2,900 research outputs found
Essential Skills for Leadership Effectiveness in Diverse Workplace Development
Globalization, technology advances, and diversity have greatly influenced international business and multinational management operations. Global managers cannot consistently apply traditional leadership when dealing with multiple cultural conflicts and managing international employees in the rapidly changed diverse workplace. This study is an initial effort to examine the new looks of leadership in the diverse workplace development and identify essential leadership skills demanded in a global context. Global leaders need to develop cultural awareness, global mindset, interpersonal skill and effective manager-employee relationship in facing the changes and challenges of the global market. Eleven essential leadership skills for the global leaders to promote effective leadership performance in the diverse workplace are presented and discussed in this study. Implications for future research are also provided
The influence of Confucian philosophy on adults\u27 preference for learning: a comparison of Confucian adult learners and non-Confucian adult learners
The primary purpose of this study was to determine the influence of the extent of agreement with the principles of Confucian philosophy on the learning preferences of students enrolled in a research extensive university in the southern region of the United States. This study also compared the extent of agreement with the Confucian philosophy and the extent of preferences for learning methods by cultural background (as defined by nonresident Far East Asians from Confucian-influenced countries, Asian Americans, and White Americans) of enrolled students. The researcher used survey methodology to determine the current level (extent to which the subjects agreed with the principles) of Confucian philosophy and to describe the current preferences for learning of the students. Exploratory factor analysis was used to summarize the information regarding the 581 university students\u27 levels of agreements with 45 statements of Confucian and their preferences for 33 learning methods. Pearson\u27s correlation, one-way ANOVA, and independent t-test were utilized to determine whether an association exists between the levels of Confucian philosophy (as well as the preferences for learning methods) and selected demographic characteristics. Three key conclusions emerged from the study. One, there are different levels of adults\u27 agreement on the values of Confucian philosophy and, as the students agreed more with the philosophy, the higher preferences for individual learning, passive/traditional learning, active learning, and group learning methods. Two, age, gender, nationality, lengths of time working inside and outside of the U.S., and academic status influenced the students\u27 values of Confucian philosophy and preferences for learning methods. Three, a universal agreement on the values of Confucian harmonious relationship and a universal preference for alternative learning methods were found (regardless of students\u27 cultural background, length of time working in the U.S., and academic status). It is recommended that human resource development professionals, adult educators, trainers, and training designers use this study to understand the cultural difference between Westerners and Confucian adult learners and to develop and manage appropriate training programs that create culturally relevant approaches to learning while addressing the students\u27 preferences for learning methods
Experimental realization of a highly structured search algorithm
The highly structured search algorithm proposed by Hogg[Phys.Rev.Lett.
80,2473(1998)] is implemented experimentally for the 1-SAT problem in a single
search step by using nuclear magnetic resonance technique with two-qubit
sample. It is the first demonstration of the Hogg's algorithm, and can be
readily extended to solving 1-SAT problem for more qubits in one step if the
appropriate samples possessing more qubits are experimentally feasible.Comment: RevTex, 11 pages + 3 pages of figure
Preparation of pseudo-pure states by line-selective pulses in Nuclear Magnetic Resonance
A new method of preparing the pseudo-pure state of a spin system for quantum
computation in liquid nuclear magnetic resonance (NMR) was put forward and
demonstrated experimentally. Applying appropriately connected line-selective
pulses simultaneously and a field gradient pulse techniques we acquired
straightforwardly all pseudo-pure states for two qubits in a single experiment
much efficiently. The signal intensity with the pseudo-pure state prepared in
this way is the same as that of temporal averaging. Our method is suitable for
the system with arbitrary numbers of qubits. As an example of application, a
highly structured search algorithm----Hogg's algorithm was also performed on
the pseudo-pure state prepared by our method.Comment: RevTEX,10 pages,5 PS figure
InfoFlowNet: A Multi-head Attention-based Self-supervised Learning Model with Surrogate Approach for Uncovering Brain Effective Connectivity
Deciphering brain network topology can enhance the depth of neuroscientific
knowledge and facilitate the development of neural engineering methods.
Effective connectivity, a measure of brain network dynamics, is particularly
useful for investigating the directional influences among different brain
regions. In this study, we introduce a novel brain causal inference model named
InfoFlowNet, which leverages the self-attention mechanism to capture
associations among electroencephalogram (EEG) time series. The proposed method
estimates the magnitude of directional information flow (dIF) among EEG
processes by measuring the loss of model inference resulting from the shuffling
of the time order of the original time series. To evaluate the feasibility of
InfoFlowNet, we conducted experiments using a synthetic time series and two EEG
datasets. The results demonstrate that InfoFlowNet can extract time-varying
causal relationships among processes, reflected in the fluctuation of dIF
values. Compared with the Granger causality model and temporal causal discovery
framework, InfoFlowNet can identify more significant causal edges underlying
EEG processes while maintaining an acceptable computation time. Our work
demonstrates the potential of InfoFlowNet for analyzing effective connectivity
in EEG data. The findings highlight the importance of effective connectivity in
understanding the complex dynamics of the brain network
An auxiliary ordinary differential equation and the exp-function method
AbstractIn this paper, the new idea of finding the exact solutions of the nonlinear evolution equations is introduced. The idea is that the exact solutions of the auxiliary ordinary differential equation are derived by using exp-function method, and then the exact solutions of the nonlinear evolution equations are derived with aid of the auxiliary ordinary differential equation. As examples, the classical KdV equation, Boussinesq equation, (3+1)-dimensional Jimbo–Miwa equation and Benjamin–Bona–Mahony equation are discussed and the exact solutions are derived
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