X. Wang

The strap-down inertial navigation system is a commonly used sensor for autonomous underground navigation, which can be used for shearer positioning under a coal mine. During the process of initial alignment, inaccurate or time-varying noise covariance matrices will significantly degrade the accuracy of the initial alignment of the shearer. To overcome the performance degradation of the existing initial alignment algorithm under complex underground environment, a novel adaptive filtering algorithm is proposed by the integration of the strong tracking Kalman filter and the sequential filter for the initial alignment of the shearer with complex underground environment. Compared with the traditional multiple fading factor strong tracking Kalman filter method, the proposed MSTSKF algorithm integrates the advantage of strong tracking Kalman filter and sequential filter, and multiple fading factor and forgetting factor for east and north velocity measurement are designed in the algorithm, respectively, which can effectively weaken the coupling relationship between the different states and increase strong robustness against process uncertainties. The simulation and experiment results show that the proposed MSTSKF method has better initial alignment accuracy and robustness than existing strong tracking Kalman filter algorithm.

Firms have been increasingly using social commerce platforms to engage with customers and support their brand value co-creation. While social commerce is now bringing a variety of benefits to business, it has also challenged marketing ethics surrounding online consumer privacy. Drawing on the trust-commitment theory, we develop a model that aims to create an ethical and trustworthy social commerce community for brand value co-creation by examining the impacts of online consumer privacy concerns and social interaction constructs on consumers’ psychological reactions. Using an empirical study, we find that: privacy risk, privacy control, and collaborative norms significantly influence consumers’ trust; consumer-peer interaction and collaborative norms are positively related to relationship commitment; and relationship commitment and trust positively affect consumers’ brand value co-creation in the context of social commerce. Theoretical and practical implications are discussed.

The aim of this research is to explore the process linking participative leadership to organizational identification. The study examines the relationship between participative leadership and internal CSR perceptions of employees and also investigates the role that pride in membership plays in the affiliation of CSR perceptions with organizational identification. By studying these relationships, the paper aspires to contemplate new presumed mediators in the association of participative leadership with organizational identification as well as determine a possible novel antecedent of employee CSR perceptions. Empirical evidence is provided from data that was collected through a survey distributed to employees working for small- and medium-sized enterprises in three countries in the Middle East and North Africa regions, particularly the United Arab Emirates, Lebanon, and Tunisia. Findings show that participative leadership leads to positive internal CSR perceptions of employees and that these CSR perceptions lead to pride in membership which, in turn, results in organizational identification. Implications of these findings are also discussed.

In the automatic detection of epileptic seizures, the monitoring of critically ill patients with time varying EEG signals is an essential procedure in intensive care units. There is an increasing interest in using EEG analysis to detect seizure, and in this study we aim to get a better understanding of how to visualize the information in the EEG time-frequency feature, and design and train a novel random forest algorithm for EEG decoding, especially for multiple-levels of illness. Here, we propose an automatic detection framework for epileptic seizure based on multiple time-frequency analysis approaches; it involves a novel random forest model combined with grid search optimization. The short-time Fourier transformation visualizes seizure features after normalization. The dimensionality of features is reduced through principal component analysis before feeding them into the classification model. The training parameters are optimized using grid search optimization to improve detection performance and diagnostic accuracy by in the recognition of three different levels epileptic of conditions (healthy subjects, seizure-free intervals, seizure activity). Our proposed model was used to classify 500 samples of raw EEG data, and multiple cross-validations were adopted to boost the modeling accuracy. Experimental results were evaluated by an accuracy, a confusion matrix, a receiver operating characteristic curve and an area under the curve. The evaluations indicated that our model achieved the more effective classification than some previous typical methods. Such a scheme for computer-assisted clinical diagnosis of seizures has a potential guiding significance, which not only relieves the suffering of patient with epilepsy to improve quality of life, but also helps neurologists reduce their workload.

Judges tend to discount the opinions of others even though advice is often helpful in improving their accuracy. The present research proposes that this phenomenon of advice discounting results from the judges’ confidence in their initial decision and little trust in advice. Furthermore, the degree of advice discounting may be predicted by the combined roles of confidence and trust. Three studies provide evidence for these hypotheses. Participants were very confident in their initial estimation and had little trust in the advice (study 1). The degree of advice discounting decreased when participants felt less confidence in performing difficult tasks compared with easy tasks (study 2) or when participants placed more trust in advice because the advice was from an expert rather than from a novice (study 3). In addition, confidence and trust predicted the degree of advice discounting across three studies. These findings shed new light on the mechanism underlying advice discounting and advice taking by indicating the combined roles of confidence and trust.

Food, money, and time are exchangeable resources essential for survival and reproduction. Individuals live within finite budgets of these resources and make tradeoffs between money and time when making intertemporal choices between an immediate smaller reward and a delayed lager reward. In this paper, I examine signaling functions of blood glucose in regulating behaviors related to resource regulations beyond caloric metabolisms. These behavioral regulations include choices between energy expenditure and energy conservation, monetary intertemporal choices, and self-control in overcoming temptations. I begin by comparing potential embodied signals for resource forecasting and proactive decision making in terms of their pros and cons as a signal for regulating both metabolism and behavioral decision making and self-control. Based on this analysis, circulating glucose emerges as not only the designated fuel for brain metabolism but also a privileged resource forecasting signal for regulating immediate, short-term, and long-term behavioral adaptations to the resource budget of the decision maker. In the context of an on-going debate between the limited resource model and the motivation accounts of behavioral effects of blood glucose, I propose a dual functions (caloric provision and resource forecasting) and dual signaling (glucose taste and ingestion) hypothesis of circulating glucose in resource management, and provide behavioral and neurophysiological evidence of the separate effects of glucose taste to motivate effort for resource acquisition and glucose ingestion to promote resource conservation and future orientation. Accumulating evidence indicates that the body is able to detect fake signals of non-caloric sweeteners and react to such “caloric crisis” with an enhanced preference for immediate rewards over future rewards, revealing the wisdom of the body.

This study examined the extent to which the impact of green transformational leadership on employee green behavior through follower perceptions of value congruence. Path analyzing on data from 193 subordinate-leader dyads showed that followers’ value congruence with their leader mediated the effects of green transformational leadership on employee green behavior. Results also supported that green identity moderated the indirect effect of green transformational leadership on employee green behavior through value congruence, such that the indirect effect was more positive when green identity was high than when it was low. These findings provided valuable contribution to green transformational leadership, value congruence and employee green behavior by exploring the relationship between them. Practical implications and directions for future research are also discussed.

Unlike other creatures, humans developed the ability to cooperate with genetically unrelated strangers and a tendency to comply with social norms. However, humans deviate from social norms in various situations. This study used the modified ultimatum game to explore why humans deviate from social norms and how their prosocial behavior can be promoted. In Study 1, participants were asked to imagine working with an anonymous counterpart to complete a task and obtain a certain amount of money (e.g., ¥10). The computer divided the money randomly in favor of the participant (e.g., 9:1 or 8:2). Participants should decide whether to accept or reject such a self-benefiting division. In the non-risk condition, an absolutely fair redivision of money would take place if participants reject self-benefiting division (e.g. 5:5 or 6:4). By contrast, in the risk condition, other-benefiting redivision of money (e.g., 1:9 or 2:8) would take place if participants rejected the self-benefiting division. Results involving 40 college students showed the main effect of condition. The frequency of accepting self-benefiting division in the risk condition was higher than that in the non-risk condition. As such, compliance with social norms is based on the preservation of material resources. In Study 2, we used economic or moral rewards to compensate for economic loss following compliance with the norm. Results involving 28 college students revealed a significant effect of compensation. The rewards, including moral praise, effectively decreased selfish choices. These findings extend previous studies on social norm compliance by emphasizing the importance of internal, fairness-based balance between material and moral needs, as well as the role of moral praise in promoting prosocial behavior.