how to automatically simulate impacts in flexible multibody systems without user action or prior knowledge of impact location and size. The first application example simulates significant elastodynamic effects within a long flexible rod. The goal is to validate the algorithm by preserving the wave propagation and energy of the system. The second application example simulates the impacts of two flexible double pendulums. This setup is a suitable benchmark for the complete adaptive impact analysis procedure as the flexible double pendulums undergo large rigid body motions.

The home health care routing with heterogeneous electric vehicles and synchronization

AbstractThis paper studies the problem of heterogeneous electric vehicles, fast chargers, and synchronized jobs that have time windows in home healthcare routing and scheduling. We consider a problem that aims to establish daily routes and schedules for healthcare nurses to provide a variety of services to patients located in a scattered area. Each nurse should be assigned to an electric vehicle (EV) from a heterogeneous fleet of EVs to perform the assigned jobs within working hours. We consider three different types of EVs in terms of battery capacity and energy consumption. We aim to minimize the total cost of energy consumption, fixed nurse cost, and costs arising from the patients that cannot be served within the working day. We model the problem as a mixed integer programming formulation. We develop a hybrid metaheuristic based on a greedy random adaptive search procedure heuristic, to generate good quality initial solutions quickly, and an adaptive variable neighborhood search algorithm to generate high quality solutions in reasonable time. The hybrid metaheuristic employs a set of new advanced efficient procedures designed to handle the complex structure of the problem. Through extensive computational experiments, the performance of the mathematical model and the hybrid metaheuristic are evaluated. We conduct analyses on the robustness of the metaheuristic and the performance contribution of employing adaptive probabilities. We analyze the impact of problem parameters such as competency requirements, job duration, and synchronized jobs.

Evaluation and application of a Chinese version symptom questionnaire for visual dysfunctions (CSQVD) in school-age children

ObjectiveTo develop and evaluate a Chinese version of the Symptom Questionnaire for Visual Dysfunctions (CSQVD) to quantify visual dysfunction symptoms in school-age children with various eye diseases, and to explore the relationship between ophthalmological disorders and visual dysfunction symptoms. MethodsFollowing standard scale adaptation procedures, the Symptom Questionnaire for Visual Dysfunctions (SQVD) was translated into Chinese (CSQVD). We employed random sampling to survey 198 outpatients aged 7–18 to assess the psychometric properties of the CSQVD. Using the reliable and validated questionnaire, we evaluated the determinants of visual dysfunction symptoms among 406 school-age patients at an eye center. The CSQVD scores were correlated with demographic and clinical variables, including gender, age, eye position, refractive power, and best-corrected visual acuity. Univariate analysis identified potential risk factors, followed by binary logistic regression and multiple linear regression analysis on factors with a P-value <0.05. ResultsThe CSQVD scale's critical ratio (CR) values ranged from 6.028 to 10.604. The Cronbach's Alpha coefficient was 0.779, and Spearman-Brown split-half reliability was also 0.779. The I-CVI varied from 0.83 to 1.000, the S-CVI/Ave was 0.857, and the KMO value was 0.821. Multifactorial regression analysis indicated that high myopia (OR ​= ​5.744, 95% CI [1.632, 20.218], P ​= ​0.006) and amblyopia (OR ​= ​9.302, 95% CI [1.878, 46.058], P ​= ​0.006) were significant predictors of CSQVD symptoms. Multiple linear regression analysis showed that BCVA of amblyopic eyes (B ​= ​−5.052, 95% CI [−7.779, 2.325], P ​= ​0.000) and SE power (B ​= ​−0.234, 95% CI [−0.375, 0.205], P ​= ​0.001) significantly affected the CSQVD scale scores. ConclusionsThe Chinese version of the SQVD scale (CSQVD) demonstrates good feasibility, discriminatory power, validity, and reliability in assessing Chinese school-aged children. Furthermore, those who have severe myopia and amblyopia reported more visual dysfunction symptoms.

Anisotropic Mach Cone Aligned Mesh Adaptation for Low Boom Simulations

An automated off-body Mach cone aligned structured curvilinear grid generation procedure is presented for near-field computational fluid dynamics simulations. This procedure combines output-based indicators and mesh redistribution to perform anisotropic mesh adaptation while maintaining Mach cone alignment. Automation is achieved through a novel direction-based adaptation indicator formulation. The adaptation procedure is demonstrated on the JAXA Wing Body geometry and X-59 C608 demonstrator models from the Second and Third AIAA Sonic Boom Prediction Workshops, respectively. It is demonstrated that anisotropic mesh adaptation may result in a greater than 50% reduction in the resource usage required to achieve the same level of accuracy as uniform and user-constructed Mach cone aligned grids for near-field pressure signatures, ground-level overpressure signatures, and loudness metrics.

Adaptive two-stage seamless sequential design for clinical trials

ABSTRACT We propose an adaptive sequential testing procedure for the selection and testing of multiple treatment options, such as dose/regimen, different drugs, sub-populations, endpoints, or a mixture of them in a seamlessly combined phase II/III trial. The selection is to be made at the end of phase 2 stage. Unlike in many of the published literature, the selection rule is not required to be to “select the best”, and does not need to be pre-specified, which provides flexibility and allows the trial investigators to use any efficacy and safety information/criteria, or surrogate or intermediate endpoint to make the selection. Sample size and power calculations are provided. The calculations have been confirmed to be accurate by simulations. Interim analysis can be performed after the selection, sample size can be modified if the observed efficacy deviates from the assumed. Inference after the trial, including p-value, median unbiased point estimate and confidence intervals, are provided. By applying a dominance theorem, the procedure can be applied to normal, binary, Poisson, negative binomial distributed endpoints and time-to-event endpoints, and a mixture of these distributions (in trials involving endpoint selection).

Guidelines and recommendations for cross-linguistic aphasia assessment: a review of 10 years of comprehensive aphasia test adaptations

ABSTRACT Background Standardised aphasia assessment tools may not always be available in a variety of languages, posing challenges for speech and language therapists to adequately assess and diagnose aphasia in speakers of those languages. In 2013, Working Group 2 (WG2) Aphasia Assessment & Outcomes, part of the Collaboration of Aphasia Trialists network, was formed with the purpose of developing reliable and valid aphasia assessment tools and their cross-linguistic adaptations. Over the past decade, WG2 has undertaken important adaptation projects, including the cross-linguistic adaptation of the Comprehensive Aphasia Test (CAT; Swinburn et al., 2004). Aims This review aims to achieve three objectives: (a) describe the adaptation procedure of the CAT within WG2, (b) summarise common guidelines and recommendations for future adaptations, and (c) provide concrete solutions for specific cross-linguistic and cross-cultural challenges encountered during the adaptation and validation procedures of the CAT. Methods Between 2013 and 2023, WG2 employed a committee approach and fully adapted the CAT into Catalan, Croatian, Dutch, French, Hungarian, Norwegian, Spanish, and Turkish. Further adaptations are in progress for Arabic (Moroccan), Basque, Cantonese Chinese, German, Greek, Icelandic, Lithuanian, Serbian, Slovenian and Swedish. The review comprehensively addresses the linguistic/cultural adaptation and validation procedure for the three components of the battery: the Cognitive screening, the Language battery and the Aphasia Impact Questionnaire. Critical outcomes and some best practice recommendations from psychometric norming and piloting are also discussed. Outcomes and results This review builds upon prior work (Fyndanis et al., 2017) and serves as a practical guide for researchers and clinicians undertaking cross-linguistic adaptations of the CAT, with specific conclusions and recommendations drawn from WG2’s adaptations in 19 languages with diverse typological properties. Building on the work exemplified in this paper, future initiatives can direct their efforts towards adapting the CAT for PWA from different linguistic backgrounds for whom validated assessment instruments may be unavailable. This can be achieved through rigorous systematic adaptation procedures for the establishment of comparable language versions of this tool, valuable for various clinical applications. Such endeavours have the potential to provide access to valuable shared datasets for their use across international aphasia trials, and for comparable clinical work within the aphasiology community.

Cochlear-implant listeners benefit from training with time-compressed speech, even at advanced ages.

This study evaluated whether adaptive training with time-compressed speech produces an age-dependent improvement in speech recognition in 14 adult cochlear-implant users. The protocol consisted of a pretest, 5 h of training, and a posttest using time-compressed speech and an adaptive procedure. There were significant improvements in time-compressed speech recognition at the posttest session following training (>5% in the average time-compressed speech recognition threshold) but no effects of age. These results are promising for the use of adaptive training in aural rehabilitation strategies for cochlear-implant users across the adult lifespan and possibly using speech signals, such as time-compressed speech, to train temporal processing.

Understanding Metaphors: A Study with Portuguese 4-6 Year-old Children

We present the first metaphor comprehension data from 36 Portuguese children aged 4, 5 and 6, using the TCM Júnior, a metaphor comprehension test for young children, in its European Portuguese version. This is an exploratory descriptive study, with a view to collecting data, contributing to the measurement and standardization of the resource used. TCM Júnior is an adaptation of its corresponding Italian acronym, which is in the process of being validated for the Portuguese population in this age group (4 to 6 years old). We describe the resource used, the TCM Junior, Metaphor Comprehension Test for 4-6 years old and the results obtained with a sample. The instrument used is in the process of gauging, or external validation that is, meeting normative data, although it is already subject to adaptation procedures, as it is an original test in Italian. In this study, 36 participants of both sexes participated. Although still incipient, because there are still few data, with groups by age and sex that are not equitable and significant, the results are promising. We will report on the data obtained and analyzed. Although still preliminary and exploratory, with a sample that is still not very representative and significant, the results appear to be not very distant from the averages obtained by their Italian counterparts. Keywords: metalinguistic awareness, understanding, figurative language, metaphors, TCM junior

Understanding Metaphors: Preliminary Results with Children 9-14 Years Old

We present the results of a study with a group of children aged 9-14 years old, on the understanding of metaphors. We describe the resource used, the TCM, Metaphor Comprehension Test for children aged 9-14 years and the results obtained with a sample. In this study, 95 subjects of both sexes participated, aged between 9 (4th grade) and 15 (9th grade), from a school in the region of Aveiro. The results revealed that, with increasing age, the rating level of responses tends to increase. The instrument used is in the process of gauging, or external validation, that is, meeting normative data, although it is already subject to adaptation procedures, as it is an original test in Italian. We will give an account of the data obtained and analyzed which, to date, seem to us to be quite promising. Although still preliminary and exploratory, with a sample that is still not very representative and significant, the results appear to be not very distant from the averages obtained by their Italian counterparts. Keywords: metalinguistic awareness, understanding, figurative language, metaphors, TCM

A greedy randomized adaptive search procedure for scheduling IoT tasks in virtualized fog–cloud computing

AbstractVirtualized fog–cloud computing (VFCC) has emerged as an optimal platform for processing the increasing number of emerging Internet of Things (IoT) applications. VFCC resources are provisioned to IoT applications in the form of virtual machines (VMs). Effectively utilizing VMs for diverse IoT tasks with varying requirements poses a significant challenge due to their heterogeneity in processing power, communication delay, and energy consumption. In addressing this challenge, in this article, we propose a system model for scheduling IoT tasks in VFCCs, considering not only individual task deadlines but also the system's overall energy consumption. Subsequently, we employ a greedy randomized adaptive search procedure (GRASP) to determine the optimal assignment of IoT tasks among VMs. GRASP, a metaheuristic‐based technique, offers appealing characteristics, including simplicity, ease of implementation, a limited number of tuning parameters, and the potential for parallel implementation. Our comprehensive experiments evaluate the effectiveness of the proposed method, comparing its performance with the most advanced algorithms. The results demonstrate that the proposed approach outperforms the existing methods in terms of deadline satisfaction ratio, average response time, energy consumption, and makespan.

Evolution inspired binary flower pollination for the uncapacitated facility location problem

The present paper introduces a modified flower pollination algorithm (FPA) enhanced by evolutionary operators to solve the uncapacitated facility location problem (UFLP), which is one of the well-known location science problems. The aim in UFLP is to select some locations to open facilities among a certain number of candidate locations so as to minimize the total cost, which is the sum of facility opening costs and transportation costs. Since UFLP is a binary optimization problem, FPA, which is introduced to solve real-valued optimization problems, is redesigned to be able to conduct search in binary domains. This constitutes one of the contributions of the present study. In this context, some evolutionary operators such as crossover and mutation are adopted by the proposed FPA. Next, the mutation operator is further enhanced by making use of an adaptive procedure that introduces greater level of diversity at earlier iterations and encourages intensification toward the end of search. Thus, while premature convergence and local optima problems at earlier iterations are avoided, a more intensified search around the found promising regions is performed. Secondarily, as demonstrated in this study, by making use of the reported evolutionary procedures, FPA is able to run in binary spaces without employing any additional auxiliary procedures such as transfer functions. All available benchmarking instances are solved by the proposed approach. As demonstrated by the comprehensive experimental study that includes statistically verified results, the developed approach is found as a promising algorithm that can be extended to numerous binary optimization problems.

Reduced-order modelling for real-time physics-based variation simulation enhanced with adaptive sampling and optimized interpolation

AbstractManufacturing industries require a right-first-time paradigm to remain competitive. Variation simulation (VS) is a key tool to predict variation of the final shape of flexible assemblies, allowing to reduce defects and waste. VS models involving compliant sheet-metal parts commonly integrate physics-based simulation with statistical approaches (usually Monte Carlo simulation). Although increasingly used as a backbone of synthesis techniques for (stochastic) optimization of assembly systems, the main roadblock of VS methods is the intense computational costs due to time-intensive simulations and high-dimensional design space. Driven by the need of time reduction, this paper presents an innovative real-time physics-based VS model of assembly systems with compliant sheet-metal parts. The proposed methodology involves a non-intrusive reduced-order model (niROM), empowered by a novel adaptive sampling procedure for dataset generation, and a cross-validation-based optimized radial basis function (RBF) formulation for interpolation. Demonstrated through two case studies—(i) a remote laser welding operation to predict mechanical distortions, with two input parameters, and (ii) the assembly of an aircraft vertical stabilizer with five input parameters—the methodology achieves accurate real-time results, with up to a 43% improvement in accuracy compared to traditional sampling techniques. Findings highlight the critical influence of the sampling strategy and the number of input parameters on ROM accuracy. Better results are reached by employing adaptive sampling in combination with optimum RBF, which additionally disengages the user from the choice of the interpolation settings. This study unlocks new avenues in the field of variation simulation and dimensional/quality monitoring by narrowing the gap between any advanced CAE solver and VS models with real-time physics-based simulations.

The Classification of Gluteal Augmentation.

Gluteal enhancement is a major growing trend within aesthetic surgery practice. Patient needs include volume augmentation and enhancement of the roundness of buttocks. In this letter we suggest a classification of gluteal augmentation procedures. The classification helps to analyze the case easier and applying the most adaptable procedure for each patient. Our classification of gluteal augmentation is divided to Pseudo-augmentation (illusionary) and Real (true) augmentation which is subdivided to Non-surgical and Surgical.

Adaptive suboptimal control of some discrete-time plants with nonstochastic bounded disturbances

This paper deals with the adaptive suboptimal control of linear, discrete-time, time-invariant, minimum phase, scalar plants in the presence of nonstochastic bounded unmeasurable disturbances whose upper and lower bounds, which may be asymmetric, are assumed to be unknown a priori. Additional assumption is that an order of the difference equation describing the plant is known a priori. The distinguishing feature of the problem stated in this paper is that neither bounds on the unmeasured disturbances, nor bounds on an allowable region to which the unknown plant parameters belong are assumed to be known a priori. To solve this problem, adaptation procedures for the point and membership set estimation are utilized. The standard recursive procedure with adjustable dead zone is employed in order to derive the point estimates of unknown plant parameters together with the point estimate of time-invariant disturbance component. The size of this dead zone depends on the previous point estimate of the bounds on the time-varying disturbance component and also on a fixed suboptimality index chosen by the designer. The estimates generated by the point estimation procedure are directly exploited to derive the adaptive control law. The main idea advanced in this paper is that, instead of unknown a priori membership set of these parameters, their peculiar hypothetical a posteriori membership sets are designed via the use of the measured system’s signals together with the current point estimate of bounds on the time-varying disturbance component. Contrary to the usual membership set estimation approach, this set is updated if only it is discovered that the unknown parameter vector does not belong in reality to this set. To this end, a remarkable property of the point estimation procedure is utilized. Such an approach makes it possible to reconstruct this set and to update the previous estimate of the bounds on the time-varying disturbance component. The finite convergence of the adaptation procedures and also the ultimate boundedness of system’s signals are established. To demonstrate an efficiency of the adaptive controller and support the theoretical study, simulation results are presented.

Cross-Cultural Adaptation of a Questionnaire Measuring Organizational Citizenship Behavior towards the Environment

Translation, adaptation, and validation of instruments for cross-cultural investigation requires a rigorous methodological procedure that should be carefully planned to deliver instruments with adequate reliability and validity. This process was applied to a questionnaire measuring Organizational Citizenship Behavior toward the Environment (OCBE), Organizational Identification (OI), Environmental Responsibility (ER), and Green Human Resources Management (GHRM) in Portuguese and Slovak organizations. Several methodological procedures for cross-cultural adaptation and validation of questionnaires were analyzed, most of which used independent translators, experts’ analysis, and backward translation to the original language. In the present study, a procedure adapted from Beaton et al. (2000) was applied successfully, and the blind backward translations; expert committee; and the two pretests to assess content validity, functional equivalence, and clarity proved to be worthy. The psychometric properties were measured using a sample from Portugal (N = 122) and Slovakia (N = 269). Although employees were perceiving neither a strong environmental responsibility of their organizations nor strong green human resources management, they identified themselves with the organizations and engaged in OCBEs. Comparing both countries, the factorial structure was remarkably similar, highlighting the eco-helping actions and eco-civic engagement of OCBEs. Comparing both countries, the factorial structure was remarkably similar, highlighting the eco-helping actions and eco-civic engagement of OCBEs. The results indicated that the translated instrument was functionally equivalent to the original one, valid (scale CVI/Ave &gt; 0.83), and reliable (Scale Alpha &gt; 0.733) for evaluating the effect of employee practices and organization management in promoting and supporting environmental sustainability.

An adaptive phase-field method for structural topology optimization

In this work, we develop an adaptive algorithm for the efficient numerical solution of the minimum compliance problem in topology optimization. The algorithm employs the phase field approximation and continuous density field. The adaptive procedure is driven by two residual type a posteriori error estimators, one for the state variable and the other for the first-order optimality condition of the objective functional. The adaptive algorithm is provably convergent in the sense that the sequence of numerical approximations generated by the adaptive algorithm contains a subsequence convergent to a solution of the continuous first-order optimality system. We provide several numerical simulations to show the distinct features of the algorithm.

The integrated planning of outgoing coil selection for retrieval, multi-crane scheduling, and location assignment to the incoming and blocking coils in steel coil warehouses

In this paper, the problem of scheduling crane-operated warehouses in a triangle stacking style is investigated. In a steel supply chain, warehouses play a significant role in establishing a connection between the producer and the customers. Therefore, improving their performance results in a competitive advantage in the supply chain. One of the challenges of steel coil warehouses is the selection of outgoing coils out of the candidate coils for retrieval. Despite its importance, this problem has not been investigated in the studies relevant to steel coil warehouses. In this study, in addition to the selection of outgoing coils, sequencing of the operations on the incoming, outgoing, and blocking coils, location assignment to the incoming and blocking coils, and crane scheduling are considered in an integrated manner. First, a mixed integer linear programming model is proposed. Further, a Greedy heuristic algorithm and two metaheuristics are developed to solve large-sized instances of the problem. Metaheuristics include a Greedy Randomized Adaptive Search Procedure (GRASP) and a hybrid algorithm that combines Ant Colony System with the GRASP (ACS-GRASP). Finally, performances of the proposed algorithms are compared over randomly generated instances as well as instances which are generated based on the real data obtained from Isfahan’s Mobarakeh Steel Company. To conduct this analysis, various performance evaluation metrics are applied. Computational results indicate that ACS-GRASP converges slower than GRASP, but is more reliable and efficient. On the other hand, in large-sized instances, the Greedy algorithm runs extremely fast and can find solutions which are comparable to the metaheuristic solutions.

Adaptation and psychometric properties of a brief version of the general self-efficacy scale for use with artificial intelligence (GSE-6AI) among university students

BackgroundIndividual beliefs about one’s ability to carry out tasks and face challenges play a pivotal role in academic and professional formation. In the contemporary technological landscape, Artificial Intelligence (AI) is effecting profound changes across multiple sectors. Adaptation to this technology varies greatly among individuals. The integration of AI in the educational setting has necessitated a tool that measures self-efficacy concerning the adoption and use of this technology.ObjectiveTo adapt and validate a short version of the General Self-Efficacy Scale (GSE-6) for self-efficacy in the use of Artificial Intelligence (GSE-6AI) in a university student population.MethodsAn instrumental study was conducted with the participation of 469 medical students aged between 18 and 29 (M = 19.71; SD = 2.47). The GSE-6 was adapted to the AI context, following strict translation and cultural adaptation procedures. Its factorial structure was evaluated through confirmatory factorial analysis (CFA). Additionally, the factorial invariance of the scale based on gender was studied.ResultsThe GSE-6AI exhibited a unidimensional structure with excellent fit indices. All item factorial loads surpassed the recommended threshold, and both Cronbach’s Alpha (α) and McDonald’s Omega (ω) achieved a value of 0.91. Regarding factorial invariance by gender, the scale proved to maintain its structure and meaning in both men and women.ConclusionThe adapted GSE-6AI version is a valid and reliable tool for measuring self-efficacy in the use of Artificial Intelligence among university students. Its unidimensional structure and gender-related factorial invariance make it a robust and versatile tool for future research and practical applications in educational and technological contexts.

Bayesian Adaptive Lasso for the Detection of Differential Item Functioning in Graded Response Models

The detection of differential item functioning (DIF) is important in psychological and behavioral sciences. Standard DIF detection methods perform an item-by-item test iteratively, often assuming that all items except the one under investigation are DIF-free. This article proposes a Bayesian adaptive Lasso method to detect DIF in graded response models (GRMs), where the DIF effects for all items can be identified simultaneously. The multiple-group GRMs are specified, and the possible DIF effects for each item are reparameterized using the increment components. Then, a Bayesian adaptive Lasso procedure is developed for parameter estimation, in which DIF effects can be automatically obtained. Our method is evaluated and compared with the commonly used likelihood ratio test method in a simulation study. The results show that our method can recover most model parameters well and has better control of false positive rates in almost all conditions. An application is presented using data from the National Longitudinal Study of Adolescent to Adult Health (Add Health).