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Spatial visualization—the ability to mentally imagine and manipulate objects—has frequently been measured using the Paper Folding Test (PFT). In this task, participants view diagrams of a paper being folded and a hole being punched. They then identify the resulting punch pattern. Although task instructions promote mentally unfolding the paper, the extent to which people follow this spatial visualization strategy is unknown. The present work assesses hypothesized PFT solution strategies and their relation to problem attributes. Accuracy was impacted by the interaction between fold types, linear mixed models revealed greater use of simple heuristics compared to the suggested unfolding. Furthermore, most participants used a single strategy but simple heuristics were more often used than unfolding. Given this, we recommend redesigning the PFT to utilize the prevalence of strategy use to assess individual differences. • Spatial visualization is often measured using the Paper Folding test. • Because participants are assumed to imagine unfolding the paper, as instructed. • We examined four possible strategies and their interaction with problem attributes. • Participants used simple heuristics and fold types predicted performance. • The Paper Folding test should be redesigned to assess strategy use. [ABSTRACT FROM AUTHOR]

Abstract: Alarmingly low pulp prices in early 2009 left pulp and paper mills across North America desperate for any way to improve thin profit margins. One solution that continues to gain popularity among the industry is improved energy management systems for cogeneration systems, which use steam for two purposes – to provide heat for the pulping process and to generate electricity for sale to regional providers. This paper presents an energy optimization algorithm for use in a pulp and paper mill cogeneration system. The algorithm is applicable to a number of popular mill configurations, power sale contracts, and fuel purchasing scenarios. The method is also extended to address weather-dependent cooling limitations encountered by a mill cogeneration facility, in which case an iterative solution is proposed in order to maintain convexity of the optimization problem. Results are presented in the form of three case studies. [ABSTRACT FROM AUTHOR]

Transport and logistics systems include a range of activities that deal with all sorts of decisions and operations from material handling to vehicle routing. One of the main challenges for transport and logistics processes is to deal with large-scale and complex problems. However, with increasingly diverse sets of operational real-world data becoming available, data-driven heuristic approaches are promising to pave the path for solving the problems in the field of transport and logistics. Thus, a comprehensive review is needed to observe the reflections of this path in literature. To bridge this gap, a total of 40 papers on the topic of 'data-driven heuristic approaches to logistics and transportation problems' are determined. Before the categorization and content analysis; descriptive, bibliometric and social network analysis are carried out to identify the current state of the literature. All the papers are systemically reviewed based on different perspectives, namely data-driven methodology, heuristics, sub-problems and etc. Based on the review, suggestions for future research are likewise provided. Subsequently, machine learning and deep learning methods are considered to be among the most promising data-driven methodologies. The review may be useful for academicians, researchers, and practitioners for a better understanding of data-driven heuristic approaches to transportation and logistics problems. [ABSTRACT FROM AUTHOR]

The sole diagram in On the Origin of Species is generally considered to be merely an illustration of Darwin's ideas, but such an interpretation ignores the fact that Darwin himself expressly stated that the diagram helped him to discover and express his ideas. This article demonstrates that developing the so-called "tree diagram" substantially aided Darwin's heuristics. This demonstration is based on an interpretation of the diagram and of 17 sketches found in Darwin's scientific papers. The key to this interpretation is the meaning that Darwin assigned to the graphic elements (points, lines, and spaces) he used to construct the preliminary sketches and the diagram. I argue that each of the sketches contributed to the shaping of Darwin's ideas and that, in their succession, each added new elements that ultimately resulted in the fully developed published diagram. [ABSTRACT FROM AUTHOR]

The exponential use of artificial intelligence (AI) to solve and automated complex tasks has catapulted its popularity generating some challenges that need to be addressed. While AI is a powerful means to discover interesting patterns and obtain predictive models, the use of these algorithms comes with a great responsibility, as an incomplete or unbalanced set of training data or an unproper interpretation of the models' outcomes could result in misleading conclusions that ultimately could become very dangerous. For these reasons, it is important to rely on expert knowledge when applying these methods. However, not every user can count on this specific expertise; non-AI-expert users could also benefit from applying these powerful algorithms to their domain problems, but they need basic guidelines to obtain the most out of AI models. The goal of this work is to present a systematic review of the literature to analyze studies whose outcomes are explainable rules and heuristics to select suitable AI algorithms given a set of input features. The systematic review follows the methodology proposed by Kitchenham and other authors in the field of software engineering. As a result, 9 papers that tackle AI algorithm recommendation through tangible and traceable rules and heuristics were collected. The reduced number of retrieved papers suggests a lack of reporting explicit rules and heuristics when testing the suitability and performance of AI algorithms. [ABSTRACT FROM AUTHOR]

Abstract: Online medical information, when presented to clinicians, must be well-organized and intuitive to use, so that the clinicians can conduct their daily work efficiently and without error. It is essential to actively seek to produce good user interfaces that are acceptable to the user. This paper describes the methodology used to develop a simplified heuristic evaluation (HE) suitable for the evaluation of screen shots of Web pages, the development of an HE instrument used to conduct the evaluation, and the results of the evaluation of the aforementioned screen shots. In addition, this paper presents examples of the process of categorizing problems identified by the HE and the technological solutions identified to resolve these problems. Four usability experts reviewed 18 paper-based screen shots and made a total of 108 comments. Each expert completed the task in about an hour. We were able to implement solutions to approximately 70% of the violations. Our study found that a heuristic evaluation using paper-based screen shots of a user interface was expeditious, inexpensive, and straightforward to implement. [Copyright &y& Elsevier]

Psychologists have identified heuristics and biases that can cause people to make assumptions about factors that contribute to the success of individuals and firms, whose outcomes may have actually resulted primarily from randomness. Yet the interpretation of these biases becomes ambiguous when they represent reasonable cognitive shortcuts that offer certain advantages. This paper addresses this ambiguity by presenting four versions (weak, semi-weak, semi-strong, strong) of a normative theory of luck that integrates insights from psychology with the chance model approach to predict the circumstances under which performance non-monotonicity occurs: higher performance may not only indicate greater luck, but also lower expected merit or quality. The semi-strong version is illustrated by examining the decoupling of citations of academic publications and their impact, illuminating when higher citations indicate lower quality. We conclude by discussing the broader implications of a normative theory of luck, emphasizing strategies to address situations where people mistake luck for skill. [ABSTRACT FROM AUTHOR]

Active learning has become an increasingly popular method for screening large amounts of data in systematic reviews and meta-analyses. The active learning process continually improves its predictions on the remaining unlabeled records, with the goal of identifying all relevant records as early as possible. However, determining the optimal point at which to stop the active learning process is a challenge. The cost of additional labeling of records by the reviewer must be balanced against the cost of erroneous exclusions. This paper introduces the SAFE procedure, a practical and conservative set of stopping heuristics that offers a clear guideline for determining when to end the active learning process in screening software like ASReview. The eclectic mix of stopping heuristics helps to minimize the risk of missing relevant papers in the screening process. The proposed stopping heuristic balances the costs of continued screening with the risk of missing relevant records, providing a practical solution for reviewers to make informed decisions on when to stop screening. Although active learning can significantly enhance the quality and efficiency of screening, this method may be more applicable to certain types of datasets and problems. Ultimately, the decision to stop the active learning process depends on careful consideration of the trade-off between the costs of additional record labeling against the potential errors of the current model for the specific dataset and context. [ABSTRACT FROM AUTHOR]

This paper explores the following questions: What is reading all about, as our technical milieu becomes increasingly digital and our reading increasingly automated? What is entailed in closely reading a book, in studying and handling the book as an object? And what is the role of philosophy—and in reading philosophy—as we grapple with new technical modes of reading? Guided by philosopher Gilbert Simondon, this paper compares the language heuristics of large language models (LLM) with human reading practices, revealing parallel and diverging technical tactics, with the aim of increasing our understanding of how and why these algorithms are part of our technical reality. This comparison moves beyond concerns with automation and alienation, using Simondon's notions of technicity and transindividuality to philosophically analyze the nature of collaborative reading in a distraction economy, and the extent to which transformer neural network models achieve an implicit embodied or grounded sense of language-use. [ABSTRACT FROM AUTHOR]

The presented scientific paper arises mainly in the context of solving current issues, problems of theory and practice of entrepreneurship. In particular, in the field of dispositional solutions, dimensions of the formation of normative basis of sustainable development in the field of production and logistics. It is an expression and continuation of the previous opinion, thought march, experiential expression of the authors on the issue. It focuses mainly on the current challenges associated with the development management of production and logistics, on the parameters that will need to be respected and, to a greater extent, applied in the future. It is also a response to the fact in the sense that the results of research, predispositions in the field are insufficient. Especially in terms of the approach to solving the problems of the normative base, not only in the responsible authorities, institutions in this area, but also in the business units themselves. [ABSTRACT FROM AUTHOR]

The generation of test vectors is a key technique that affects the efficiency and fault detection rate of the boundary scan test. Aiming at the local optimal solution problem of the current common test vectors generation algorithm, this paper proposes a test vectors generation algorithm based on improved GA-AO* model, through which the test vectors are generated by using the idea of heuristic search and backtracking correction. In order to speed up the heuristic search, this paper designed a heuristic function with both prior and posterior parameters to describe the influence of typical faults on the failure probability index of the test vectors. At the same time, this paper used a genetic algorithm (GA) to determine the specific values of the posterior parameters iteratively. Finally, through theoretical analysis and physical verification, compared with the test vector generated by the traditional method, the test vector generated by this method is optimized on the prior failure probability index and performs better in the physical experiment. [ABSTRACT FROM AUTHOR]

This paper addresses waste collection problems in which urban household and solid waste are brought from waste collection points to waste disposal plants. The collection of waste from the collection points herein is modeled as a multi-depot vehicle routing problem (MDVRP), aiming at minimizing the total transportation distance. In this study, we propose a heuristic solution method to address this problem. In this method, we firstly assign waste collection points to waste disposal plants according to the nearest distance, then each plant solves the single-vehicle routing problem (VRP) respectively, assigning customers to vehicles and planning the order in which customers are visited by vehicles. In the latter step, we propose the sector combination optimization (SCO) algorithm to generate multiple initial solutions, and then these initial solutions are improved using the merge-head and drop-tail (MHDT) strategy. After a certain number of iterations, the optimal solution in the last generation is reported. Computational experiments on benchmark instances showed that the initial solutions obtained by the sector combination optimization algorithm were more abundant and better than other iterative algorithms using only one solution for initialization, and the solutions with distance gap were obtained using the merge-head and drop-tail strategy in a lower CPU time compared to the Tabu search algorithm. [ABSTRACT FROM AUTHOR]

In this paper, we present an algorithm that solves a paper reel layout problem where the available space is divided into equal-size cells. The problem is to find a layout with the minimum transportation cost subject to adjacency and other constraints. A genetic algorithm is used in a two-stage iterative approach to solve the problem. Computational results seem to indicate the efficiency and effectiveness of the proposed solution method. [ABSTRACT FROM AUTHOR]

Recent geometric approaches to visual‐inertial odometry have shown impressive accuracy with real‐time performance in autonomous tracking applications in several fields including virtual and augmented reality (VR & AR) as well as robotics. But these methods are still not robust to challenging conditions due to their dependence on hand‐engineered features, heuristics, sensor calibration and manual synchronization (when using visual and inertial sensors). In this paper, we review the recent advances in deep learning based approaches to odometry and identify some future research directions. [ABSTRACT FROM AUTHOR]

Research on dynamic capabilities (DCs) has focused primarily on reactive DC deployment (i.e., opportunity discovery) with less attention being paid to proactive DC deployment (i.e., opportunity creation). Drawing on the opportunity creation perspective in entrepreneurship, we argue that proactive DC deployment is characterized by uncertainty, which makes deductive reasoning less effective and thus requires the use of heuristic reasoning. We also incorporate the evolutionary logic of variation, selection, and retention to theorize about the role of heuristic reasoning in the process of proactive DC deployment. Specifically, we integrate the concept of ecologically rational heuristic reasoning to answer two key questions: First, how does ecologically rational heuristic reasoning facilitate proactive DC deployment when the decision context is uncertain? Second, why is ecologically rational heuristic reasoning effective for proactive DC deployment? In summary, our paper advances the ongoing debate concerning DCs and the way in which heuristic reasoning assists a firm in deploying such capabilities. [ABSTRACT FROM AUTHOR]

Presents the last paper of writer Nicholai Aleksandrovitch Bernstein on neurophysiology. Purpose of the paper; Revelation of the heuristic typical of Bernstein; Parting message.

This paper proposes a hybrid algorithm to tackle a real-world problem arising in the context of pulp and paper production. This situation is modelled as a production problem where one has to decide which wood will be used by each available processing unit (wood cooker) in order to minimize the variance of wood densities within each cooker for each period of the planning horizon. The proposed hybrid algorithm is built around two distinct phases. The first phase uses two interacting heuristic methods to identify a promising reduced search space, which is then thoroughly explored in the second phase. This hybrid algorithm produces high-quality solutions in reasonable computation times, especially for the largest test instances. Extensive computational experiments demonstrated the robustness and efficiency of the method. [ABSTRACT FROM AUTHOR]

To address the issue of intelligent ship route planning, a ship planning method based on the improved D* Lite algorithm is proposed. Firstly, a navigation environment grid map is constructed using the acquired meteorological and hydrological datasets. The grids are divided into navigable and non-navigable according to navigation requirements, and a route planning model is built. Secondly, the heuristic function and the path function of the D* Lite algorithm are improved. The heuristic function is optimized and weighted, and a risk factor is introduced into the path function to enhance efficiency of path planning while maintaining a safe distance between the planned route and obstacles. Finally, by dynamically adjusting the search step length and the selectable directions of the D* Lite algorithm, the number of waypoints is reduced, and the voyage of the planned route is shortened, resulting in a smooth and collision-free route of ships. The effectiveness of the proposed algorithm is verified through three sets of simulation experiments. The simulation results show that the proposed method in this paper is more suitable for ship route planning and ship maneuvering in practice and can effectively avoid non-navigable grids while optimizing path length, path smoothness, and computation time, making the routes more aligned with actual navigation tasks. [ABSTRACT FROM AUTHOR]

The RRT*-Connect algorithm enhances efficiency through dual tree bias growth, yet this bias can be inherently blind, potentially affecting the algorithm’s heuristic performance. In contrast, the Informed RRT* algorithm narrows the planning problem’s scope by leveraging an informed region, thereby improving convergence efficiency towards optimal solutions. However, this approach relies on the prior establishment of feasible paths. Combining these two algorithms can address the challenges posed by Informed RRT while also accelerating convergence towards optimality, albeit without resolving the issue of blind bias in dual trees.In this paper, we proposed a novel algorithm: Dynamic Informed Bias RRT*-Connect. This algorithm, grounded in potential and explicit informed bias sampling, introduces a dynamical bias points set that guides dual tree growth with precision objectives. Additionally, we enhance the evaluation framework for algorithmic heuristics by introducing two innovative metrics that effectively capture the algorithm’s characteristics. The improvements observed in traditional indicators demonstrate that the proposed algorithm exhibits greater heuristic compared to RRT*-Connect and Informed RRT*-Connect. These findings also suggest the viability of the new metrics introduced in our evaluation framework. [ABSTRACT FROM AUTHOR]

This paper analyses a novel two-step Monte Carlo simulation algorithm to estimate the weighted volume of a polytope of the form A ⁢ z ≤ T . The essential idea is to partition the columns of A into two categories – a lightweight category and a heavyweight category. Simulation is done in a two-step manner where, for every sample of the lightweight category variables we use multiple samples of the heavyweight category variables. Thus, the heavyweight category variables are oversampled with respect to the lightweight category variables and increasing samples of the heavyweight variables at the expense of the lightweight variables will lead to a more efficient Monte Carlo method. In this paper we present a fast heuristic approximate for estimating the optimal oversampling ratio and substantiate with experimental results which confirm the effectiveness of the method. [ABSTRACT FROM AUTHOR]

Cloud manufacturing (CMfg) is a new paradigm that has been known as a promising integrated technology in which distributed resources of manufacturing are integrated and transformed into manufacturing services and handled centrally. It permits multiple users to request services simultaneously by submitting required tasks to a manufacturing platform. The service composition and optimal selection (SCOS) is the fundamental issue of CMfg that aims to select appropriate services from available manufacturing cloud resources to complete the manufacturing task and satisfy the users. Surveying and analyzing the available studies on this NP-hard problem is highly desirable. Therefore, as far as we know, this paper is the first research that tries to investigate and discuss the CMfg-SCOS methods in a systematic way. In this regard, the selected studies have been classified into two distinct groups comprising multi-objective and single-objective techniques. Furthermore, this research provides a comprehensive investigation of the current articles and compares them from several aspects based on various factors such as QoS parameters, other criteria, their adopted datasets, simulation tools, and algorithms. Moreover, hot papers, journals, and authors in this field have been revealed. In addition, the open challenging and the lacks within this issue have been discussed which can be applied to upcoming research. [ABSTRACT FROM AUTHOR]

Constructing a 3D papercraft model from its unfolding has been fun for both children and adults since we can reproduce virtual 3D models in the real world. However, facilitating the papercraft construction process is still a challenging problem, especially when the shape of the input model is complex in the sense that it has large variation in its surface curvature. This paper presents a new heuristic approach to unfolding 3D triangular meshes without any shape distortions, so that we can construct the 3D papercraft models through simple atomic operations for gluing boundary edges around the 2D unfoldings. Our approach is inspired by the concept of topological surgery, where the appearance of boundary edges of the unfolded closed surface can be encoded using a symbolic representation. To fully simplify the papercraft construction process, we developed a genetic-based algorithm for unfolding the 3D mesh into a single connected patch in general, while optimizing the usage of the paper sheet and balance in the shape of that patch. Several examples together with user studies are included to demonstrate that the proposed approach works well for a broad range of 3D triangular meshes. [ABSTRACT FROM AUTHOR]

One way to measure the scientific progress of a country is to evaluate the curriculum vitae (CV) of its researchers. In Brazil, this is not different. The Lattes Platform is an information system whose primary objective is to provide a single repository to store the CV of the Brazilian researchers. This system is increasingly acquiring expressiveness as the main source of information regarding the Brazilian community of researchers, students, managers, and other actors in the national system of science, technology, and innovation. However, the integrity of this important tool for gaging the national bibliographic production may be affected by the effect of ambiguities or referential inconsistencies in coauthoring citations. A first step towards solving this problem lies in identifying such inconsistencies. For that, we propose a heuristic-based approach that uses similarity search to match papers from coauthors of CV. We then use this technique to analyze over 2000 curricula of researchers from a given institution recovered from the Lattes Platform. The results indicate 18.98% of the analyzed publications present referential inconsistencies, which is a significant amount for a dataset that is supposed to be correct and trustable. [ABSTRACT FROM AUTHOR]

Background: Possible solutions to overcome the many challenges of home delivery are collection and delivery points (CDPs). In addition to commercial facilities, the role of CDPs can also be played by users' households, providing a crowd storage service. Key decisions regarding CDPs relate to their location, as well as the allocation of users to selected locations, so that the distance of users from CDPs is minimal. Methods: In this paper, the described problem is defined as a p-median problem and solved for the area of the city of Belgrade, using the heuristic "greedy" and the simulated annealing algorithm. Results: Fifty locations of CDPs were selected and the users allocated to them were distributed in over 950 zones. The individual distances between users and the nearest CDPs and the sum of these distances, multiplied by the number of requests, were obtained. An example of modification of the number of CDPs is presented as a way of obtaining solutions that correspond to different preferences of operators and/or users in terms of their distances from the CDPs. Conclusions: User households can be used as CDPs to achieve various benefits. Locating CDPs, i.e., selecting households, can be solved as a p-median problem, using a combination of heuristic and metaheuristic algorithms. In addition, by modifying the number of medians, the total and average distances between users and CDPs can be better managed. The main contributions of the paper are the establishment of users' households as potential locations of CDPs, the establishment of a framework for analysis of impact of the number of CDPs on the sum and average distances from the customers, as well as the creation of a basis for upgrading and modifying the model for implementation in the business practice. [ABSTRACT FROM AUTHOR]

This paper discusses the selection and design of heuristic procedures for solving one-dimensional roll trim problems. These are well-defined combinatorial problems which are too large to optimize. Five different roll trim problems from the paper and film industries are described along with the heuristic procedures that have been used successfully to improve the quality of the solutions generated. The paper concludes with some general guidelines for developing "industrial-grade" heuristic problem solving procedures. [ABSTRACT FROM AUTHOR]

A traditional logistics decision model mainly studies the location decision of logistics distribution centers, storage inventory management, vehicle scheduling, and transportation routes. The logistics location-inventory-routing problem (LIRP) is an integrated optimization of the three problems—a comprehensive optimization problem for the whole logistics system. This review paper uses the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) method to review the literature on LIRP systematically. A total of 112 LIRP-related studies published between 2010 and 2021 are reviewed and classified based on 10 abstract and citation databases. The classification includes four aspects: problem characteristics, demand data types, model-based solutions, and application fields. From this systematic review, a few observations are recorded. First, the most popular problems among researchers are the multi-period multi-product problem, the multi-echelon single-link problem, and the multi-depot multi-retailer problem. Based on the objective function, the minimization of total supply chain cost is the primary concern of the LIRP literature. Researchers also favor other problem characteristics such as multi-objective programming, inventory control replenishment policy, and a homogeneous fleet of vehicles. We found that stochastic data are a common factor in an uncertain environment and have broad coverage. When dealing with the LIRP, heuristic and metaheuristic algorithms are the most widely used solution methodologies in the literature. In the application field of LIRP, the perishable products logistics network is mentioned in most applications. Finally, we discuss and emphasize the challenges of and recommendations for future work. This paper provides a systematic review of the literature on LIRP based on the PRISMA method, which contributes vital support and valuable information for researchers interested in LIRP. [ABSTRACT FROM AUTHOR]

Purpose: This paper proposes a theory-based process model for the generation, articulation, sharing and application of managerial heuristics, from their origin as unspoken insight, to proverbialization, to formal or informal sharing, and to their adoption as optional guidelines or policy. Design/methodology/approach: A conceptual paper is built using systematic and non-systematic review of literature. This paper employs a three-step approach to propose a process model for the emergence of managerial heuristics. Step one uses a systematic review of empirical studies on heuristics in order to map extant research on four key criteria and to obtain, by flicking through this sample in a moving-pictures style, the static stages of the process; step two adapts a knowledge management framework to yield the dynamic aspect; step three assembles these findings into a graphical process model and uses insights from literature to enrich its description and to synthesize four propositions. Findings: The paper provides insights into how heuristics originate from experienced managers confronted with negative situations and are firstly expressed as an inequality with a threshold. Further articulation is done by proverbialization, refining and adapting. Sharing is done either in an informal way, through socialization, or in a formal way, through regular meetings. Soft adoption as guidelines is based on expert authority, while hard adoption as policy is based on hierarchical authority or on collective authority. Research limitations/implications: The findings are theory-based, and the model must be empirically refined. Practical implications: Practical advice for managers on how to develop and share their portfolio of heuristics makes this paper valuable for practitioners. Originality/value: This study addresses the less-researched aspect of heuristics creation, transforms static insights from literature into a dynamic process model, and, in a blended-theory approach, considers insights from a distant, but relevant literature – paremiology (the science of proverbs). [ABSTRACT FROM AUTHOR]

This paper proposes a method to find an optimal T' with the most terminal of the subset of T' trees that can be connected by a given length by improving a memetic genetic algorithm within several constraints, when the set of terminal T is given to the Euclidean plane R2. Constraint (1) is that a given length cannot connect all terminals of T, and (2) considers only the rectilinear layout of the edge connecting each terminal. The construction of interconnections has been used in various design-related areas, from network to architecture. Among these areas, there are cases where only the rectilinear layout is considered, such as wiring paths in the computer network and VLSI design, network design, and circuit connection length estimation in standard cell deployment. Therefore, the heuristics proposed in this paper are expected to provide various cost savings in the rectilinear layout. [ABSTRACT FROM AUTHOR]

Key of development for OLED devices is compatibility between organic materials. Therefore, the construction of the materials' properties DB should be followed in order to advance characterization and prediction of the OLED device. In particular, it is necessary to build a number of organic materials DB unlike the conventional Si‐based homo‐junction and alloy changing only heterojunction. So, it should be built based on the organic material parameters, SIMDB (Simulation DB), it is possible to predict and optimize driving voltage and efficiency characteristics for OLED devices. However, the skilled Engineer gets to decide on the simple repeat operation and time consumption for calibrating the material parameter/structure (4~5 layer device based on 20,000 times or more). In order to solve such problems, this paper presents an automatic optimization for electro‐optical characteristics of OLED device. The proposed method and tool are based on a unique heuristic algorithm, which is obtained from accumulated manual calibration experience. In other words, the convergence know‐how is applied random search algorithm and heuristic algorithm were constructed in‐house optimizer enables automated extraction of OLED properties. Finally, by utilizing the built SIMDB is expected to various factors affecting the OLED elements is optimized to be analyzed and prior prediction. [ABSTRACT FROM AUTHOR]

Dividend policy is one of the most discussed and controversial topics in corporate finance for decades. Due to the increase of computational power, few scholars tried to find most informative determinants with the help of advanced heuristic methods, a.k.a. Machine Learning. However, some critiques need to be addressed regarding the metric scores, model selection or robustness of their approaches. This paper proposes a working methodology that deals with these critiques. A Principal Components Analysis as well as numerous ML models, resample techniques and metric scores have been applied in order to better understand the dividend puzzle. The conclusions suggest that the size of the companies is the most informative determinant, larger and less risky firms being more likely to pay dividends. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to evaluate and structure the basic heuristics consumers use in evaluating word-of-mouth (WOM) about luxury hotel brands while analyzing the impact of deception in online consumer reviews. Design/methodology/approach: The research used a two-study mixed-methods approach, using interpersonal deception theory and social proof theory as lenses to conduct our analysis. For the first study, a qualitative conceptual mapping analysis was conducted, examining online consumer reviews to identify key concepts and their relationships in the context of luxury hotel brands. In the second study, the themes were further examined using a fuzzy-set qualitative comparative analysis to analyze their causal complexity and association between variables to determine how they influence the perceived helpfulness of online reviews for luxury hotel brands. Findings: The results underline the importance of functional, objective variables, such as the number of reviews and stars, as social proof heuristics and other factors, including clout, authenticity and analytic tone, as interpersonal communication heuristics. Therefore, consumers use a combination of social and interpersonal communication heuristics to extract information from reviews and manage deception risk. Research limitations/implications: The paper contributes to the consumer–brand relationship literature by assessing the heuristics consumers use in evaluating online reviews and provides additional information for research in online reputation management. Practical implications: This study's results can help marketing practitioners and brand managers manage their online reputations better. It can also aid managers in improving their messaging on hotel websites to entice consumers to complete bookings. Heuristics play an essential role in such messaging and understanding them can help marketers appeal directly to their target market. Originality/value: This study contributes to the literature on consumer–brand relationships by providing a framework of heuristics that consumers use when evaluating luxury service brands and contributes to WOM and online reputation research by highlighting factors that may make online reviews more helpful. [ABSTRACT FROM AUTHOR]

As near-surface mineral resources are being depleted, mining operations are focused on deepening. Rising environmental concerns prefer underground mining methods because their footprint is less than that of surface mining methods. Among the underground mining methods, block caving is a method with low operating costs and comparable production rate to open-pit mines. Mine design and planning optimization is performed to ensure the optimal use of mineral resources with minimal possible extraction costs. Stope boundary optimization is vital in the underground mining planning process, and numerous algorithms have been proposed in that regard. The floating stope algorithm is the most widely used algorithm which is presented for those mining methods where selective mining is possible. This paper tries to apply the floating stope algorithm for stope boundary optimization in the case of block caving. In that regard, a framework is discussed to determine the input parameters of the floating stope algorithm that are suited for block caving including minimum block size, floating ranges, and cutoff grade. These parameters are defined to customize the floating stope algorithm for the block caving method. Then the customized algorithm is applied to optimize the boundary of the underground block caving stope. Then, the corresponding undercut level is determined using the "effective cross-section" heuristic. The procedure is applied in the Songun copper mine. Based on the results, the minable reserve is 617 million tons with an average copper grade of 0.53%. [ABSTRACT FROM AUTHOR]

One of the most widely used robust regression methods for solving simple linear regression problems is the Theil-Sen (TS) estimator. This estimator has some notable advantages; however, it does not belong to the most robust estimation methods (called high-breakdown estimators) and is prone to outliers whose distribution is highly asymmetric with respect to the correct data points. This paper presents a modification of the TS estimator, the Robustified Theil-Sen (RTS) estimator. The new method uses a heuristic-based selection procedure to reduce the number of initial estimates of the regression function parameters computed with at least one outlier, thereby improving the regression results. The use of this heuristic procedure only slightly increases the computational time required for using the RTS estimator compared to the TS estimator. Preliminary results of two numerical experiments presented in the paper show that the RTS estimator outperforms other comparable estimators, i.e., the TS estimator and the repeated median estimator, in terms of robustness. The results presented also suggest that the breakpoint value (which is a measure of the robustness of estimators) of the RTS estimator is higher than the breakpoint value of the TS estimator and equal to the breakpoint value of the high-breakpoint estimators. [ABSTRACT FROM AUTHOR]

This paper focuses on the problem of dynamic target search in a curve-shaped area by an unmanned aerial vehicle (UAV) with an optical camera. Our objective is to generate an optimal path for UAVs to obtain the maximum detection reward by a camera in the shortest possible time, while satisfying the constraints of maneuverability and obstacle avoidance. First, based on prior qualitative information, the original target probability map for the curve-shaped area is modeled by Parzen windows with 1-dimensional Gaussian kernels, and then several high-value curve segments are extracted by density-based spatial clustering of applications with noise (DBSCAN). Then, given an example that a target floats down river at a speed conforming to beta distribution, the downstream boundary of each curve segment in the future time is expanded and predicted by the mean speed. The rolling self-organizing map (RSOM) neural network is utilized to determine the coverage sequence of curve segments dynamically. On this basis, the whole path of UAVs is a successive combination of the coverage paths and the transferring paths, which are planned by the Dubins method with modified guidance vector field (MGVF) for obstacle avoidance and communication connectivity. Finally, the good performance of our method is verified on a real river map through simulation. Compared with the full sweeping method, our method can improve the efficiency by approximately 31.5%. The feasibility is also verified through a real experiment, where our method can improve the efficiency by approximately 16.3%. [ABSTRACT FROM AUTHOR]

This paper puts forward a conceptual framework to support the dual challenges of strategic and practical integrative action of Education for Sustainable Development (ESD) across Higher Education Institutions (HEIs). There are numerous existing resources and toolkits providing appropriate actions, guidance or approaches to monitor and measure ESD engagement. Our intended distinctive contribution in this paper is to complement these with heuristic ways of thinking that offer clarity on the context and evolution of progress on ESD at an institutional level. Our proposals were developed through structured comparative discussions by ESD practitioners from seven European universities, leading to a consensus view on key contextual influences across a range of environments, embodied in our proposed heuristic metaphors. The resulting proposed framework, built upon a systems-based visual metaphor of a forest ecosystem of HEIs, proposes the use of the dimensions of capacity and commitment, to define an integrative framework with four positional scenarios: "Pockets of Practice", "Emerging Agenda" to "Integrated Impact" and "Off the Agenda". To illustrate its application, it is used to contextualize relevant steps to progress ESD associated with each scenario in the areas of strategy, staff development, formal education and extra-curricular opportunities. We argue that the adoption of such a framework by HEI practitioners could support day-to-day decision-making and strategic planning towards an integrated approach to ESD that engages with all areas of university activity. [ABSTRACT FROM AUTHOR]

Shaded conditions cause a decrease in the performance of photovoltaic (PV) systems. In this situation, the power versus voltage curve shows two maximum power points, namely local (LMPP) and global (GMPP). The main challenge for extracting the maximum power from a PV system during shading conditions is the existence of a false maximum or LMPP along with a true maximum or GMPP. Traditional maximum power point tracking (MPPT) has faced hurdles in overcoming the situation. Therefore, this paper describes the implementation of Queen Honey Bee Migration (or QHBM for short) to track GMPP of PV systems, which called QHBM MPPT. The highlight of this paper is the simulation results of QHBM MPPT on PV systems under various shading conditions. We implemented QHBM MPPT on a boost converter installed on a 1200 Wp PV system. We conducted a simulation using MATLAB® with five scenarios which aim to show the various shadows that PV systems might encounter in reality. The MPPT QHBM is tested repeatedly and then the average value is taken to measure performance in MPP tracking. The average value is used to calculate tracking efficiency, number of iteration or convergence time. We also compared QHBM with other methods, namely incremental conductance (IC) and Particle Swarm Optimization (PSO). The results obtained show that the QHBM and PSO MPPTs outperform the IC MPPT in terms of efficiency, convergence time and the number of iterations. IC MPPTs oscillate under shading conditions since no knowledge of GMPP. Both PSO and QHBM MPPTs know GMPP from scouts or particles, respectively. Therefore, PSO and QHBM MPPTs are better than IC MPPT in various shading cases. [ABSTRACT FROM AUTHOR]