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Asymmetric information and corporate risk management by using foreign currency derivatives
No full textLittle brown bats (Myotis lucifugus) recognize individual identity of conspecifics using sonar calls
No full textEvaluation of a Peer Mentoring Program for Early Career Gerontological Nursing Faculty and Its Potential for Application to Other Fields in Nursing and Health Science
No full textOrbitDANN: A Mechanism-Informed Transfer Learning Method for Automatic Fault Diagnosis of Turbomachinery
No full textThe traditional feature-based fault diagnosis methods for turbomachinery largely rely on manual extraction and selection of features. However, this introduces additional uncertainties into the modeling process. Furthermore, practical applications often suffer from insufficient sensor data for specific fault modes, resulting in inaccurate diagnosis results. This article presents a mechanism-informed adversarial transfer learning approach integrated with domain-adversarial neural network (DANN) for turbomachinery fault diagnosis. It aims to enhance the diagnosis accuracy even when only a small amount of sensor data is available. This approach seamlessly integrates physics-embedded axis orbits corresponding to various fault modes in different turbomachines with the DANN model, so-called orbit-based DANN (OrbitDANN). We have developed a generalized procedure to implement this proposed method for automatic fault diagnosis in various turbomachines. Orbit images are generated from both simulated signals and measured sensor data to illustrate the accuracy and feasibility of the proposed model. Parametric sensitivity analysis is conducted to establish an optimal model for fault diagnosis. In a comparative study with feature-based back-propagation and convolutional neural network (CNN) models using a limited amount of real-world data, we demonstrate the advantages of the proposed model and procedure. This study offers a promising approach to constructing a general artificial intelligence (AI) model to support predictive maintenance of turbomachinery, even when only a small amount of actual sensor data is available
Increasing Cultural Competency to Reduce Bias in the Business Ecosystem
No full textThis paper connects the ideologies of cultural competence to the diverse business ecosystem. Contributing to the body of knowledge the critical need for cultural competency in business. Providing practical suggestions for leaders to enhance cultural competency within their organization. Written for practitioners to provide an understanding of cultural competency and business ecosystems. It includes business rationales for increasing cultural competency and reducing biases within operations. It is widely regarded that cultural competence is a fundamental requirement for working effectively with diverse people and have both intangible and tangible benefits. This paper discusses the benefits of cultural competence in business ecosystems
The Wind in the Willows, Vol. 3. The Gates of Dawn. Based on the novel by Kenneth Grahame.
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