Based Learning

In this paper, we propose a wavelet type-2 fuzzy brain imitated controller (WT2FBIC) for nonlinear robotic systems. The suggested method combines a wavelet type-2 fuzzy system (WT2FS) and a brain imitated controller (BIC) to improve learning efficiency.

11p viling 11-10-2024 1 1   Download

In this study, we explore the potential of graph neural networks (GNNs), in combination with transfer learning, for the prediction of molecular solubility, a crucial property in drug discovery and materials science. Our approach begins with the development of a GNN-based model to predict the dipole moment of molecules.

8p viling 11-10-2024 1 1   Download

This paper introduces a new clustering technique based on granular computing. In tradional clustering algorithms, the integration of the high shaping capability of the existing datasets becomes fussy which in turn results in inferior functioning.

8p viling 11-10-2024 3 1   Download

This research aimed to investigate teachers’ perceptions and practices of projectbased learning (PBL) in teaching speaking skill at some high schools in a Central Vietnam province. The mixed methods research was adopted with the population of twenty-five teachers of English as a foreign language (EFL).

16p viling 11-10-2024 1 0   Download

This study explored community members’ perceptions of service-learning (SL) activities of pre-service primary school teachers (PSTs) of a university in Vietnam. More specifically, the study aimed at investigating how community members (CMs) perceive the impacts of SL activities organized at primary school settings on primary school students and the professional development of PSTs.

15p viling 11-10-2024 2 1   Download

Low-rank representation (LRR) plays a significant role in image classification tasks due to its ability to capture the underlying structure and variations in image data. However, traditional low-rank representation-based dictionary learning methods struggle to leverage discriminative information effectively.

9p viling 11-10-2024 3 1   Download

The process of neural stem cell (NSC) differentiation into neurons is crucial for the development of potential cell-centered treatments for central nervous system disorders. However, predicting, identifying, and anticipating this differentiation is complex. In this study, we propose the implementation of a convolutional neural network model for the predictable recognition of NSC fate, utilizing single-cell brightfield images.

7p viengfa 28-10-2024 2 2   Download

In this paper, we propose an effective AMC using deep learning (DL) for flexible and adaptive OFDM-based optical networks. The proposed DL-based AMC is able to classify four typical modulation schemes such as binary phase-shift keying (BPSK), quadrature PSK (QPSK), 8-PSK, and 16- quadrature amplitude modulation (QAM) in dynamic network conditions.

6p viengfa 28-10-2024 3 2   Download

This paper is structured as follows. The following section presents related work. Section 3 summarizes the characteristics of the two datasets utilized in the model and the system’s overall architecture for image-based disease diagnosis. Section 4 provides our experimental results that compare the performance metrics with other studies.

6p viengfa 28-10-2024 3 2   Download

Sentiment Analysis and Opinion Mining have emerged as highly popular fields for analyzing and extracting valuable information from textual data sourced from diverse platforms like Facebook, Twitter, and Amazon. These techniques hold a crucial role in empowering businesses to actively enhance their strategies by gaining comprehensive insights into customers' feedback regarding their products.

6p viengfa 28-10-2024 4 2   Download

This study proposes to test a combination model between CNN network and XGBoost algorithm for weather image classification problem. The proposed model uses deep learning network, namely CNN for feature extraction, then feeds the features into the XGBoost classifier to recognize the images.

6p viengfa 28-10-2024 1 1   Download

Despite certain advancements achieving high accuracy, current methods still require substantial improvements to be applicable in practical scenarios. Diverging from text detection in images/videos, this paper addresses the issue of text detection within license plates by amalgamating multiple frames of distinct perspectives.

10p viengfa 28-10-2024 5 2   Download

This study intends to investigate the task-based language teaching (TBLT), known for its effectiveness in English Language Teaching (ELT) to improve students' communicative English skills. The study also aims to get insights into students' perspectives on learning grammar through Task-Based Language Teaching (TBLT).

13p viengfa 28-10-2024 2 1   Download

The study aims at examining EFL teachers’ perceptions on their roles and how they occupy these roles in project-based learning at a Vietnamese state university. Narrative interviews were employed to collect qualitative data with the participation of five teachers at the Faculty of Foreign Languages at Ho Chi Minh City University of Technology and Education.

8p viengfa 28-10-2024 1 1   Download

Accurate forecasting of the electrical load is a critical element for grid operators to make well-informed decisions concerning electricity generation, transmission, and distribution. In this study, an Extreme Learning Machine (ELM) model was proposed and compared with four other machine learning models including Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU).

10p viengfa 28-10-2024 2 1   Download

Artificial neural networks, which are an essential tool in Machine Learning, are used to solve many types of problems in different fields. This article will introduce an application of the artificial neural network model in the diagnosis of heart disease based on the heart.csv data file.

6p viengfa 28-10-2024 2 2   Download

Predicting the macroscopic permeability of porous media is critical in various scientific and engineering applications. This study proposes a novel model that combines Random Forest (RF) and rime-ice (RIME) optimization algorithm, denoted RIME-RF-RIME, to predict permeability based on six key features covering fluid phase dimensions, geometric characteristics, surrounding phase permeability, and media porosity.

14p viengfa 28-10-2024 2 2   Download

Efficient ship detection is essential for inland waterway management. Recent advances in artificial intelligence have prompted research in this field. This study introduces a real-time ship detection model utilizing computer vision and the YOLO object detection framework.

14p viengfa 28-10-2024 2 2   Download

This paper develops an Artificial Neural Network (ANN) model based on 96 experimental data to forecast the dynamic modulus of asphalt concrete mixtures. This study applied the repeated KFold cross-validation technique with 10 folds on the training data set to make the simulation results more reliable and find a model with more general predictive power.

9p viengfa 28-10-2024 5 2   Download

In this study, an artificial neural networkbased Bayesian regularization (ANN) model is proposed to predict the compressive strength of concrete. The database in this study includes 208 experimental results synthesized from laboratory experiments with 9 input variables related to temperature change and design material composition.

12p viengfa 28-10-2024 2 2   Download