Uncertainty in Recurrent Neural Network with Dropout

Recurrent Neural Network is a powerful tool for processing temporal data. However, assessing prediction uncertainty from recurrent models has proven challenging. This thesis attempts to evaluate the validity of uncertainty from recurrent models using dropout. Traditional neural network focuses on optimising data likelihood; in order to obtain model and predictive uncertainty, we need to, instead, optimise model posterior. Model posterior is usually intractable, thus we employ various dropout based approach, in the form of variational Bayesian Monte Carlo, to estimate the learning objective. This technique is applied to existing recurrent neural network benchmarks MIMIC-III. The thesis shows that Monte Carlo dropout applied to recurrent neural network can give comparable performance to the current state of the art methods, and meaningful uncertainty of predictions

Family of Circulant Graphs and Its Expander Properties

In this thesis, we apply spectral graph theory to show the non-existence of an expander family within the class of circulant graphs. Using the adjacency matrix and its properties, we prove Cheeger\u27s inequalities and determine when the equalities hold. In order to apply Cheeger\u27s inequalities, we compute the spectrum of a general circulant graph and approximate its second largest eigenvalue. Finally, we show that circulant graphs do not contain an expander family

A Deep Learning Model for Splicing Image Detection

With the advancement of digital technology, manipulating images has become relatively easy through many photo editing techniques. One of the techniques is the splicing image method, which crops parts of images and puts them into another image creating a new composite image. The image splicing detection system is soon regarded as an exciting topic for many researchers to solve the problems of forgery images on the Internet, especially in social networks. ResNet-50 and VGG-16 are powerful architectures of convolutional neural networks, but they reveal many weaknesses when operating on low-end computers. The ultimate goal of this research is to create a model for image splicing detection working well in limited memory machines. The study proposes the model, which is the improvement of VGG-16 applying residual network (ResNet). As a result, the proposed model achieves a test accuracy of 92.5% while the ResNet-50 gives an accuracy of 85.6% after 20 epochs of training 9,319 images from the CASIA v2.0 dataset, which are used for forgery classification. The result proves the efficiency of the proposed model for image splicing detection, especially when working on low-end computers

EFL SECONDARY AND HIGH SCHOOL STUDENTS’ PERCEPTIONS OF ADVANTAGES AND DIFFICULTIES OF WRITTEN FEEDBACK BY QUESTIONING IN WRITING

This paper reports a descriptive study to enquire into English as a Foreign Language (EFL) secondary and high school (K-12) students’ perceptions about the advantages and difficulties of written feedback by questioning in writing. This paper draws on the data collected as part of a larger project including questionnaires and focus-group interviews. The findings reveal that students held positive perceptions about the impact of written feedback by questioning in writing, particularly on motivation, writing skills, and attitudes and preferences.  Article visualizations

Identification and characteristics of MYB4 transcription factor related to regulation of abiotic stress tolerance in peanut

Peanut (Arachis hypogaea L.), an economically valuable crop, provides protein and oil for human and animal consumption. The transcription factor MYB4 has been identified as a potential drought tolerance gene in peanut. This study aimed to isolate and characterize the MYB4 gene in the L14 peanut cultivar. The isolated AhL14_MYB4 gene was found to be 1.1 kb long, with a 663 bp coding sequence containing 3 exons and 2 introns. In silico analysis showed that AhL14_MYB4 possesses a nuclear localization signal and two DNA-binding domains characteristic of transcription factors. The findings revealed key molecular features of AhL14_MYB4 and provided insights into improving drought resistance in peanut varieties. Further research on AhL14_MYB4 may aid efforts to enhance drought tolerance in local peanut cultivars through molecular breeding or genetic engineering. Overall, this finding about preliminary characterization of the peanut MYB4 gene lays the groundwork for potential genetic improvements to this economically important crop