Social value of maintaining baby-friendly hospital initiative accreditation in Australia: case study by Andini Pramono, Julie Smith, Jane Desborough, Siobhan Bourke

“…We interviewed the hospital’s Director of Maternity Services and the Clinical Midwifery Educator, guided by a structured questionnaire, which examined the cost (financial, time and other resources) and benefits of each of the Ten Steps. …”
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Implementing blended learning in emergency airway management training: a randomized controlled trial by Madeleine Huei Tze Kho, Keng Sheng Chew, Muhaimin Noor Azhar, Mohd Lotfi Hamzah, Kee Man Chuah, Aida Bustam, Hiang Chuan Chan

“…Blended learning (BL) refers to the systematic integration of online and face-to-face learning aimed to facilitate complex thinking skills and flexible participation at a reduced financial, time and manpower cost. This study was conducted to evaluate its effectiveness in emergency airway management training. …”
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Overcoming the pitfalls in employee performance evaluation: An application of ratings mode of the Analytic Hierarchy Process by Rafikul Islam, Nagendran Periaiah

“…FINDINGS: Five criteria, namely Services, Quality, Financial, Timing, and Teamwork, are found to be important for the evaluation of employee performance at CLSB. …”
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Análisis de cambio de régimen en series de tiempo no lienales utilizando modelos TAR by Fredy Pérez, Velásquez Hermilson

“…Clasificación JEL: C23, C51   Abstract:   In some situations, theoreticians recommend a given predictive model for a series of financial time. However, some inappropriate behaviors in given series make such a model unsuitable. …”
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Educational Level Is Related to Physical Fitness in Patients with Type 2 Diabetes - A Cross-Sectional Study. by Lara Allet, Olivier Giet, Jérôme Barral, Nicolas Junod, Dominique Durrer, Francesca Amati, Gerasimos P Sykiotis, Pedro Marques-Vidal, Jardena J Puder

“…Such programs should be structured and integrate the norms, needs and capacities (financial, time, physical capacities and self-efficacy) of this population, and their effectiveness should be tested in future studies.University of Lausanne clinicaltrials.gov NCT01289587.…”
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Structure learning in high-dimensional graphical models by Wang, Yuhao,Ph.D.Massachusetts Institute of Technology.

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Podemos prever a taxa de cambio brasileira? Evidência empírica utilizando inteligência computacional e modelos econométricos Can we forecast Brazilian exchange rates? Empirical evi... by Leandro dos Santos Coelho, André Alves Portela Santos, Newton Carneiro Affonso da Costa Jr.

“…In Finance applications, there is evidence that these computational intelligence models are able to provide a more accurate forecast given their capacity for capturing nonlinearities and other stylized facts of financial time series. Thus, this paper investigates the hypothesis that the mathematical models of multilayer perception, radial basis function neural networks (NN), and the Takagi-Sugeno (TS) fuzzy systems are able to provide a more accurate out-of-sample forecast than the traditional AutoRegressive Moving Average (ARMA) and ARMA Generalized AutoRegressive Conditional Heteroskedasticity (ARMA-GARCH) models. …”
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Bayesian nonparametric learning of complex dynamical phenomena by Fox, Emily Beth

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Essays on behavioral heterogeneity and asset pricing by Li, Changtai

“…HAMs with interacting agents have the ability to explain most of the stylized facts observed in financial time series. Combining with sentiment, HAMs could be more powerful to demonstrate the role of investor’s behavior in asset pricing. …”
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Application of Deep Learning Architectures in Stock Price Forecasting: A Convolutional Neural Network ‎Approach by Amir Sharif far, Maryam Khaliliaraghi, Iman Raeesi Vanani, Mirfeyz Fallahshams

“…Upon running the model with various architectures and parameters for the stock price of Esfahan Steel Company, the results showed that a CNN with max-pooling layers (a combination of Batch size=64, filters=256, and ReLU Activation Function) and Mean Absolute Percentage Error (MAPE) of 1.79% and Normalized Root Mean Square Error (NRMSE) of 2.71% had a higher prediction accuracy than other CNN architectures and Recurrent Neural Network (RNN).IntroductionAmong the various deep learning techniques that have many applications in different sciences, specific algorithms like Recurrent Neural Network (RNN), Long Short-Term Memory (LSTM), and Convolutional Neural Network (CNN) have been used by researchers due to their characteristics of financial time series (Sezer, Gudelek, & Ozbayoglu, 2020). …”
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