The purpose of this study is to understand the current state of learners' use of social media in entrepreneurship courses and explore uses and gratifications on social media in entrepreneurship courses from the learners' perspective. The respondents must have participated in government or private entrepreneurship courses and joined the online group of those courses. Respondents are not college students, but more entrepreneurs, and their multi-attribute makes the research results and explanatory more abundant. The methods used are in-depth interviews and questionnaires, (...) a total of 458 valid data was collected. The results of the survey revealed four gratification factors namely trust, profit, learning, and social in online entrepreneurial groups. It is also found that the structures of the four gratification factors vary in three social media (Line, Facebook, and WeChat). In terms of the trust factor, there are significant differences among the three social media. and the score of ''trust'' outranks other factors. Most of the entrepreneurs' business is "networking business", and the business unit is mostly "micro". In short, the two gratification factors of trust and profit can be seen as specific gratifications for online entrepreneurial groups, especially the trust factor, which deserves more attention in the further research of online entrepreneurial courses on social media. (shrink)

Consider the concept combination ‘pet human’. In word association experiments, human subjects produce the associate ‘slave’ in relation to this combination. The striking aspect of this associate is that it is not produced as an associate of ‘pet’, or ‘human’ in isolation. In other words, the associate ‘slave’ seems to be emergent. Such emergent associations sometimes have a creative character and cognitive science is largely silent about how we produce them. Departing from a dimensional model of human conceptual space, this (...) article will explore concept combinations, and will argue that emergent associations are a result of abductive reasoning within conceptual space, that is, below the symbolic level of cognition. A tensor-based approach is used to model concept combinations allowing such combinations to be formalized as interacting quantum systems. Free association norm data is used to motivate the underlying basis of the conceptual space. It is shown by analogy how some concept combinations may behave like quantum-entangled particles. Two methods of analysis were presented for empirically validating the presence of non-separable concept combinations in human cognition. One method is based on quantum theory and another based on comparing a joint probability distribution with another distribution based on a separability assumption using a chi-square goodness-of-fit test. Although these methods were inconclusive in relation to an empirical study of bi-ambiguous concept combinations, avenues for further refinement of these methods are identified. (shrink)

In coal mining industry, the running state of mine ventilators plays an extremely significant role for the safe and reliable operation of various industrial productions. To guarantee the better reliability, safety, and economy of mine ventilators, in view of early detection and effective fault diagnosis of mechanical faults which could prevent unscheduled downtime and minimize maintenance fees, it is imperative to construct some viable mathematical models for mine ventilator fault diagnosis. In this article, we plan to establish a data-based mine (...) ventilator fault diagnosis method to handle situations where engineers are absent or they are incapable of coming to a conclusion from multisource data. In the process of building the mine ventilator fault diagnosis model, considering that probabilistic rough sets could reduce the errors triggered by incompleteness, inconsistency, and inaccuracy without needing any additional assumptions and Pythagorean fuzzy multigranulation rough sets over the two universes’ model could effectively handle data representation, fusion, and analysis issues, we generalize the existing PF MGRSs over the two universes’ model to the PRS setting, as well as to further establish a novel model named Pythagorean fuzzy multigranulation probabilistic rough sets over two universes. In the granular computing paradigm, three types of PF MG-PRSs over two universes based on the risk attitude of engineers are proposed at first. Afterwards, several basic propositions of the newly proposed model are explored. Moreover, a PF multigranulation probabilistic model for mine ventilator fault diagnosis based on PF MG-PRSs over two universes is investigated. At last, a real-world case study of dealing with a mine ventilator fault diagnosis problem is given to illustrate the practicality of the presented model, and a validity test, a sensitivity analysis, and a comparison analysis are further explored to demonstrate the effectiveness of the presented model. (shrink)

A superheterodyne receiver is a type of device universally used in a variety of electronics and information systems. Fault detection and diagnosis for superheterodyne receivers are therefore of critical importance, especially in noise environments. A general purpose fault detection and diagnosis scheme based on observers and residual error analysis was proposed in this study. In the scheme, two generalized regression neural networks are utilized for fault detection, with one as an observer and the other as an adaptive threshold generator; faults (...) are detected by comparing the residual error and the threshold. Then, time and frequency domain features are extracted from the residual error for diagnosis. A probabilistic neural network acts as a classifier to realize the fault diagnosis. Finally, to mimic electromagnetic environments with noise interference, simulation model under different fault conditions with noise interferences is established to test the effectiveness and robustness of the proposed fault detection and diagnosis scheme. Results of the simulation experiments proved that the presented method is effective and robust in simulated electromagnetic environments. (shrink)

Diminishing awareness is a consequence of the information explosion: disciplines are becoming increasingly specialized; individuals and groups are becoming ever more insular. This paper considers how awareness can be enhanced via abductive knowledge discovery the goal of which is to produce suggestions which can span disparate islands of knowledge. Knowledge representation is motivated from a cognitive perspective. Words and concepts are represented as vectors in a high dimensional semantic space automatically derived from a text corpus. Information flow computation between vectors (...) is proposed as a means of suggesting potentially interesting implicit associations between concepts. Information flow is applied to computational scientific discovery by attempting to simulate Swanson's Raynaud-fish oil discovery in medical texts. Both automatic and semi-automatic attempts were studied and compared against suggestions computed via semantic association. Even though this work is preliminary and speculative in nature, there is some justification to believe that appropriate suggestions can be “abduced” from semantic space. (shrink)

Spiritual pedagogy as a new educational theory aims to apply cultural and spiritual values in classroom practices. It has been the focus of research in different fields such as counselling, management, and science in the past decades. However, its application in second/foreign language research and practice has been widely overlooked by L2 researchers, to date. To fill this gap, the present study made an effort to provide a theoretical analysis of the conceptualizations, scientific background, benefits, and practical techniques to implement (...) SP in the context of L2 education. In so doing, this paper suggests a number of practices through which SP can be integrated into L2 education among which positive psychology was more highlighted. Additionally, some practical implications were provided for EFL teachers, teacher trainers, students, curriculum designers, and researchers to enhance their knowledge of spirituality and education. In the end, different suggestions for future research were presented to move this research domain forward. (shrink)

Rationale: Deep brain stimulation (DBS) of the hippocampus is proposed for enhancement of memory impaired by injury or disease. Many pre-clinical DBS paradigms can be addressed in epilepsy patients undergoing intracranial monitoring for seizure localization, since they already have electrodes implanted in brain areas of interest. Even though epilepsy is usually not a memory disorder targeted by DBS, the studies can nevertheless model other memory-impacting disorders, such as Traumatic Brain Injury (TBI). Methods: Human patients undergoing Phase II invasive monitoring for (...) intractable epilepsy were implanted with depth electrodes capable of recording neurophysiological signals. Subjects performed a delayed-match-to-sample (DMS) memory task while hippocampal ensembles from CA1 and CA3 cell layers were recorded to estimate a multi-input, multi-output (MIMO) model of CA3-to-CA1 neural encoding and a memory decoding model (MDM) to decode memory information from CA3 and CA1 neuronal signals. After model estimation, subjects again performed the DMS task while either MIMO-based or MDM-based patterned stimulation was delivered to CA1 electrode sites during the encoding phase of the DMS trials. Each subject was sorted (post hoc) by prior experience of repeated and/or mild-to-moderate brain injury (RMBI), TBI, or no history (control) and scored for percentage successful delayed recognition (DR) recall on stimulated vs. non-stimulated DMS trials. The subject’s medical history was unknown to the experimenters until after individual subject memory retention results were scored. Results: When examined compared to control subjects, both TBI and RMBI subjects showed increased memory retention in response to both MIMO and MDM-based hippocampal stimulation. Furthermore, effects of stimulation were also greater in subjects who were evaluated as having pre-existing mild-to-moderate memory impairment. Conclusion: These results show that hippocampal stimulation for memory facilitation was more beneficial for subjects who had previously suffered a brain injury (other than epilepsy), compared to control (epilepsy) subjects who had not suffered a brain injury. This study demonstrates that the epilepsy/intracranial recording model can be extended to test the ability of DBS to restore memory function in subjects who previously suffered a brain injury other than epilepsy, and support further investigation into the beneficial effect of DBS in TBI patients. (shrink)

Diminishing awareness is a consequence of the information explosion: disciplines are becoming increasingly specialized; individuals and groups are becoming ever more insular. This article considers how awareness can be enhanced via operational abductive systems. The goal is to generate and justify suggestions which can span disparate islands of knowledge. Knowledge representation is motivated from a cognitive perspective. Words and concepts are represented as vectors in a high dimensional semantic space automatically derived from a text corpus. Various mechanisms will be presented (...) for computing suggestions from semantic space: information flow, semantic similarity, pre-inductive generalization. The overall goal of this article is to introduce semantic space to the model-based reasoning and abduction community and to illustrate its potential for principled, operational abduction by semi-automatically replicating the Swanson Raynaud/fish oil discovery in medical text. (shrink)

Consider the concept combination ‘pet human’. In word association experiments, human subjects produce the associate ‘slave’ in relation to this combination. The striking aspect of this associate is that it is not produced as an associate of ‘pet’, or ‘human’ in isolation. In other words, the associate ‘slave’ seems to be emergent. Such emergent associations sometimes have a creative character and cognitive science is largely silent about how we produce them. Departing from a dimensional model of human conceptual space, this (...) article will explore concept combinations, and will argue that emergent associations are a result of abductive reasoning within conceptual space, that is, below the symbolic level of cognition. A tensor-based approach is used to model concept combinations allowing such combinations to be formalized as interacting quantum systems. Free association norm data is used to motivate the underlying basis of the conceptual space. It is shown by analogy how some concept combinations may behave like quantum-entangled particles. Two methods of analysis were presented for empirically validating the presence of non-separable concept combinations in human cognition. One method is based on quantum theory and another based on comparing a joint probability distribution with another distribution based on a separability assumption using a chi-square goodness-of-fit test. Although these methods were inconclusive in relation to an empirical study of bi-ambiguous concept combinations, avenues for further refinement of these methods are identified. (shrink)