2022 9th NAFOSTED Conference on Information and Computer Science (NICS)最新文献_第5页

Comparative Study on Auto-Releasing Mechanisms of Tipper Truck 自卸车自动释放机构的比较研究

2022 9th NAFOSTED Conference on Information and Computer Science (NICS) Pub Date : 2022-10-31 DOI: 10.1109/NICS56915.2022.10013421

T. D. Hong, Y. T. H. Nguyen, Long Thanh Le, M. Q. Pham, T. Huynh, Truong Thanh Nguyen

引用次数: 0

Smart Desk in Hybrid Classroom: Detecting student's lack of concentration when studying 混合教室中的智能桌:检测学生学习时注意力不集中

2022 9th NAFOSTED Conference on Information and Computer Science (NICS) Pub Date : 2022-10-31 DOI: 10.1109/NICS56915.2022.10013468

Manh Hung Le, Thien Minh Doan, Duy Dieu Nguyen, Minh-Son Nguyen

{"title":"Smart Desk in Hybrid Classroom: Detecting student's lack of concentration when studying","authors":"Manh Hung Le, Thien Minh Doan, Duy Dieu Nguyen, Minh-Son Nguyen","doi":"10.1109/NICS56915.2022.10013468","DOIUrl":"https://doi.org/10.1109/NICS56915.2022.10013468","url":null,"abstract":"Students who do not concentrate when studying will find it difficult to absorb the lesson well. Usually, in order for all students to focus on the lesson, the teacher during the lecture will have to observe the students and come up with solutions if the students are not paying attention. However, in the case of many students, following to detect students who have not paid attention to the lesson is a task that requires teachers to put in a lot of effort. In this article, we propose to use machine learning algorithms based on the MediaPipe library to analyze facial features and expressions, including eyes closed, yawning, not looking at the board, or absent, to determine if students have been distracted or not to build a system to assist teachers in detecting student lack of concentration when studying in Smart Desks (Student desks are designed based on embedded devices, with cameras and screens). When detecting that students are not paying attention while studying, the system will warn the teacher so that the teacher can provide solutions. We tested the algorithm on a Jetson Nano embedded device with configuration [Quad-Core 64-bit ARM, 128-bit GPU CUDA, 4GB RAM] and obtained FPS: 8 ~ 18, accuracy achieved from 89 ~ 97% in lighting conditions from 300–400 lux.","PeriodicalId":381028,"journal":{"name":"2022 9th NAFOSTED Conference on Information and Computer Science (NICS)","volume":"16 12","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120917707","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Sentiment Analysis based on word vector representation for short comments in Vietnamese language 基于词向量表示的越南语短评论情感分析

2022 9th NAFOSTED Conference on Information and Computer Science (NICS) Pub Date : 2022-10-31 DOI: 10.1109/NICS56915.2022.10013426

Thien Ho Huong, Kiet Tran-Trung, D. Lai, Vinh Truong Hoang

引用次数: 1

Leveraging Semantic Representations Combined with Contextual Word Representations for Recognizing Textual Entailment in Vietnamese 利用语义表示结合上下文词表示识别越南语文本蕴涵

2022 9th NAFOSTED Conference on Information and Computer Science (NICS) Pub Date : 2022-10-31 DOI: 10.1109/NICS56915.2022.10013423

Quoc-Loc Duong, Duc-Vu Nguyen, N. Nguyen

{"title":"Leveraging Semantic Representations Combined with Contextual Word Representations for Recognizing Textual Entailment in Vietnamese","authors":"Quoc-Loc Duong, Duc-Vu Nguyen, N. Nguyen","doi":"10.1109/NICS56915.2022.10013423","DOIUrl":"https://doi.org/10.1109/NICS56915.2022.10013423","url":null,"abstract":"RTE is a significant problem and is a reasonably active research community. The proposed research works on the approach to this problem are pretty diverse with many different directions. For Vietnamese, the RTE problem is moderately new, but this problem plays a vital role in natural language understanding systems. Currently, methods to solve this problem based on contextual word representation learning models have given outstanding results. However, Vietnamese is a semantically rich language. Therefore, in this paper, we want to present an experiment combining semantic word representation through the SRL task with context representation of BERT relative models for the RTE problem. The experimental results give conclusions about the influence and role of semantic representation on Vietnamese in understanding natural language. The experimental results show that the semantic-aware contextual representation model has about 1% higher performance than the model that does not incorporate semantic representation. In addition, the effects on the data domain in Vietnamese are also higher than those in English. This result also shows the positive influence of SRL on RTE problem in Vietnamese.","PeriodicalId":381028,"journal":{"name":"2022 9th NAFOSTED Conference on Information and Computer Science (NICS)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122480706","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Training Siamese Neural Network Using Triplet Loss with Augmented Facial Alignment Dataset 基于增强面部对齐数据集的三重损失训练Siamese神经网络

2022 9th NAFOSTED Conference on Information and Computer Science (NICS) Pub Date : 2022-10-31 DOI: 10.1109/NICS56915.2022.10013393

Anh Le-Phan, Xuan-Phuc Nguyen, Nga Ly-Tu

引用次数: 0

An Effective Contextual Language Ensemble Model for Vietnamese Aspect-based Sentiment Analysis 面向越南语面向方面情感分析的有效语境语言集成模型

2022 9th NAFOSTED Conference on Information and Computer Science (NICS) Pub Date : 2022-10-31 DOI: 10.1109/NICS56915.2022.10013429

Dang Van Thin, D. Hao, N. Nguyen

引用次数: 2

Improvement on Mechanics Attention Deep Learning model for Classification Ear-tag of Swine 猪耳标分类力学注意深度学习模型的改进

2022 9th NAFOSTED Conference on Information and Computer Science (NICS) Pub Date : 2022-10-31 DOI: 10.1109/NICS56915.2022.10013403

Thinh Pham-Duc, M. Ullah, T. Le-Tien, M. Luong, F. A. Cheikh, Øyvind Nordb⊘

{"title":"Improvement on Mechanics Attention Deep Learning model for Classification Ear-tag of Swine","authors":"Thinh Pham-Duc, M. Ullah, T. Le-Tien, M. Luong, F. A. Cheikh, Øyvind Nordb⊘","doi":"10.1109/NICS56915.2022.10013403","DOIUrl":"https://doi.org/10.1109/NICS56915.2022.10013403","url":null,"abstract":"Classification is a commonly used task that helps computer to resemble human vision in deep neural network problems. In this paper, we investigated the enhanced attention mechanism to improve the model's accuracy and apply the focal loss to deal with the imbalance of data for the ear-tag classification. Briefly, the combination of spatial-channel attention and the current state-of-the-art Convolution Neural Network (CNN), such as ResNet, DenseNet, and EfficientNet enhances model's efficiency in the provided dataset. Moreover, data augmentations namely rotation, shear, Gaussian noise, cropping, and a set of different augmentations are applied to the training phase in which the focal loss is specifically used instead of the traditional cross-entropy (CE) to avoid data imbalance. The research data presented in this paper was collected at a Norwegian farm and manually annotated. An ablation study relating to the augmentation, backbone model, and attention mechanism has proved the importance of each module in the classification. A detailed analysis on the models and their hyperparameters has provided evidence of a significant improvement in the performance.","PeriodicalId":381028,"journal":{"name":"2022 9th NAFOSTED Conference on Information and Computer Science (NICS)","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127281991","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Study on Information Extraction: Application to Administrative Document Images 信息提取技术在行政文件图像中的应用研究

2022 9th NAFOSTED Conference on Information and Computer Science (NICS) Pub Date : 2022-10-31 DOI: 10.1109/NICS56915.2022.10013381

Huu Thang Nguyen, Cong Linh Le, Hoai-Nam Tran, T. A. Tran

引用次数: 0

A Comprehensive Survey of Fuzzy Inference Systems Used for Clustering Problems in WSNs 用于wsn聚类问题的模糊推理系统综述

2022 9th NAFOSTED Conference on Information and Computer Science (NICS) Pub Date : 2022-10-31 DOI: 10.1109/NICS56915.2022.10013479

Trong-Minh Hoang, Anh-Thu Pham, Thanh - Thuy Tran Thi, Van Son Nguyen

引用次数: 0

Proposing System to Recognize Emotions in Public Network Using Phobert Deep Learning Model 基于Phobert深度学习模型的公共网络情绪识别系统

2022 9th NAFOSTED Conference on Information and Computer Science (NICS) Pub Date : 2022-10-31 DOI: 10.1109/NICS56915.2022.10013321

P. N. Huu, T. Anh, Long Hoang Phi, Dinh Dang Dang, Chau Nguyen Le Bao, Q. Minh

引用次数: 0