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All pieces of hardware and software involve multiple systems and features working together to complete tasks. Therefore, innovations in computer science require breaking down large goals into small, manageable parts. This book shows readers how achieving programmatic goals is not so different from achieving personal goals, elaborating on the mechanics of computer programming in an easy-to-follow way.

Existing multifactorial particle swarm optimisation (MFPSO) algorithms only explore a relatively narrow area between the inter-task particles. Meanwhile, these algorithms use a fixed inter-task learning probability throughout the evolution process. However, the parameter is problem dependent and can be various at different stages of the evolution. In this work, the authors devise an inter-task learning-based information transferring mechanism to replace the corresponding part in MFPSO. This inter-task learning mechanism transfers the searching step by using a differential term and updates the personal best position by employing an inter-task crossover. By this mean, the particles can explore a broad search space when utilising the additional searching experiences of other tasks. In addition, to enhance the performance on problems with different complementarity, they design a self-adaption strategy to adjust the inter-task learning probability according to the performance feedback. They compared the proposed algorithm with the state-of-the-art algorithms on various benchmark problems. Experimental results demonstrate that the proposed algorithm can transfer inter-task knowledge efficiently and perform well on the problems with different complementarity.

This book is about the role and potential of using digital technology in designing teaching and learning tasks in the mathematics classroom and explores mathematics task design when digital technology is part of the teaching and learning environment.

An underlying hypothesis for broad transfer from cognitive training is that the regional brain signals engaged during the training task are related to the transfer tasks. However, it is unclear whether the brain activations elicited from a specific cognitive task can generalize to performance of other tasks, esp. in normal aging where cognitive training holds much promise. In this large dual‐site functional magnetic resonance imaging (fMRI) study, we aimed to characterize the neurobehavioral correlates of task‐switching in normal aging and examine whether the task‐switching‐related fMRI‐blood‐oxygen‐level‐dependent (BOLD) signals, engaged during varieties of cognitive control, generalize to other tasks of executive control and general cognition. We therefore used a hybrid blocked and event‐related fMRI task‐switching paradigm to investigate brain regions associated with multiple types of cognitive control on 129 non‐demented older adults (65–85 years). This large dataset provided a unique opportunity for a data‐driven partial least squares–correlation approach to investigate the generalizability of multiple fMRI‐BOLD signals associated with task‐switching costs to other tasks of executive control, general cognition, and demographic characteristics. While some fMRI signals generalized beyond the scanned task, others did not. Results indicate right middle frontal brain activation as detrimental to task‐switching performance, whereas inferior frontal and caudate activations were related to faster processing speed during the fMRI task‐switching, but activations of these regions did not predict performance on other tasks of executive control or general cognition. However, BOLD signals from the right lateral occipital cortex engaged during the fMRI task positively predicted performance on a working memory updating task, and BOLD signals from the left post‐central gyrus that were disengaged during the fMRI task were related to slower processing speed in the task as well as to lower general cognition. Together, these results suggest generalizability of these BOLD signals beyond the scanned task. The findings also provided evidence for the general slowing hypothesis of aging as most variance in the data were explained by low processing speed and global low BOLD signal in older age. As processing speed shared variance with task‐switching and other executive control tasks, it might be a possible basis of generalizability between these tasks. Additional results support the dedifferentiation hypothesis of brain aging, as right middle frontal activations predicted poorer task‐switching performance. Overall, we observed that the BOLD signals related to the fMRI task not only generalize to the performance of other executive control tasks, but unique brain predictors of out‐of‐scanner performance can be identified. This dual‐site functional magnetic resonance imaging (fMRI) study (n = 129) uses multivariate partial least squares–correlation analysis to examine the relationships between fMRI brain activations from task‐switching and performance on other tasks of executive control functions and general cognition. We found that the brain activations from this fMRI task can predict performance on a broad range of cognitive tasks.

\"Task-based language teaching is an approach which differs from traditional approaches by emphasizing the importance of engaging learners' natural abilities for acquiring language incidentally through the performance of tasks that draw learners' attention to form. Drawing on the multiple perspectives and expertise of five leading authorities in the field, this books provides a comprehensive and balanced account of task-based language teaching (TBLT). Split into five sections, the book provides an historical account of the development of TBLT and introduces the key issues facing the area. A number of different theoretical perspectives that have informed TBLT are presented, followed by a discussion on key pedagogic aspects - syllabus design, methodology of a task-based lesson, and task-based assessment. The final sections consider the research that has investigated the effectiveness of TBLT, addresses critiques and suggest directions for future research. Task-based language teaching is now mandated by many educational authorities throughout the world and this book serves as a core source of information for researchers, teachers and students\"-- Provided by publisher.

PurposeThis paper aims to present a concise review on the variant state-of-the-art dynamic task allocation strategies. It presents a thorough discussion about the existing dynamic task allocation strategies mainly with respect to the problem application, constraints, objective functions and uncertainty handling methods.Design/methodology/approachThis paper briefs the introduction of multi-robot dynamic task allocation problem and discloses the challenges that exist in real-world dynamic task allocation problems. Numerous task allocation strategies are discussed in this paper, and it establishes the characteristics features between them in a qualitative manner. This paper also exhibits the existing research gaps and conducive future research directions in dynamic task allocation for multiple mobile robot systems.FindingsThis paper concerns the objective functions, robustness, task allocation time, completion time, and task reallocation feature for performance analysis of different task allocation strategies. It prescribes suitable real-world applications for variant task allocation strategies and identifies the challenges to be resolved in multi-robot task allocation strategies.Originality/valueThis paper provides a comprehensive review of dynamic task allocation strategies and incites the salient research directions to the researchers in multi-robot dynamic task allocation problems. This paper aims to summarize the latest approaches in the application of exploration problems.

Recounts a 1993 firefight in Mogadishu, Somalia, that resulted in the deaths of eighteen Americans and more than five hundred Somalis, examining the rationales behind the disastrous raid.

Consumer eHealth interventions are of a growing importance in the individual management of health and health behaviors. However, a range of access, resources, and skills barriers prevent health care consumers from fully engaging in and benefiting from the spectrum of eHealth interventions. Consumers may engage in a range of eHealth tasks, such as participating in health discussion forums and entering information into a personal health record. eHealth literacy names a set of skills and knowledge that are essential for productive interactions with technology-based health tools, such as proficiency in information retrieval strategies, and communicating health concepts effectively. We propose a theoretical and methodological framework for characterizing complexity of eHealth tasks, which can be used to diagnose and describe literacy barriers and inform the development of solution strategies. We adapted and integrated two existing theoretical models relevant to the analysis of eHealth literacy into a single framework to systematically categorize and describe task demands and user performance on tasks needed by health care consumers in the information age. The method derived from the framework is applied to (1) code task demands using a cognitive task analysis, and (2) code user performance on tasks. The framework and method are applied to the analysis of a Web-based consumer eHealth task with information-seeking and decision-making demands. We present the results from the in-depth analysis of the task performance of a single user as well as of 20 users on the same task to illustrate both the detailed analysis and the aggregate measures obtained and potential analyses that can be performed using this method. The analysis shows that the framework can be used to classify task demands as well as the barriers encountered in user performance of the tasks. Our approach can be used to (1) characterize the challenges confronted by participants in performing the tasks, (2) determine the extent to which application of the framework to the cognitive task analysis can predict and explain the problems encountered by participants, and (3) inform revisions to the framework to increase accuracy of predictions. The results of this illustrative application suggest that the framework is useful for characterizing task complexity and for diagnosing and explaining barriers encountered in task completion. The framework and analytic approach can be a potentially powerful generative research platform to inform development of rigorous eHealth examination and design instruments, such as to assess eHealth competence, to design and evaluate consumer eHealth tools, and to develop an eHealth curriculum.

\"This book describes research on training using cognitive psychology to build a complete empirical and theoretical picture of the training process. It includes a review of relevant cognitive psychological literature, a summary of recent laboratory experiments, a presentation of original theoretical ideas, and a discussion of possible applications to real-world training settings\"--Provided by publisher.

PurposeThis study explored whether crowdsourcing work characteristics are associated with perceived work effort in competitive crowdsourcing markets. The study also investigated the important contextual variables and internal mechanisms related to perceived work effort.Design/methodology/approachA questionnaire was posted as a crowdsourcing task on China's Time Fortune website. Data from 231 valid questionnaires were analyzed using SmartPLS 3.FindingsCrowdsourcing workers' intrinsic and extrinsic motivations were significantly and positively correlated with their perceived work effort. Task autonomy and feedback were significantly and positively correlated with intrinsic motivation. Skill variety, task significance, task identity, and task clarity had no significant correlations with intrinsic motivation. However, task clarity was significantly and positively correlated with perceived work effort. Moreover, the relationship between workers' trust in task requesters and perceived work effort was fully mediated by intrinsic motivation.Originality/valueThis study extended the job characteristic model into the virtual competitive crowdsourcing market. The authors verified the relationship between task clarity/trust in task requesters and workers' motivation and perceived work effort.