Heuristic

Sand cat swarm optimization algorithm is a meta-heuristic algorithm created to replicate the hunting behavior observed by sand cats. The presented sand cat swarm optimization method (CWXSCSO) addresses the issues of low convergence precision and local optimality in the standard sand cat swarm optimization algorithm. It accomplished this through the utilization of elite decentralization and a crossbar approach. To begin with, a novel dynamic exponential factor is introduced. Furthermore, throughout the developmental phase, the approach of elite decentralization is incorporated to augment the capacity to transcend the confines of the local optimal...

Scrolling is a widely used mean to interact with visual displays, usually to move content to a certain target location on the display. Understanding how user scroll might identify potentially suboptimal use and allows to infer users' intentions. In the present study, we examined where users click on a scrollbar depending on the intended scrolling action. In two online experiments, click positions were systematically adapted to the intended scrolling action. Click position selection could not be explained as strict optimization of the distance traveled with the cursor, memory load, or motor-cognitive factors...

BACKGROUND: Diagnostic reasoning is a complex cognitive process that requires intuitive, heuristic processing from knowledge and experience, as well as deliberate and reflective thinking. Evidence on interventions to improve diagnostic reasoning is inconsistent, in part because different terms and models are used to guide research. PURPOSE: To present a model of the factors of diagnostic reasoning in Advanced Practice Registered Nurses (APRNs), based on a review of the literature supporting the Metacognitive Diagnostic Reasoning (MDR) Model©...

Artificial intelligence (AI) algorithms are prone to bias at multiple stages of model development, with potential for exacerbating health disparities. However, bias in imaging AI is a complex topic that encompasses multiple coexisting definitions. Bias may refer to unequal preference to a person or group owing to preexisting attitudes or beliefs, either intentional or unintentional. However, cognitive bias refers to systematic deviation from objective judgment due to reliance on heuristics, and statistical bias refers to differences between true and expected values, commonly manifesting as systematic error in model prediction (ie, a model with output unrepresentative of real-world conditions)...

Perfectly rational decision making is almost always out of reach for people because their computational resources are limited. Instead, people may rely on computationally frugal heuristics that usually yield good outcomes. Although previous research has identified many such heuristics, discovering good heuristics and predicting when they will be used remains challenging. Here, we present a theoretical framework that allows us to use methods from machine learning to automatically derive the best heuristic to use in any given situation by considering how to make the best use of limited cognitive resources...

BACKGROUND: Defining healthcare facility catchment areas is a key step in predicting future healthcare demand in epidemic settings. Forecasts of hospitalisations can be informed by leading indicators measured at the community level. However, this relies on the definition of so-called catchment areas or the geographies whose populations make up the patients admitted to a given hospital, which are often not well-defined. Little work has been done to quantify the impact of hospital catchment area definitions on healthcare demand forecasting...

BACKGROUND: Statistical process control (SPC) is a powerful statistical tool for process monitoring that has been highly recommended in healthcare applications, including radiation therapy quality assurance (QA). The AAPM TG-218 report described the clinical implementation of SPC for Volumetric Modulated Arc Therapy (VMAT) pre-treatment verifications, pointing out the need to adjust tolerance limits based on plan complexity. However, the quantification of plan complexity and its integration into SPC remains an unresolved challenge...

The incorporation of cleavable comonomers as additives into polymers can imbue traditional polymers with controlled deconstructability and expanded end-of-life options. The efficiency with which cleavable comonomer additives (CCAs) can enable deconstruction is sensitive to their local distribution within a copolymer backbone, which is dictated by their copolymerization behavior. While qualitative heuristics exist that describe deconstructability, comprehensive quantitative connections between CCA loadings, reactivity ratios, polymerization mechanisms, and deconstruction reactions on the deconstruction efficiency of copolymers containing CCAs have not been established...

Real-time control strategies deal with the day's dynamics in bus rapid transit systems. This work focuses on minimizing the number of buses of the same line cruising head-to-tail or arriving at a stop simultaneously by implementing bus holding times at the stops as a control strategy. We propose a new mathematical model to determine the bus holding times. It has quadratic constraints but a linear objective function that minimizes the bus bunching penalties. We also propose a beam-search heuristic to reduce computational solution time to solve large instances...

Lung cancer is one of the most deadly diseases in the world. Lung cancer detection can save the patient's life. Despite being the best imaging tool in the medical sector, clinicians find it challenging to interpret and detect cancer from Computed Tomography (CT) scan data. One of the most effective ways for the diagnosis of certain malignancies like lung tumours is Positron Emission Tomography (PET) imaging. So many diagnosis models have been implemented nowadays to diagnose various diseases. Early lung cancer identification is very important for predicting the severity level of lung cancer in cancer patients...

ConspectusDue to its importance for electrolyzers or metal-air batteries for energy conversion or storage, there is huge interest in the development of high-performance materials for the oxygen evolution reaction (OER). Theoretical investigations have aided the search for active material motifs through the construction of volcano plots for the kinetically sluggish OER, which involves the transfer of four proton-electron pairs to form a single oxygen molecule. The theory-driven volcano approach has gained unprecedented popularity in the catalysis and energy communities, largely due to its simplicity, as adsorption free energies can be used to approximate the electrocatalytic activity by heuristic descriptors...

The COVID-19 pandemic expedited the growing rate of reliance on telehealth, as it provided a safer option for patients to seek the care they need and avoid potential negative consequences of being exposed to the COVID-19 virus. The aim of this study is to develop a series of Human-Computer Interaction (HCI)-based leading indicators to proactively analyze and evaluate the user interface in telehealth and virtual visits. Building on Nielsen's usability heuristics and mapping them to the six aspects of quality of care introduced by the Institute of Medicine, we identified the design features that had the highest impact on the quality of care and developed a list of leading indicators for each feature...

According to many, we live in "posttruth" times, with the pervasiveness of falsehoods being an existential threat to democracy and the functioning of free societies. Why do people believe and propagate falsehoods? Current accounts focus on psychological deficiencies, heuristic errors, self-enhancing motivations, and motivations to sow chaos. Here, we advance a complementary, outwardly (vs. inwardly) oriented, and ultimate (vs. proximate) account that people often believe and spread falsehoods for socially functional reasons...

In this research, a bio-inspired heuristic computing approach has been developed to solve the nonlinear behavior of the human liver, which is categorized into the liver and blood. The solutions of the human liver model are presented by using the stochastic computation procedure based on the artificial neural network (ANN) along with the optimization of genetic algorithm (GA) and interior-point (IP). A fitness function is designed through the differential form of the nonlinear human liver model and then optimized by using the hybrid competency of GAIP scheme...

The primary goal of the binary model in this study was to understand the convergence pattern of the Pheidole latinoda ants. Forager and scout ants on the hunt for food use path integration. When they find a food source, they leave a trail pheromone to alert other nest mates. Every ant starts following that trail and reinforces it on their way back home. To investigate the ant convergence pattern, binary and ternary bridges of varying lengths are used. Each bridge is built in such a way that one end is connected to a food source whilst the other end is connected to the nest...

There is consensus about the importance of developing a strong cadre of effective multilevel interventions to eliminate the impacts of unjust social processes, such as structural racism and other harmful social determinants of health (SDOH), on health inequities in the USA. However, the available cadre of rigorously evaluated evidence-based interventions for SDOH mitigation remains underdeveloped relative to the magnitude of historic and current health inequities. The proposed manuscript addresses this gap in two ways: first, by introducing a heuristic framework to inform decisions in multilevel intervention development, study design, and selection of analytic methods and, second, by providing a roadmap for future applications of the framework in multilevel intervention research through an exemplar application using the ongoing NIH-funded evaluation study of the Nurse-Community-Family Partnership (NCFP) intervention...

The highly multimodal Rastrigin test function is analyzed by deriving a new aggregated progress rate measure. It is derived as a function of the residual distance to the optimizer by assuming normally distributed positional coordinates around the global optimizer. This assumption is justified for successful ES-runs operating with sufficiently slow step-size adaptation. The measure enables the investigation of further convergence properties. For moderately large mutation strengths a characteristic distance-dependent Rastrigin noise floor is derived...

BACKGROUND: In the metagenomic assembly of a microbial community, abundant species are often thought to assemble well given their deeper sequencing coverage. This conjuncture is rarely tested or evaluated in practice. We often do not know how many abundant species are missing and do not have an approach to recover them. RESULTS: Here, we propose k-mer based and 16S RNA based methods to measure the completeness of metagenome assembly. We show that even with PacBio high-fidelity (HiFi) reads, abundant species are often not assembled, as high strain diversity may lead to fragmented contigs...

Communities face the challenge of finding restoration strategies in the aftermath of disasters. In particular, independent and self-interested utility managers devise such strategies for infrastructure through a heuristic decentralized process. This paper takes a game-theoretic approach to model the decentralized and strategic restoration decision making with application to interdependent infrastructure. Particularly, we model the decision process using simultaneous games to investigate decision makers' conflicting preferences...

Natural language processing techniques enable extraction of valuable information from large amounts of published literature for the application of data science and technology, i.e. machine learning in the field of materials science. Nevertheless, the automated extraction of data from full-text documents remains a complex task. We propose a document-level natural language processing pipeline for literature extraction of comprehensive information on layered cathode materials for sodium-ion batteries. The pipeline enhances entity recognition with contextual supplementary information while capturing the article structure...