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关键词： Computer science   Quantum information   Mathematics and computing  

摘要： Sang-Wook Han hopes that the technology will spark innovations in materials science, drug development, finance and defence.

关键词： Training   Loss measurement   Recommender systems   Fans   Electronic mail   Uncertainty   Motion pictures   Computer science   Vectors   Upper bound   Loss function   matrix factorization   outlier   recommender system (RS)  

摘要： Outliers are intrinsic to recommender systems (RSs) due to user uncertainty and bring large deviations to the total loss. Classical loss functions such as L-1 and L-2 do not consider this issue, thus biasing the model toward abnormal ratings. Advanced ones such as Logcosh, Huber, and Wing losses try to control model biasing;however, they do not consider the rating ranges of recommender systems. In this article, we propose a Seagull loss combining quadratic and softsign functions to handle this issue. The quadratic function aims to preserve or appropriately increase losses caused by small deviations, while softsign function aims to suppress losses caused by large deviations. It is distinguished from three types of popular losses. Compared with L-1 and L-2, it controls the upper bound, therefore suppressing the influence of outliers. Compared with Logcosh and Huber, it not only adjusts the loss of small deviations but also suppresses the loss of large deviations. Compared with Wing loss, it considers the characteristics of data in RSs and therefore is more suitable to the matrix factorization model. Experiments are undertaken on six real-world recommendation datasets in comparison with six popular loss functions. Results show that Seagull loss function has superiority to all losses above on mean absolute error (MAE) and root mean square error (RMSE) and slight inferiority to L-2 and Wing on hit ratio (HR), mean average precision (MAP), and normalized discounted cumulative gain (NDCG).

关键词： maths   engineering   physics   chemistry   computer science   Earth science  

关键词： Programming   Teaching and learning   Interdisciplinary pedagogy   Computer science   Business school   UTAUT  

摘要： PurposeThis study aims to develops an interdisciplinary business and computer science pedagogy for teaching and learning computer programming in business schools at higher education institutions and explores its associated benefits, challenges and ***/methodology/approachBased on a body of theories, an interdisciplinary pedagogy is developed and tested for programming education in a business context. Meanwhile, based on the unified theory of acceptance and use of technology, the authors used observation study and thematic analysis to explore opportunities, challenges and future improvements associated with this interdisciplinary *** developed pedagogy includes integrating humanism and construction theory, problem-based learning, cognitive development, active instructional strategies, synergy of individual and group programming tasks and creating an encouraging and inclusive learning environment. This study shows that business students perceive this novel pedagogy as highly valuable because it enhances their logical thinking and problem-solving abilities while giving them a sense of accomplishment. Although students face challenges in data preprocessing, error handling and translating theoretical knowledge, they find it useful to review teaching materials, seek peer support and learn independently through online resources. Further improvements in pedagogy include incorporating collaborative code reviews, using shared documents for troubleshooting and grouping students based on their prior programming *** implicationsThis interdisciplinary pedagogy can guide business schools to improve the quality of programming-related modules, enhance students' performance and prepare them for future ***/valueThis is the first interdisciplinary study investigating teaching programming in a business context.

摘要： This article has been retracted: please see Elsevier Policy on Article Withdrawal ( https://***/locate/withdrawalpolicy ). This article has been retracted at the request of the Editor-in-Chief of Theoretical Computer Science, Section A. The article is a duplicate of a paper that has already been published in Int. J. Nonlinear Anal. Appl., Volume 13 (2022), Issue 2, Pages 1893-1905, http://***/10.22075/ijnaa.2022.27403.3588 . One of the conditions of submission of a paper for publication is therefore that authors declare explicitly that the paper has not been previously published and is not under consideration for publication elsewhere. As such this article represents a misuse of the scientific publishing system. The scientific community takes a very strong view on this matter and apologies are offered to readers of the journal that this was not detected during the submission process.

关键词： Heuristic algorithms   Event detection   Predictive control   Prediction algorithms   Electronic mail   Trajectory   Economic indicators   Couplings   Computer science   Circuit stability   Coupled nonlinear systems   distributed model predictive control   dynamic self-triggered mechanism  

摘要： This article proposes a dynamic self-triggered distributed model predictive control algorithm for coupled nonlinear systems facing external disturbances and constraints on state and input variables. A dynamic self-triggered mechanism that combines the advantages of event-triggered and self-triggered strategies is designed to simultaneously reduce the frequencies of both sampling and solving optimization problems. Particularly, the triggering threshold is adaptively adjusted using a dynamic variable, which can effectively balance control performance and computational resources. Furthermore, through the construction of a two-model optimal control problem and the analysis of input-to-state practical stability for the overall system, a single-mode distributed model predictive control framework is established for each subsystem within the proposed algorithm, which enables a fully distributed implementation. Sufficient conditions for recursive feasibility and robust stability are investigated, and conservatism is reduced by eliminating the requirement for the system state to reach the terminal region in finite time. Finally, the effectiveness of the developed algorithm is validated through two numerical examples with comparisons.

关键词： Quantum physics   Computer science   History  

摘要： A century ago, physics had its Darwinian moment - a change in perspective that was as consequential for the physical sciences as the theory of evolution by natural selection was for biology. A century ago, physics had its Darwinian moment - a change in perspective that was as consequential for the physical sciences as the theory of evolution by natural selection was for biology.

关键词： artificial intelligence   biology   diagnostics   machine learning   nervous system   neuroscience   neurology   therapeutics  

摘要： Unlike other fields of biology, neuroscience and the study of the nervous system across a range of 19 species were characterized early on by the need for the analysis of highly complex data sets. In seminal 20 areas of neuroscience, such as electrophysiology, neuroimaging, and neurophysiology, progress in both 21 data acquisition and data analysis was limited by the capabilities of hardware and software solutions 22 available to researchers. At the same time, critical advances in computer science and software 23 engineering not only led to fundamentally important new discoveries in neuroscience but were often 24 also driven by challenges resulting from paradigm-shifting discoveries in neuroscience, such as the In summary, the Frontiers Research Topic on Advances in computer science and their impact on 89 data acquisition and analysis in neuroscience, provides novel contributions exemplifying how 90 interdisciplinary work in computer science and neuroscience can synergistically improve data analysis 91 in a wide range of scientific and medical utilities increasing both scientific knowledge and the value of 92 tools in clinical diagnostics, prognostics, and therapeutics, altogether reducing the socio-economic 93 burden of disease conditions affecting the nervous system. 94 95

关键词： Heuristic algorithms   Probabilistic logic   Servers   Crowdsensing   Electronic mail   Mirrors   Computer science   Channel allocation   Optimization   Dynamic scheduling   Probabilistic maximum coverage   online learning   combinatorial bandit   network application optimization  

摘要： The Probabilistic Maximum Coverage (PMC) problem plays a pivotal role in modeling various network applications, such as mobile crowdsensing, which involves selecting nodes within a graph that probabilistically cover other nodes. Our study focuses on PMC within the framework of online learning, termed the PMC bandit, where the network parameters are initially unknown. In this scenario, the decision-maker is tasked with learning these parameters to maximize the cumulative rewards from covered nodes. Despite prior research on the PMC bandit, we propose a novel variant, dynamic PMC-G bandit, which extends the semi-bandit feedback model to represent applications more accurately. To tackle the complexities of the time-varying combinatorial arm set rather than traditional static, we enhance the Combinatorial Upper Confidence Bound (CUCB) algorithms by developing two innovative variance-aware strategies: the Variance-Adaptive Combinatorial Upper Confidence Bound (VACUCB) for probabilistically triggered arms, and the Action-Based Combinatorial Upper Confidence Bound (ABCUCB) for self-reliant arms, i.e., independent arms with probabilistically triggered outcomes. Based on variance-aware properties, our contributions notably reduce the dependence on the number of nodes K selected per round, demonstrating that: (i) VACUCB effectively minimizes the regret associated with the triggered arms, enhancing the CUCB by a factor of (O) over tilde (K;(ii) ABCUCB further diminishes the dependence on K in the leading term. Empirical results from synthetic and real-world datasets confirm that our proposed algorithms outperform current benchmarks in three network applications.

关键词： Black employees   Black scholarship   Ethical leadership   Signaling theory   Psychological diversity climate  

摘要： The goal of our work is to explore and highlight factors that contribute to positive experiences of Black employees. To accomplish this, we integrate behavioral ethics research into the Black scholarship literature. Specifically, we focus on the role of ethical leadership. We leverage signaling theory to explain the Black cultural implications associated with ethical leadership and how ethical leaders create racially just workplaces. Across three studies (i.e., one cross-sectional field study and two experimental vignettes), we demonstrate that ethical leadership operates as a welcoming signal for Black employees, which positively impacts Black employees' evaluations of psychological diversity climate. By cultivating Black employees' evaluations of psychological diversity climate, Black employees are more likely to be engaged and are less likely to be ostracized in the workplace, which are key indicators of a racially just workplace. Theoretical and practical implications are discussed. We conclude with limitations and future research ideas.