The influence of follower cultural orientation on attitudinal responses towards transformational leadership: evidence from the Chinese hospitality industry

In addition to extending the empirical investigation of the relationship between transformational leadership and follower affective commitment to the Chinese hospitality industry, this study makes a theoretical contribution by investigating the influence of individually held cultural values on this relationship. Building on previous research which has examined whether collectivism moderates the transformational leadership/affective commitment relationship, this study investigates the moderating effects of two additional cultural value orientations, namely power distance and uncertainty avoidance. Hierarchical regression analysis was utilized to analyse survey data from 398 employees of four Chinese hotels in Zhejiang Province. In addition to finding a positive relationship between transformational leadership and affective commitment, data analysis revealed that followers low in power distance exhibited higher levels of affective commitment when working under a transformational leader than those high in power distance. In addition, followers high in uncertainty avoidance and collectivism exhibited greater commitment when working under a transformational leader than those low in uncertainty avoidance and collectivism. These findings clearly indicate the importance of within-country cultural differences to the effectiveness of leaders in the workplace. © 2014 © 2013 Taylor & Francis.

Influence of pacing on reliability of middle-distance cycling performance

The purpose of the present study was to examine the reliability of middle distance cycling time trials using fast-, even-, and slow-starts. Eighteen endurance-trained male cyclists [mean ± standard deviation; VO2peak 63.1 ± 6.1 mL⋅kg-1⋅min-1] performed nine cycling time trials where the total external work (96.5 ± 11.2 kJ) was identical to the better of two, 5-minute habituation time trials. Power output during the first quarter of the time-trials (24.1 ± 2.8 kJ) was fixed to induce fast-, even- or slow-starting strategies (60, 75 and 90 s, respectively). In consecutive sessions, participants performed three trials of each pacing condition although the order of these pacing conditions was counterbalanced. Average power output and performance time were unaffected by trial number in the fast- (P = 0.60), even- (P = 0.18) and slow-start (P = 0.53) trials. In all three pacing conditions, average power output was highly reliable and similar between trial 1 to 2 and trial 2 to 3 in fast- (standard error of measurement; SEM=8.3 and 8.2W), even (coefficient of variation; CV=2.8 and 2.4%) and slow-start (CV=2.4 and 1.5%) trials. In conclusion, the reproducibility of 5-min cycling time trials is unaffected by starting strategy and is acceptable following two selfpaced habituation trials. Research examining the influence of pacing strategies may therefore be conducted without the need for familiarisation trials using each individual pacing condition.

GTES: An optimized game-theoretic demand-side management scheme for smart grid

Demand-side management in smart grids has emerged as a hot topic for optimizing energy consumption. In conventional research works, energy consumption is optimized from the perspective of either the users or the power company. In this paper, we investigate how energy consumption may be optimized by taking into consideration the interaction between both parties. We propose a new energy price model as a function of total energy consumption. Also, we propose a new objective function, which optimizes the difference between the value and cost of energy. The power supplier pulls consumers in a round-robin fashion and provides them with energy price parameter and current consumption summary vector. Each user then optimizes his own schedule and reports it to the supplier, which, in turn, updates its energy price parameter before pulling the next consumers. This interaction between the power company and its consumers is modeled through a two-step centralized game, based on which we propose our game-theoretic energy schedule (GTES) method. The objective of our GTES method is to reduce the peak-to-average power ratio by optimizing the users' energy schedules. The performance of the GTES approach is evaluated through computer-based simulations. © 2014 IEEE.

Analytical assessment of optimum magnet pole-arc for PMSM under influence of different magnetization patterns

Permanent magnet synchronous machines (PMSMs) are popular in both industrial and domestic applications because of its high efficiency, power density, and reliability as compared with the conventional types of electrical machines. Generally, the analytical models and their field solutions are preferable to provide an accurate insight of the PMSM performances, instead of using the finite element models, because the former takes a considerably shorter computational time. PMSM design could have different properties of either slotted or slotless, or varieties of magnet placement on the rotor. By focusing on semi-closed surface-mounted PMSMs, the 2D analytical subdomain model in [1] demonstrates an accurate prediction of the magnetic fields that can facilitate the evaluation of the global quantities of PMSMs, such as cogging torque (Tcog), back-EMF, and total harmonic distortion (THDv). Previously, researchers investigated the influences of the machine performance by a single factor, e.g., the variation of Tcog during changes of magnet pole-arc (αP) [2, 3], or slot-opening [2, 3]. These investigations normally considered two types of magnetization patterns, i.e., parallel (PaM) and radial magnetization (RM). Therefore, the motivation of our work hinges on predicting the optimum value of αP in designing a surface-mounted PMSM under influence of four different magnetization patterns, using the analytical subdomain model.

Stable deep doping of vapor-phase polymerized poly(3,4-ethylenedioxythiophene)/ionic liquid supercapacitors

Liquid-solution polymerization and vapor-phase polymerization (VPP) have been used to manufacture a series of chloride- and tosylate-doped poly(3,4-ethylenedioxythiophene) (PEDOT) carbon paper electrodes. The electrochemistry, specific capacitance, and specific charge were determined for single electrodes in 1-ethyl-3-methylimidazolium dicyanamide (emim dca) ionic liquid electrolyte. VPP-PEDOT exhibits outstanding properties with a specific capacitance higher than 300 F g(-1) , the highest value reported for a PEDOT-based conducting polymer, and doping levels as high as 0.7 charges per monomer were achieved. Furthermore, symmetric PEDOT supercapacitor cells with the emim dca electrolyte exhibited a high specific capacitance (76.4 F g(-1) ) and high specific energy (19.8 Wh kg(-1) ). A Ragone plot shows that the VPP-PEDOT cells combine the high specific power of conventional ("pure") capacitors with the high specific energy of batteries, a highly sought-after target for energy storage.

Protection of big data privacy

In recent years, big data have become a hot research topic. The increasing amount of big data also increases the chance of breaching the privacy of individuals. Since big data require high computational power and large storage, distributed systems are used. As multiple parties are involved in these systems, the risk of privacy violation is increased. There have been a number of privacy-preserving mechanisms developed for privacy protection at different stages (e.g., data generation, data storage, and data processing) of a big data life cycle. The goal of this paper is to provide a comprehensive overview of the privacy preservation mechanisms in big data and present the challenges for existing mechanisms. In particular, in this paper, we illustrate the infrastructure of big data and the state-of-the-art privacy-preserving mechanisms in each stage of the big data life cycle. Furthermore, we discuss the challenges and future research directions related to privacy preservation in big data.