VNU Journal of Science: Computer Science and Communication Engineering最新文献_第2页

A Thermal Cycler based on Solid-state Active Heat Pump and PID Control Algorithm toward Biomedical Applications 基于固态主动热泵和PID控制算法的生物医学应用热循环器

VNU Journal of Science: Computer Science and Communication Engineering Pub Date : 2022-12-16 DOI: 10.25073/2588-1086/vnucsce.298

Loc Xuan Pham, T. Bui, T. D. Chu

{"title":"A Thermal Cycler based on Solid-state Active Heat Pump and PID Control Algorithm toward Biomedical Applications","authors":"Loc Xuan Pham, T. Bui, T. D. Chu","doi":"10.25073/2588-1086/vnucsce.298","DOIUrl":"https://doi.org/10.25073/2588-1086/vnucsce.298","url":null,"abstract":"The demand for a compact, easy-to-use and precise thermal cycler is always extremely high in biomedical field due to the decisive role of temperature in determining the accuracy of many biomedical applications. In this study, a new design of thermal cycler is proposed to improve the ease of manipulation as well as production process while maintaining the required accuracy of temperature handling. Specifically, a semiconductor component called Peltier is utilized as the main heat generation source in this work, which offers an operation range of 15-80°C. As Peltier has already been mass produced in the market and gained its popularity by appearing in many home appliances, the production cost and time could be minimized. Additionally, by applying the PID control algorithm, the accuracy of the proposed system could be maintained (maximum variation within 1°C in case of Isothermal Amplification and 2°C in case of Temperature Cycling Amplification) as compared with other thermal cyclers with sophisticated heating technology. The thermal cycler proposed in this work is expected to be further developed to be integrated into the microfluidic chip for rapid virus detection applications.","PeriodicalId":416488,"journal":{"name":"VNU Journal of Science: Computer Science and Communication Engineering","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121651090","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

The VNNLI - VLSP 2021: Leveraging Contextual Word Embedding for NLI Task on Bilingual Dataset VNNLI - VLSP 2021:利用上下文词嵌入在双语数据集上的NLI任务

VNU Journal of Science: Computer Science and Communication Engineering Pub Date : 2022-12-16 DOI: 10.25073/2588-1086/vnucsce.317

Quoc-Loc Duong

引用次数: 0

ViMRC - VLSP 2021: Using XLM-RoBERTa and Filter Output for Vietnamese Machine Reading Comprehension ViMRC - VLSP 2021:使用XLM-RoBERTa和过滤器输出进行越南语机器阅读理解

VNU Journal of Science: Computer Science and Communication Engineering Pub Date : 2022-12-16 DOI: 10.25073/2588-1086/vnucsce.336

Văn Nhân Đặng, Minh Le Nguyen

{"title":"ViMRC - VLSP 2021: Using XLM-RoBERTa and Filter Output for Vietnamese Machine Reading Comprehension","authors":"Văn Nhân Đặng, Minh Le Nguyen","doi":"10.25073/2588-1086/vnucsce.336","DOIUrl":"https://doi.org/10.25073/2588-1086/vnucsce.336","url":null,"abstract":"Machine Reading Comprehension (MRC) has recently made significant progress. This paper is the result of our participation in building an MRC system specifically for Vietnamese on Vietnamese Machine Reading Comprehension at the 8th International Workshop on Vietnamese Language and Speech Processing (VLSP 2021). Based on SQuAD2.0, the organizing committee developed the Vietnamese Question Answering Dataset UIT-ViQuAD2.0, a reading comprehension dataset consisting of questions posed by crowd-workers on a set of Wikipedia Vietnamese articles. The UIT-ViQuAD2.0 dataset evolved from version 1.0 with the difference that version 2.0 contained answerable and unanswerable questions. The challenge of this problem is to distinguish between answerable and unanswerable questions. The answer to every question is a span of text, from the corresponding reading passage, or the question might be unanswerable. Our system employs simple yet highly effective methods. The system uses a pre-trained language model called XLM-RoBERTa (XLM-R), combined with filtering results from multiple output files to produce the final result. We created about 5-7 output files and select the answers with the most repetitions as the final prediction answer. After filtering, our system increased from 75.172% to 76.386% at the F1 measure and achieved 65,329% in the EM measure on the Private Test set.","PeriodicalId":416488,"journal":{"name":"VNU Journal of Science: Computer Science and Communication Engineering","volume":"18 6","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120921725","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

ViMRC VLSP 2021: XLM-R versus PhoBERT on Vietnamese Machine Reading Comprehension ViMRC VLSP 2021: XLM-R与PhoBERT在越南语机器阅读理解上的对比

VNU Journal of Science: Computer Science and Communication Engineering Pub Date : 2022-12-16 DOI: 10.25073/2588-1086/vnucsce.334

Nhat Nguyen Duy, Phong Nguyen-Thuan Do

引用次数: 0

ViMRC - VLSP 2021: Improving Retrospective Reader for Vietnamese Machine Reading Comprehension ViMRC - VLSP 2021:改进越南语机器阅读理解的回顾性阅读器

VNU Journal of Science: Computer Science and Communication Engineering Pub Date : 2022-12-16 DOI: 10.25073/2588-1086/vnucsce.346

Quan Quoc Chu, Vi Van Ngo, N. H. Le, Duc Sy Nguyen

{"title":"ViMRC - VLSP 2021: Improving Retrospective Reader for Vietnamese Machine Reading Comprehension","authors":"Quan Quoc Chu, Vi Van Ngo, N. H. Le, Duc Sy Nguyen","doi":"10.25073/2588-1086/vnucsce.346","DOIUrl":"https://doi.org/10.25073/2588-1086/vnucsce.346","url":null,"abstract":"In recent years, there are multiple systems (eg. search engines and dialogue systems) that require machines to be able to read and understand human text to serve several tasks in application. Machine Reading Comprehension (MRC) has posed a challenge to the Natural Language Processing (NLP) community in teaching machines to understand the meaning of human text in order to answer questions provided. Specifically in this challenge, the dataset contains questions that can be unanswerable, otherwise the answers can be extracted from the given passages. To deal with this challenge, our works mainly based on a recent approach, known as Retrospective Reader, to confronting unanswerable questions. Additionally, we focuses on enhancing the ability of answer extraction by applying properly attention mechanism and improving the representation ability through semantic information. Besides, we also present an ensemble way to acquire significant improvement in results provided by single models. Our method achieves 1$^{st}$ place on Vietnamese MRC shared task at the $8^{th}$ International Workshop on Vietnamese Language and Speech Processing (VLSP) with F1-score of textbf{0.77241} and exact match (EM) of textbf{0.66137} on the private test phase. For research purpose, our source code is available at url{https://github.com/NamCyan/MRC_VLSP2021}","PeriodicalId":416488,"journal":{"name":"VNU Journal of Science: Computer Science and Communication Engineering","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132431092","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

ViMRC - VLSP 2021: Context-Aware Answer Extraction in Vietnamese Question Answering ViMRC - VLSP 2021:越南语问答中的上下文感知答案提取

VNU Journal of Science: Computer Science and Communication Engineering Pub Date : 2022-12-16 DOI: 10.25073/2588-1086/vnucsce.316

Thi-Thu-Hong Le

引用次数: 0

On-chip All-optical Haar Transform based on a 4x4 MMI coupler cascaded with a 2x2 MMI coupler for Image Compression 基于4x4 MMI耦合器级联2x2 MMI耦合器的片上全光Haar变换用于图像压缩

VNU Journal of Science: Computer Science and Communication Engineering Pub Date : 2022-12-16 DOI: 10.25073/2588-1086/vnucsce.446

T. Le, T. Bui, The Ngoc Dang

引用次数: 0

VLSP 2021 - vnNLI Challenge: Vietnamese and English-Vietnamese Textual Entailment VLSP 2021 - vnli挑战:越南语和英越语文本蕴涵

VNU Journal of Science: Computer Science and Communication Engineering Pub Date : 2022-12-16 DOI: 10.25073/2588-1086/vnucsce.363

Q. T. Ngo, Anh Tuan Hoang, Huyen Nguyen, Lien Nguyen

{"title":"VLSP 2021 - vnNLI Challenge: Vietnamese and English-Vietnamese Textual Entailment","authors":"Q. T. Ngo, Anh Tuan Hoang, Huyen Nguyen, Lien Nguyen","doi":"10.25073/2588-1086/vnucsce.363","DOIUrl":"https://doi.org/10.25073/2588-1086/vnucsce.363","url":null,"abstract":"This paper presents the first challenge on recognizing textual entailment (RTE), also known as natural language inference (NLI), held in a Vietnamese Language and Speech Processing workshop (VLSP 2021).The challenge aims to determine, for a given pair of sentences, whether the two sentences semantically agree, disagree, or are neutral/irrelevant to each other. The input sentences are in English or Vietnamese and may not be in the same language. This task is important in identifying, from different information sources, the evidence that supports or refutes a statement. The identification of such evidence is subsequently useful for many information tracking applications, such as opinion mining, brand and reputation management, and particularly fighting against fake news.Through this challenge, we would like to provide an opportunity for participants who are interested in the problem, to contribute their knowledge to improve the existing techniques and methods for the task, so as to enhance the effectiveness of those applications.In the paper, we introduce a collection of Vietnamese and English sentences in the domain of health that we built to serve as a benchmarking dataset for the task. We also describe the evaluation results of systems participating in the challenge.","PeriodicalId":416488,"journal":{"name":"VNU Journal of Science: Computer Science and Communication Engineering","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121661122","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: 4

HEVC Compatible Multiple Description Coding for Robust Video Transmission over Lossy Networks HEVC兼容多描述编码在有损网络上的鲁棒视频传输

VNU Journal of Science: Computer Science and Communication Engineering Pub Date : 2022-12-16 DOI: 10.25073/2588-1086/vnucsce.309

Huy Phi Cong, Xiem Hoang Van, Duong Trieu Dinh

引用次数: 0

VLSP 2021 - VieCap4H Challenge: Automatic Image Caption Generation for Healthcare Domain in Vietnamese VLSP 2021 - VieCap4H挑战:越南医疗保健领域的自动图像标题生成

VNU Journal of Science: Computer Science and Communication Engineering Pub Date : 2022-12-16 DOI: 10.25073/2588-1086/vnucsce.341

Thao Minh Le, Long Hoang Dang, Thanh-Son Nguyen, Huyen Nguyen, Xuan-Son Vu

引用次数: 7