Reverse Task Research Articles

Algebraic reasoning in years 5 and 6: classifying its emergence and progression using reverse fraction tasks

This paper builds on our previous research and investigates how students’ fractional competence and reasoning can provide clear evidence of non-symbolic algebraic thinking and its progressive transition towards fully generalised algebraic thinking. In a large-scale study, 470 primary students completed a written paper and pencil test. This included three reverse fraction tasks which required students to find an unknown whole when presented with a quantity representing a fraction of that whole. Seventeen students from one participating primary school undertook a semi-structured interview which included reverse fraction tasks, similar to those on the written test, but with progressive levels of abstraction, starting with particular instances and becoming more generalised. Two important products of the study are the Classification Framework for Reverse Fraction Tasks and the Emerging Algebraic Reasoning Framework. The interview results highlight two critical transition points for the emergence of students’ algebraic reasoning. The first is the ability to transition from additive strategies to multiplicative strategies to solve reverse fraction problems. Students reliant on diagrams and additive strategies struggled to solve more generalised tasks that required multiplicative rather than additive strategies. The second transition is the shift from multiplicative thinking to algebraic reasoning where students could generalise their multiplicative knowledge to deal with any quantity represented in a reverse fraction task.

Effects of environmental enrichment on exploratory behavior, win-stay and lose-shift performance, motor sequence learning, and reversal learning during the three-lever operant task in mice

Beneficial effects of environmental enrichment (EE) on the central nervous system have been demonstrated. Although the effects of EE on spatial learning have been extensively studied, studies on reward-based motor learning are limited. In this study we examined the effects of EE on the performance of operant tasks using three levers (A–C). Mice were divided into two groups and housed either in the control condition or in the physical EE condition. The mice were trained in three types of operant tasks in sequence. First, mice were trained to press one of the active levers for a food reward (one-lever task). Second, mice were trained to press the three levers in the order of A, B, and C (three-lever task). Third, the lever order was reversed to C, B, and A (reverse three-lever task). We found some behavioral differences between control and EE mice. When all three levers were active in the one-lever task, mice tended to press the three levers equally at first, then shifted to press one lever preferentially. This behavioral shift from exploration to exploitation was delayed in EE mice. When only one lever was active, EE mice showed a higher lose-shift performance. In the three-lever and reverse three-lever tasks, EE mice pressed three levers more often and acquired more food rewards, compared to control mice, although the success rate in both tasks was not different between the two groups. These behavioral features observed in EE mice (higher lose-shift performance and higher trial and error activity) might be advantageous when circumstances are not stable.

Why are some inhibitory tasks easy for preschool children when most are difficult? Testing two hypotheses

Understanding the processes that create inhibitory demands is central to understanding the role of inhibitory control in all aspects of development. The processes that create inhibitory demands on most developmental tasks seem clear and well understood. However, there is one inhibitory task that appears substantially easier than the others: the Reverse Categorization task, in which children are asked to “reverse sort” items (e.g., put large items in a small box and put small items in a large box). This finding is both surprising and problematic because it cannot be explained by any existing account of inhibitory development. Four experiments with 3- and 4-year-olds sought to explain why the Reverse Categorization task is easy. Two experiments (N = 64) investigated the hypothesis that children conceptualize the task in a way that reduces its inhibitory demands; and two experiments (N = 56) tested the hypothesis that the task is easier because children sort items slowly. The data indicate that children spontaneously respond more slowly on the Reverse Categorization task than on other inhibitory tasks and that this slowing reduces the task’s cognitive demands. The way in which slowed responding works, and its relation to other inhibition-reducing interventions, is discussed.

Reckless gambles and responsible ventures: Racialized prototypes of risk-taking.

Risk-taking is sometimes admired and sometimes disparaged. In this research, we examine previously unexplored questions concerning how membership in social groups is related to expectations and perceptions of risk-taking. We propose that prototypes of risk-takers incorporate racial associations. We conducted five studies (NTotal = 1,603, predominantly White residents of the United States) examining whether prototypes of risk-takers-primarily reckless and responsible ones-activate racial stereotypes and discrimination. We first focused on whether participants perceive Black (vs. White) men as more likely to engage in risk-taking, broadly construed (Study 1). Next, we tested whether the trait attributions (Studies 2 and 3) and mental images constructed with the reverse correlation task (Study 3) of reckless risk-takers are more stereotypically Black (and less White) than responsible risk-takers. In Study 4, we employed an investment game to investigate participants' willingness to trust targets we depicted using the racialized mental images of reckless and responsible risk-takers derived from Study 3. A final study examined whether thinking about reckless risk-takers evokes Black stereotypes broadly, including even positive stereotype content. Findings confirmed that reckless risk-takers were imagined as more phenotypically Black and as having more stereotypically Black traits (both positive and negative), compared with responsible risk-takers. Theoretical and practical implications for this novel stereotype content in the domain of risk are discussed. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Binary code traceability of multigranularity information fusion from the perspective of software genes

Binary code traceability aims to use the relevant characteristics of anonymous binary codes to identify concealed authors or teams and replace error-prone and time-consuming manual reverse engineering tasks with automated systems. Although significant progress has been made in source code traceability technology, research on tracking binary files is still limited. Hence, we propose a feature extraction method and deep learning model that exploit the sequence and structure information of binary codes to identify the authors of anonymous and malicious binary codes and their relations with other known binary code families. We further propose a new multigranularity information fusion feature based on biological genes oriented to the traceability of binary codes. The evaluations conducted on the Google Code Jam (GCJ) dataset indicate that our method can accurately trace the binary code from 1000 people to the target author with an accuracy rate of 71%. Further, experimental results verify the robustness of the proposed model. For malicious code datasets, in particular, the proposed method achieved a stable traceability accuracy rate for malicious samples using only a small number of training samples. For the problem of malicious code tracking, in 300 team organizations, the proposed method achieved a code-tracing accuracy rate of 82%.

Метод восстановления протокольных автоматов по бинарному коду

Security analysis of network programs includes set of reverse engineering tasks of network protocols. Data formats restoring and implemented protocol automaton are the previous task issues. Unlike quite researched problem of formats restoring where there are lots of scientist’s papers, finding out the protocol's automaton program implementation looks like terra incognita and the cornerstone is a protocol state description currently undefined. There are two general ways to retrieve the implemented protocol automaton: an analysis of the network traces and looking into binary trace of the target application. This article offers a second one method. The first aim of the paper is the way to describe a mathematical model of a protocol automaton and a method for projecting it onto an executing application binary code. The second is concept of the protocol state definition and a principle to detect the states transitions based on some "global" binary trace objects, are described. Thirdly, there is suggested a protocol automaton precising manner by in-memory fuzzing based on a "floating" fork-server to manage states transitions. Finally, developed toolset's scheme and experiments on its using with a real VPN client, are shown.

Adaptive Path-Following Control for Autonomous Semi-Trailer Docking

Maneuvering a truck-trailer system while docking is extremely challenging. This article aims to alleviate this problem by presenting an enhanced path-following control framework for autonomous semi-trailer docking. In the proposed system, adaptive controllers that utilize gain scheduling are introduced for forward and reverse path-following tasks in docking maneuvers to increase the robustness and path-following performance. The system includes an improved pure pursuit controller with adaptive look-ahead distance for forward path following; a cascade controller of reverse pure pursuit and a gain-scheduled LQ control for reverse path-following. In the evaluation of the path-following performance of forward and reverse controllers, the closed-loop system of path-following controllers with the truck-trailer kinematic model is simulated in MATLAB/Simulink for various test cases, and the results are compared with those of other studies. Furthermore, different docking scenarios are generated via the cascade path planning algorithm for autonomous semitrailer docking. These are tested with a high degree semi-trailer model within the IPG TruckMaker simulation environment, and with a full truck-trailer vehicle in the test field. The results of both simulations and physical testing clearly demonstrate improvements in terms of the control problem formulation, i.e., the stabilized path-following is obtained with acceptable path-following errors.

What constitutes a compassionate response? The important role of culture.

American compassionate responses (i.e., sending sympathy cards) focus more on the positive (e.g., comforting memories) and less on the negative (e.g., the pain of someone's death) than German compassionate responses, partly because of cultural differences in how much people want to avoid feeling negative (i.e., avoided negative affect [ANA]). However, are these culture-specific compassionate responses considered more comforting and compassionate within their respective cultural context? We predicted that Americans would find responses that focus on the negative less and those that focus on the positive more comforting and compassionate than Germans will and that ANA would mediate these differences. In Study 1, 152 Americans and 315 Germans reported their ANA and rated how comforting they considered receiving different sympathy cards. As predicted, Americans found sympathy cards that contained negative content less and cards that contained positive content more comforting than Germans did. In Studies 2a and 2b, to examine whether these culture-specific conceptualizations of a comforting response would generalize to how people conceptualize a compassionate face, 118 Americans and 80 Germans selected stimuli that most resembled a compassionate (or happy) face using a reverse correlation task. As predicted, people's mental representation of a compassionate face contained more happiness/less sadness in an American than German context. Across studies, ANA partially mediated the cultural differences. This research demonstrates that responses that are intended to be compassionate might not be considered equally compassionate and comforting across cultures, which has implications for relief efforts, which are often organized internationally. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Perceptual Learning of Object Recognition in Simulated Retinal Implant Perception - The Effect of Video Training.

PurposeRetinal implants (RIs) provide new vision for patients suffering from photoreceptor degeneration in the retina. The limited vision gained by RI, however, leaves room for improvement by training regimes.MethodsTwo groups of normal-sighted participants were respectively trained with videos or still images of daily objects in a labeling task. Object appearance was simulated to resemble RI perception. In Experiment 1, the training effect was measured as the change in performance during the training, and the same labeling task was conducted after 1 week to test the retention. In Experiment 2 with a different pool of participants, a reverse labeling task was included before (pre-test) and after the training (post-test) to show if the training effect could be generalized into a different task context.ResultsBoth groups showed improved object recognition through training that was maintained for a week, and the video group showed better improvement (Experiment 1). Both groups showed improved object recognition in a different task that was maintained for a week, but the video group did not show better retention than the image group (Experiment 2).ConclusionsTraining with video materials leads to more improvement than training with still images in simulated RI perception, but this better improvement was specific to the trained task.Translational RelevanceWe recommend videos as better training materials than still images for patients with RIs to improve object recognition when the task-goal is highly specific. We also propose here that achieving highly specific training goals runs the risk of limiting the generalization of the training effects.

Information supply of the power control system of the synchronous generator of the autonomous wind unit

This paper deals with information supply of automatic maximum power control system of synchronous hybrid excited genera-tor for the autonomous wind unit. The power supply system based on an autonomous wind turbine consists of an electric generator, a battery charging controller, a battery pack and an inverter, which provides the required frequency and valueof the consumer's supply voltage.Three phase permanent magnet synchronous generator that have high technical and economic indicators are most widely used as electric generator of autonomous wind turbines.The main disadvantage of these generators is the lack of effective methods of magnetic flux control, limiting the optimization of the energy balance of the wind turbine.The paper discusses the application of synchronous generator with hybrid excitation system that consists of permanent magnets and additional field excitation winding lo-cated on the stator. Mathematical model of a hybrid excited synchronous generator is presented. Also,an output maximum power control system in a case of wind speed change by varying field excitation current is developed. Control system is developed based on concept of reverse task of dynamics in combination with minimization of local functionals of instantaneous values of energies.In the basics of the control method is put an idea of the reversibility of the Lyapunov direct method for the stability analysis.Obtained con-trol law provides thesystem stability inwhole, which allows solving control tasks of interrelated objects via mathematical models of local loops. Control law also provides low sensitiveness to parametric disturbances and gives dynamic decomposition of interrelated non linear system that ensures its practical implementation. The study of the proposed power control system based on parameters of hybrid excited synchronous generatorexperimental sample has been carried out. The graphs of transient process of armature power, voltage and current in a case of wind speed change from 3 to 8 m/s were obtained, as well as in a case of active resistance load change. The results of study showed high efficiency of power control of a wind turbine with hybrid excited synchronous generator.

The possibility of physical implementation of active vibration reduction

This work presents non-classical method of design of mechanic systems with subsystem reducing vibrations. The purpose of this paper is also introduces synthesis of mechanic system with reducing vibrations understand as design of this type of systems. This work presents method of reduction unwanted vibration by using mechanical elements, electrical elements, magnetorheological damper ect. The use of such a method enables the analysis and synthesis of mechanical systems irrespective of the type and number of the elements of such a system. The purpose of this paper is also introduces synthesis of mechanical system which is the reverse task of dynamics. The result of synthesis is obtaining system meeting the defined requirements. The system was consisted from mechanical elements and sub-system realized by many types of elements. This subsystem is an active or semiactive subsystem which enables overcoming limitations which occur if passive elements are used. The majority of vibration occurring in devices and machines is harmful and has a disadvantageous effect on their condition. Harmful impact of vibration is caused by the occurrence of increased stresses and the loss of energy, which results in faster wear machinery. Introduced in this work approach adopted makes it possible to undertake actions aiming at the elimination of phenomena resulting in the unwanted operation of machinery or generation of hazardous situations in the machinery environment. Thank to the approach, can be conducted as early as during the designing of future functions of the system as well as during the construction of the system.

Identifying Adverse Drug Events by Relational Learning

The pharmaceutical industry, consumer protection groups, users of medications and government oversight agencies are all strongly interested in identifying adverse reactions to drugs. While a clinical trial of a drug may use only a thousand patients, once a drug is released on the market it may be taken by millions of patients. As a result, in many cases adverse drug events (ADEs) are observed in the broader population that were not identified during clinical trials. Therefore, there is a need for continued, postmarketing surveillance of drugs to identify previously-unanticipated ADEs. This paper casts this problem as a reverse machine learning task, related to relational subgroup discovery and provides an initial evaluation of this approach based on experiments with an actual EMR/EHR and known adverse drug events.

Effects of High-Sucrose and High-Saturated Fat Diets on Learning Abilities in Old Sprague-Dawley Rats

With an increase in longevity, many studies have explored the influences of different lifestyle factors on successful aging. This study hypothesizes that older rats fed with a nutritionally balanced standard diet would perform better on learning tasks than rats fed with either a high-sucrose or a high-saturated fat. It also hypothesizes that older rats fed with a high-sucrose diet would perform better than those fed with a high-saturated fat. The learning abilities of the 15-month-old rats (N = 36) were assessed by conducting forward and reverse learning tasks using a T-maze apparatus. The results showed that rats on a nutritionally balanced diet performed significantly better on both learning tasks than those on either the high-sucrose or the high-saturated fat (p’s < .05). This may be due to the fact that the high-sucrose and high-saturated fat diets exacerbated a cognitive decline in geriatric rats. There was no significant difference between the learning abilities of the rats on a high-sucrose or high-saturated fat diet (p’s > .05). This finding suggests that, at an older age, both high-sucrose and high-saturated fat diets have a similarly detrimental influence on cognitive health.

Application of Selected Reverse Engineering Procedures Based on Specific Requirements

Abstract The paper describes a solution of reverse engineering tasks using the equipment of the laboratory of the Technical University in Zvolen. The first task was linked to evaluation of a wear rate of the tool used to for mulching and elimination of unwanted wood or weed vegetation. The obtained data will be used as a base line for determination of the time interval for the tool replacement. We developed a prototype of components and their drawing documentation for a single-purpose machine for cutting barley. We created the 3D model using the method of photogrammetry. The finished drawing documentation and prototypes were handed over to the company KRUP. Finally, we identified the most suitable procedures for creating a model of a part with a complex shape. We tested the techniques of editing the point cloud processing, as well as of smoothing the surfaces and automating the creation of partial geometric elements of the model. Based on the properties of the component, which is the starting point of the entire reverse engineering process and from the achieved results, we set recommendations for the selection of appropriate procedures.

Crack Detection in Images of Masonry Using CNNs.

While there is a significant body of research on crack detection by computer vision methods in concrete and asphalt, less attention has been given to masonry. We train a convolutional neural network (CNN) on images of brick walls built in a laboratory environment and test its ability to detect cracks in images of brick-and-mortar structures both in the laboratory and on real-world images taken from the internet. We also compare the performance of the CNN to a variety of simpler classifiers operating on handcrafted features. We find that the CNN performed better on the domain adaptation from laboratory to real-world images than these simple models. However, we also find that performance is significantly better in performing the reverse domain adaptation task, where the simple classifiers are trained on real-world images and tested on the laboratory images. This work demonstrates the ability to detect cracks in images of masonry using a variety of machine learning methods and provides guidance for improving the reliability of such models when performing domain adaptation for crack detection in masonry.

Distributive Behavior Differences Between Ingroup and Outgroup and the Influence of Inhibitory Control and Intelligence on Preschoolers’ Distributive Behavior

Objectives: The purpose of this study was to investigate the patterns and characteristics of distributive behavior in preschoolers, influence of inhibitory control and intelligence on the distributive behavior, and associations between them.Methods: The data was collected through a one-on-one interview experiment with 328 children aged 3–5 years old attending daycare centers and kindergartens. The distributive behavior was measured by modifying the procedure of the dictator game. Children’s cognitive and emotional inhibitory control (IC) were assessed using the day-night task and the reverse compensation task respectively. The intelligence was assessed using the K-WPPSI short form test. Pearson's correlation, paired samples t-test, one-way ANOVA, McNemar test, multiple regression, and the verification of mediation were performed to analyze the dataResults: First, there were differences among boys in resource allocation according to the type of group (in-group vs. outgroup). That is, boys aged four and five gave more resources to classmates rather than anonymous children. Second, cognitive IC and performance intelligence were associated with distributive behavior towards anonymous children. However, only performance intelligence was related to the children’s distributive behavior towards their classmates. Lastly, performance intelligence was completely mediated in the association between cognitive IC and distributive behavior towards anonymous children.Conclusion: We provide empirical evidence that cognitive IC and thinking skills necessary for performance intelligence were related to distributive behavior towards outgroup. In particular, boys aged four and five tended to consider more social relations in distributive behavior. This may be useful information for teaching altruism and sharing in early childhood.

Joint task offloading and resource allocation in vehicle-assisted multi-access edge computing

Multi-access Edge Computing (MEC) has significant advantages in improving resource efficiency of Internet of Things (IoT) and 5G networks, however its limited resources cannot meet the demand of data communication and computation capability during off-peak time. Incentivizing intelligent vehicles with idle computation resources as vehicle edge nodes (VENs) to provide computation offloading for nearby user equipments (UEs) is an appealing idea. Thus, we propose a vehicle-assisted MEC (VMEC) paradigm, where tasks can be offloaded to MEC server and VENs. In this paper, we first establish a differentiated pricing model based on different states of resources and a dynamic incentive model according to the demands of UEs. Then, we formulate a Stackelberg game between UEs and MEC service provider (MEC SP) to obtain the optimal offloading strategy and pricing scheme. A gradient-based resource allocation iteration algorithm (GRAIA) is designed for the Nash equilibrium solution. Finally, considering the matching between UEs and vehicles, we present a reverse auction-based task scheduling algorithm (RATSA) to choose VENs. The simulation results demonstrate that the proposed scheme can achieve significant performance improvement and is superior to the existing schemes in improving system utility.

The acute effect of moderate-intensity exercise on inhibitory control and activation of prefrontal cortex in younger and older adults.

Exercise has a significant effect on maintaining the health of inhibitory function, a fundamental cognitive ability that supports daily mental processes. While previous studies have shown that a single bout of exercise, called acute exercise, could improve inhibitory control by stimulating the prefrontal cortex (PFC) and the arousal state, few studies have focused on the differences in the effects of exercise by age. In this study, young and older adults (mean age, 22.7 ± 1.4 and 68.7 ± 5.3years, respectively) engaged in acute moderate-intensity exercise and inhibitory control. Before and at 5 and 30min after exercise, the participants were asked to complete the reverse Stroop task, and their arousal state and PFC activity were measured using functional near-infrared spectroscopy. The findings showed that the overall inhibitory control improved immediately after performing acute exercise and remained improved even after 30min. Particularly, there was a difference in the arousal state and middle PFC activity between the two age groups. Especially, the young adults showed an increase in the arousal state post-exercise, while the older adults tended to show an increase in the middle PFC activity. These results suggested that the acute exercise effects on the arousal state and PFC activity may vary depending on the developmental stage, but not for inhibitory control overtime. When these findings are considered, it is important to note that the exercise impact on cognitive control remained the same throughout the generations despite the observed changes in its impact on internal states.

The Neglected C of Intercultural Relations. Cross-Cultural Adaptation Shapes Sojourner Representations of Locals

We investigated, by means of the Reverse Correlation Task (RCT), visual representations of the culturally dominating group of local people held by sojourners as a function of their degree of cross-cultural adaptation. In three studies, using three different methods (reduced RCT, full RCT, conceptual replication) with three independent samples of sojourners and seven independent samples of Portuguese and US-American raters, we gathered clear evidence that poor adaptation goes along with more negative representations of locals. This indicates that sojourner adaptation is reflected, at a social-cognitive level, in the valence of outgroup representations.

The circular economy meets artificial intelligence (AI): understanding the opportunities of AI for reverse logistics

PurposeTechnology is an important force in the entrepreneurial ecosystem as it has the potential to impact entrepreneurial opportunities and processes. This paper explores the emerging technology of artificial intelligence (AI) and its implications for reverse logistics within the circular economy (CE). It considers key reverse logistics functions and outlines how AI is known to, or has the potential to, impact these functions.Design/methodology/approachThe paper is conceptual and utilizes the literature from entrepreneurship, the CE and reverse logistics to explore the implications of AI for reverse logistics functions.FindingsAI provides significant benefits across all functions and tasks in the reverse logistics process; however, the various reverse logistics functions and tasks rely on different forms of AI (mechanical, analytical, intuitive).Research limitations/implicationsThe paper highlights the importance of technology, and in particular AI, as a key force in the digital entrepreneurial ecosystem and discusses the specific implications of AI for entrepreneurial practice. For researchers, the paper outlines avenues for future research within the entrepreneurship and/or CE domains of the study.Originality/valueThis paper is the first to present a structured discussion of AI's implications for reverse logistics functions and tasks. It addresses a call for more research on AI and its opportunities for the CE and emphasizes the importance of emerging technologies, particularly AI, as an external force within the entrepreneurial ecosystem. The paper also outlines avenues for future research on AI in reverse logistics.