Search results

Due to the advantages of fast response, high positioning precision and large stiffness, the piezoelectric-actuated nanopositioning stage is widely used in the micro/nanomachining fields. However, due to the inherent nonlinear hysteresis of the piezoelectric-actuator, the positioning accuracy of nanopositioning stage is greatly degraded. Besides, the nanopositioning stage is always performed with repetitive trajectories as the reference signals in applications, which makes the hysteresis behavior periodic. To this end, an adaptive resonance suppression iterative learning control (ARS-ILC) is proposed to address the hysteresis effect. With this effort, the positioning accuracy of the nanopositioning stage is improved.

The hysteresis behavior is identified by the Prandtl–Ishlinskii model. By establishing a convergence function, it is demonstrated that the learnable band of ILC is restricted by the lightly damping resonance of nanopositioning stage. Then, an adaptive notch filter (ANF) with constrained poles and zeros is adopted to suppress the resonant peak. Finally, online stability supervision (OSS) is used to ensure that the estimated frequency converges to the resonant frequency.

A series of experiments were carried out in the nanopositioning stage, and the results validated that the OSS is available to ensure the convergence of the ANF. Furthermore, the learnable band was extended via ARS-ILC; thus, the hysteresis behavior of nanopositioning stage has been canceled.

Due to high accuracy and easy implementation, the ARS-ILC can be used in not only nanopositioning stage control but other fabrication process control with repetitive motion.

A striking feature of Jaques' work is his “no nonsense” attitude to the “manager‐subordinate” relationship. His blunt account of the origins of this relationship seems at first sight to place him in the legalistic “principles of management” camp rather than in the ranks of the subtler “people centred” schools. We shall see before long how misleading such first impressions can be, for Jaques is not making simplistic assumptions about the human psyche. But he certainly sees no point in agonising over the mechanism of association which brings organisations and work‐groups into being when the facts of life are perfectly straightforward and there is no need to be squeamish about them.

This paper aims to explore factors affecting young consumers’ purchasing of new smart products under the influence of social media.

Twenty semi-structured, face-to-face, in-depth interviews were conducted with young consumers who used new media, and five extended interviews were conducted with popular smartwatch retailers in Macau.

The findings reveal that they tend to garner product information from multiple channels of communication. Social media exert the greatest influence. Reliable information, strong branding and interactions with vendors are also influential, although new product pre-announcements may be boring and difficult to understand.

This study presents new insights into diffusion of innovation theory and provides retailers launching smart products with a better understanding of their target young customers’ purchasing behavior.

While interest in and demand for entrepreneurial universities has gained prominence in recent years (e.g. Clark, 1998; Etzkowitz, 2008; Thorp and Goldstein, 2010), there is minimal research on the learning experiences and career-making events that transform traditional faculty members into faculty entrepreneurs who are able to successfully apply their research knowledge toward endeavors that intersect with the private market. As a result, the purpose of this paper is to understand, from the perspective of faculty entrepreneurs, the lived learning experiences that contributed to their development from traditional faculty member to faculty entrepreneur. Specifically, this study explored the question on how faculty members who were founders or co-founders of a business learned “to work in entrepreneurial ways” (Rae and Carswell, 2000, p. 220). In general, individuals who are interested in pursuing a career as a professor are not generally socialized during graduate school to engage in technology transfer activities or encouraged to start businesses (Bercovitz and Feldman, 2008). This study also sought to understand how faculty entrepreneurs learn to persist in an organizational culture that does not always support entrepreneurial endeavors outside the scope of researching, teaching, and service.

A phenomenological qualitative research design was employed using in-depth, semi-structured interview questions. Entrepreneurial learning was the theoretical framework that grounded this study.

The data analysis process revealed six themes which offer insights on the learning experiences, contextual factors, and patterns of behavior that helped the participants to develop and to persist as faculty entrepreneurs.

First, the data were dependent upon the learning experiences identified and articulated by the faculty entrepreneurs. There is a possibility that significant learning or career-making experiences were omitted or unintentionally not reported by the participants. Second, the author used a broad net when searching and recruiting for faculty entrepreneurs. Any faculty member who was in a tenure-track position and who had founded or co-founded an organization was eligible to participate in this study. However, the data analysis process may have yielded different results if the author had elected to study faculty entrepreneurs from a specific academic discipline or if the author had chosen to only interview faculty entrepreneurs who had founded a specific type of business. Third, this study focussed only on tenured faculty members who are currently involved with the businesses that they founded or co-founded. Subsequently, this study did not include any faculty members whose entrepreneurial pursuits were unsuccessful (i.e. closing the business). There is the possibility that former faculty entrepreneurs may have had similar learning experiences as the individuals who were interviewed for this study.

The findings may be instructive for traditional faculty members who are interested in applying their research findings and expertise with an entrepreneurial endeavor such as starting a business. In addition, these findings may be useful for higher education administrators who seek to cultivate an entrepreneurial learning environment in their institutions and for future researchers who want to expand the study of faculty entrepreneurs.

There is a gap in the literature on how traditional faculty members learn to couple their research knowledge and expertise with an entrepreneurial endeavor such as starting a small business. In addition, there has been minimal research that delineates how the faculty entrepreneur comes into existence at the individual level (Clarysse et al., 2011; Pilegaard et al., 2010). Subsequently, this is one of the first phenomenological qualitative research studies to examine the lived learning experiences of faculty entrepreneurs.

The purpose of this paper is twofold. First, it empirically examines two theory-based models of applicants’ job search developed from planned happenstance theory (PHT) and theory of planned behavior (TPB). Second, it tests the cross-cultural compatibility of these models in Japan and Korea.

The authors tested two theory-based job search models, PHT model and TPB model based on samples of college students from Japan (n=175) and Korea (n=172).

The results indicated that the TPB model was a significantly better fitting to the data than the PHT model. Moreover, a multi-group test of the TPB model demonstrated that the TPB model was invariant between the Japanese and the Korean samples.

Although there had been an important question among job search literatures regarding how important the planned behavior in the job search processes would be, the study gave an empirical support to the TPB job search model in contrast to the PHT model. Another contribution is that the study tested the Western-driven theories using Asian samples from Japan and Korea, constituting an important benchmark for further studies that attempt to test the generalizability of the TPB model, particularly in countries/areas that employ different employment systems.

Owing to highly volatile and chaotic external events, predicting future movements of cryptocurrencies is a challenging task. This paper advances a granular hybrid predictive modeling framework for predicting the future figures of Bitcoin (BTC), Litecoin (LTC), Ethereum (ETH), Stellar (XLM) and Tether (USDT) during normal and pandemic regimes.

Initially, the major temporal characteristics of the price series are examined. In the second stage, ensemble empirical mode decomposition (EEMD) and maximal overlap discrete wavelet transformation (MODWT) are used to decompose the original time series into two distinct sets of granular subseries. In the third stage, long- and short-term memory network (LSTM) and extreme gradient boosting (XGB) are applied to the decomposed subseries to estimate the initial forecasts. Lastly, sequential quadratic programming (SQP) is used to fetch the forecast by combining the initial forecasts.

Rigorous performance assessment and the outcome of the Diebold-Mariano’s pairwise statistical test demonstrate the efficacy of the suggested predictive framework. The framework yields commendable predictive performance during the COVID-19 pandemic timeline explicitly as well. Future trends of BTC and ETH are found to be relatively easier to predict, while USDT is relatively difficult to predict.

The robustness of the proposed framework can be leveraged for practical trading and managing investment in crypto market. Empirical properties of the temporal dynamics of chosen cryptocurrencies provide deeper insights.