计算机工程与设计最新文献_第3页

Developing a news classifier for Greek using BERT 使用BERT开发希腊语新闻分类器

计算机工程与设计 Pub Date : 2022-09-23 DOI: 10.1109/SEEDA-CECNSM57760.2022.9932996

George Gkolfopoulos, Iraklis Varlamis

{"title":"Developing a news classifier for Greek using BERT","authors":"George Gkolfopoulos, Iraklis Varlamis","doi":"10.1109/SEEDA-CECNSM57760.2022.9932996","DOIUrl":"https://doi.org/10.1109/SEEDA-CECNSM57760.2022.9932996","url":null,"abstract":"Text categorization is a significant task in the re-search field of text mining, which has recently benefited from deep neural network algorithms and advanced learning techniques that extract language models from large textual corpora. These Pre-Trained Language Models are the main components of state-of-the-art solutions in many natural language processing and text-mining tasks can be very generic, trained in generic text corpora, or domain-specific when they employ large corpora from specific application domains (e.g. social media, news, sciences, etc.). When only generic language models are available the overall performance in the task can be improved by adapting or fine-tuning the model used for the task, e.g. the classifier. Although multilingual language models are reported in the literature, such models are usually language-specific. This work presents a news article classifier, which has been trained on a small corpus and employs a Greek version of BERT language model. Comparison with existing machine learning-based classifiers shows that the proposed method outperforms well-known methods in text classification. In addition, the proposed approach allows the continuous training of the classifier through user-provided feedback on falsely classified articles.","PeriodicalId":68279,"journal":{"name":"计算机工程与设计","volume":"64 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2022-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77510273","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

Tracking individuals’ health using mobile applications and Machine Learning 使用移动应用程序和机器学习跟踪个人健康状况

计算机工程与设计 Pub Date : 2022-09-23 DOI: 10.1109/SEEDA-CECNSM57760.2022.9932927

Giannis Botilias, Lamprini Pappa, P. Karvelis, C. Stylios

引用次数: 1

Parameter Tuning of Linear Programming Solvers 线性规划求解器的参数整定

计算机工程与设计 Pub Date : 2022-09-23 DOI: 10.1109/SEEDA-CECNSM57760.2022.9933002

N. Ploskas

引用次数: 0

beHost: A web application for potential accommodation providers interested in participating in the sharing economy beHost:一个面向有兴趣参与共享经济的潜在住宿供应商的web应用程序

计算机工程与设计 Pub Date : 2022-09-23 DOI: 10.1109/SEEDA-CECNSM57760.2022.9932936

Foteini Tatsi, Fotios Tatsis, K. Karamanis

引用次数: 0

Security and Privacy Vulnerabilities in Human Activity Recognition systems 人体活动识别系统中的安全和隐私漏洞

计算机工程与设计 Pub Date : 2022-09-23 DOI: 10.1109/SEEDA-CECNSM57760.2022.9932957

V. Liagkou, S. Sakka, C. Stylios

引用次数: 0

An experimental protocol for exploration of stress in an immersive VR scenario with EEG 在一个沉浸式虚拟现实场景与脑电图探索压力的实验协议

计算机工程与设计 Pub Date : 2022-09-23 DOI: 10.1109/SEEDA-CECNSM57760.2022.9932987

Andreas Miltiadous, Vasileios Aspiotis, Konstantinos Sakkas, N. Giannakeas, E. Glavas, A. Tzallas

{"title":"An experimental protocol for exploration of stress in an immersive VR scenario with EEG","authors":"Andreas Miltiadous, Vasileios Aspiotis, Konstantinos Sakkas, N. Giannakeas, E. Glavas, A. Tzallas","doi":"10.1109/SEEDA-CECNSM57760.2022.9932987","DOIUrl":"https://doi.org/10.1109/SEEDA-CECNSM57760.2022.9932987","url":null,"abstract":"Stress is a subject always relevant to scientific research due to the numerous implications in human life. Typical biomarkers used in the physiological evaluation of stress include Electrocardiography, cortisol levels, galvanic skin response and other. Recently, one less widely used instrument for the assessment of stress that has been re-emerged due to advancements in computational power and machine learning techniques, is Electroencephalography. Moreover, as Virtual Reality HMDs are being rapidly adopted by the research community it becomes apparent that leveraging the offered advantages of VR for the exploration of stress can lead to novel controlable and reproducable experimental procedures. In this paper we combine EEG, ECG and the Perceived Stress Scale with a Virtual Reality phobia induction setting, to propose a protocol for assessing stress. The suggested protocol can be used for functional brain connectivity investigation and thus the evaluation of stress while it and can be expanded via the incorporation of machine learning algorithms for automatic stress level classification.","PeriodicalId":68279,"journal":{"name":"计算机工程与设计","volume":"49 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2022-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86464586","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

Brain MRI based diagnosis of autoimmune diseases using deep learning 基于脑MRI的自身免疫性疾病深度学习诊断

计算机工程与设计 Pub Date : 2022-09-23 DOI: 10.1109/SEEDA-CECNSM57760.2022.9932959

D. Amanatidis, Georgios Chatzisavvas, Michael F. Dossis

引用次数: 0

Distributed Gibbs Sampling and LDA Modelling for Large Scale Big Data Management on PySpark 基于PySpark的大规模大数据管理的分布式Gibbs采样和LDA建模

计算机工程与设计 Pub Date : 2022-09-23 DOI: 10.1109/SEEDA-CECNSM57760.2022.9932990

Christos N. Karras, Aristeidis Karras, D. Tsolis, K. Giotopoulos, S. Sioutas

{"title":"Distributed Gibbs Sampling and LDA Modelling for Large Scale Big Data Management on PySpark","authors":"Christos N. Karras, Aristeidis Karras, D. Tsolis, K. Giotopoulos, S. Sioutas","doi":"10.1109/SEEDA-CECNSM57760.2022.9932990","DOIUrl":"https://doi.org/10.1109/SEEDA-CECNSM57760.2022.9932990","url":null,"abstract":"Big data management methods are paramount in the modern era as applications tend to create massive amounts of data that comes from various sources. Therefore, there is an urge to create adaptive, speedy and robust frameworks that can effectively handle massive datasets. Distributed environments such as Apache Spark are of note, as they can handle such data by creating clusters where a portion of the data is stored locally and then the results are returned with the use of Resilient Distributed Datasets (RDDs). In this paper a method for distributed marginal Gibbs sampling for widely used latent Dirichlet allocation (LDA) model is implemented on PySpark along with a Metropolis Hastings Random Walker. The Distributed LDA (DLDA) algorithm distributes a given dataset into P partitions and performs local LDA on each partition, for each document independently. Every nth iteration, local LDA models, that were trained on distinct partitions, are combined to assure the model ability to converge. Experimental results are promising as the proposed system demonstrates comparable performance in the final model quality to the sequential LDA, and achieves significant speedup time-optimizations when utilized with massive datasets.","PeriodicalId":68279,"journal":{"name":"计算机工程与设计","volume":"119 1","pages":"1-8"},"PeriodicalIF":0.0,"publicationDate":"2022-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88663874","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: 5

Open weather data evaluation for crop irrigation prediction mechanisms in the AUGEIAS project AUGEIAS项目作物灌溉预测机制的开放气象数据评价

计算机工程与设计 Pub Date : 2022-09-23 DOI: 10.1109/SEEDA-CECNSM57760.2022.9932913

Thomai Karamitsou, Dimitrios Seventekidis, Christos Karapiperis, Konstantina Banti, Ioanna Karampelia, Thomas S. Kyriakidis, M. Louta

引用次数: 0

Object Detection for Low Light Images 低光图像的目标检测

计算机工程与设计 Pub Date : 2022-09-23 DOI: 10.1109/SEEDA-CECNSM57760.2022.9932921

Dimitrios Mpouziotas, Eleftherios Mastrapas, Nikos Dimokas, Petros Karvelis, E. Glavas

引用次数: 0