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A Methodology for Stock Movement Prediction Using Sentiment Analysis on Twitter and StockTwits Data 基于Twitter和StockTwits数据的情绪分析的股票走势预测方法
Pub Date : 2021-09-24 DOI: 10.1109/SEEDA-CECNSM53056.2021.9566242
Christina Nousi, Christos Tjortjis
Application of Machine Learning (ML) and sentiment analysis on data from microblogging services has become a common approach for stock market prediction. In this paper, we propose a methodology using sentiment analysis on Twitter and StockTwits data for Stock movement prediction. The methodology was evaluated by analyzing stock movement and sentiment data. We present a case study focusing on Microsoft stock. We collected tweets from Twitter and StockTwits along with financial data extracted from Finance Yahoo. Sentiment analysis was applied on tweets, and two ML models namely SVM and Logistic Regression were implemented. Best results were achieved when using tweets from Twitter with VADER and SVM. Top F-score was 76.3% and top Area Under Curve (AUC) was 67%. SVM also achieves the greatest accuracy equal to 65.8%, when using StockTwits with TextBlob on this imbalanced data set.
机器学习和情感分析在微博服务数据上的应用已经成为股市预测的常用方法。在本文中,我们提出了一种使用Twitter和StockTwits数据的情绪分析来预测股票走势的方法。该方法是通过分析股票走势和情绪数据来评估的。我们提出了一个以微软股票为重点的案例研究。我们收集了Twitter和StockTwits上的推文,以及财经雅虎(Finance Yahoo)上的财务数据。对推文进行情感分析,实现了SVM和Logistic回归两种机器学习模型。将Twitter上的tweet与VADER和SVM结合使用,效果最好。最高f值为76.3%,最高曲线下面积(AUC)为67%。在此不平衡数据集上使用StockTwits和TextBlob时,SVM也达到了最高的准确率,达到65.8%。
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引用次数: 6
Exploring the role of educational neuroscience in learning through the perspectives of adult vocational education students of computer science in the field of online learning. A case study 通过成人职业教育计算机科学专业学生在在线学习领域的视角,探索教育神经科学在学习中的作用。案例研究
Pub Date : 2021-09-24 DOI: 10.1109/SEEDA-CECNSM53056.2021.9566229
E. Malliou, Spyridon Doukakis, Sarah Vlachou, Evangelia Filippakopoulou
Online learning had a decisive role in all levels of education during the pandemic. In this study, we will explore adult vocational education students of computer science that experienced the online education during the school academic year 2020–2021. The study attempts to explore the views of 10 adult students. At the same time, an attempt is made to determine the role of educational neuroscience in students' learning. Participants were asked to answer 14 questions about the online education they had experienced. This was followed by data analysis using NVivo software. According to the findings, 6 students identified the reasons why they prefer to be educated in a physical learning environment and 1 student stated that he prefers a mixed model that will include lessons with both physical and online presence. In addition, 9 out of 10 students stated that they prefer synchronous online teaching to asynchronous. Also, 7 out of 10 students identified that in the theoretical part they were able to achieve the expected learning outcomes but on the other hand, 6 out of 10 learners reported difficulties in attending the workshops. Nevertheless, 8 out of 10 stated that they were quite consistent with the obligations they had during the course. The findings indicate that the principles of educational neuroscience can be a critical component of effective online learning.
在大流行期间,在线学习在各级教育中发挥了决定性作用。在本研究中,我们将探讨在2020-2021学年经历在线教育的计算机科学成人职业教育学生。本研究试图探讨10名成年学生的观点。同时,试图确定教育神经科学在学生学习中的作用。参与者被要求回答14个关于他们所经历的在线教育的问题。随后使用NVivo软件进行数据分析。根据调查结果,6名学生确定了他们喜欢在实体学习环境中接受教育的原因,1名学生表示他更喜欢混合模式,包括实体和在线教学。此外,90%的学生表示他们更喜欢同步在线教学而不是异步在线教学。此外,10个学生中有7个认为在理论部分他们能够达到预期的学习成果,但另一方面,10个学习者中有6个报告参加研讨会有困难。然而,10个人中有8个人说,他们完全符合他们在课程期间所承担的义务。研究结果表明,教育神经科学的原理可以成为有效在线学习的关键组成部分。
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引用次数: 0
DataPAL: Data Protection and Authorization Lifecycle framework DataPAL:数据保护和授权生命周期框架
Pub Date : 2021-09-24 DOI: 10.1109/SEEDA-CECNSM53056.2021.9566212
S. Bandopadhyay, T. Dimitrakos, Yair Diaz, Alicia Y Hariri, Tezcan Dilshener, Antonio La Marra, A. Rosetti
This paper introduces a new model for handling data privacy throughout data lifecycle via the introduction of a policy profile using the Abbreviated Language For Authorization (ALFA) policy language. Our approach extends previous models In three complementary ways: (1) By introducing Administration and Delegation Profile (ADP) in ALFA policy where users and companies can restrict the scope of access/usage policies related to data as well as specify a chain of custody for data (moreover such an approach eases up the tasks of handling users' consent); (2) Thanks to our framework Usage Control System Plus (UCS+) users can monitor the usage of data and revoke its usage upon specific conditions or at will; (3) By introducing new states for policy evaluation, i.e. Admissible/NotAdmissible to filter out those applicable policies that were unauthorized in the first place.
本文通过引入使用缩写授权语言(缩写Language for Authorization, ALFA)策略语言的策略概要,介绍了一个在整个数据生命周期中处理数据隐私的新模型。我们的方法以三种互补的方式扩展了以前的模型:(1)通过在ALFA政策中引入管理和授权配置文件(ADP),用户和公司可以限制与数据相关的访问/使用政策的范围,并指定数据的监管链(此外,这种方法简化了处理用户同意的任务);(2)由于我们的框架使用控制系统Plus (UCS+),用户可以监控数据的使用情况,并在特定情况下或随意撤销其使用;(3)通过引入新的状态进行策略评估,即adeable / notadeable,过滤掉那些一开始就未经授权的适用策略。
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引用次数: 1
Rapid Blockchain Scaling with Efficient Transaction Assignment 快速区块链扩展与高效交易分配
Pub Date : 2021-09-24 DOI: 10.1109/SEEDA-CECNSM53056.2021.9566222
Panagiotis Drakatos, Eleni Koutrouli, A. Tsalgatidou
The abrupt development of cryptocurrencies and blockchain technology has pointed to the importance of deploying large scale, highly robust Byzantine fault-tolerant schemes to handle critical distributed failures in system networks. Although traditional wisdom is to build systems by following synchronous protocols such as PBFT consensus, these protocols strongly rely on network time limitations and only guarantee liveness when the nodes behave arbitrary. This paper presents the design and implementation of Adrastus, a scalable blockchain system. The main contributions of Adrastus are the use of a consistent hashing mechanism which solves load balancing problems and the efficient assignment of transactions on parallel regions of single-chain consensus systems, referred to as zones, without introducing unnecessary overhead. We claim that the Adrastus blockchain system scales linearly without compromising system security. We present theoretical analysis, discuss our solution, and examine the conditions to meet both safety and liveness of our fault-tolerant system.
加密货币和区块链技术的突然发展表明,部署大规模、高度健壮的拜占庭式容错方案来处理系统网络中的关键分布式故障非常重要。虽然传统智慧是通过遵循PBFT共识等同步协议来构建系统,但这些协议强烈依赖于网络时间限制,并且仅在节点行为任意时保证活动。本文介绍了一个可扩展的区块链系统Adrastus的设计和实现。Adrastus的主要贡献是使用一致的哈希机制,该机制解决了负载平衡问题,并在单链共识系统的并行区域(称为区域)上有效分配事务,而不会引入不必要的开销。我们声称Adrastus区块链系统在不影响系统安全性的情况下线性扩展。我们提出了理论分析,讨论了我们的解决方案,并检查了同时满足我们的容错系统的安全性和活跃性的条件。
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引用次数: 2
A Smart Assistant Nightstand For Hospitals 医院智能助手床头柜
Pub Date : 2021-09-24 DOI: 10.1109/SEEDA-CECNSM53056.2021.9566220
M. Kalafati, A. Kakarountas
The exponential growth of the number and variety of monitoring devices for patients in the hospital, as well as the improvement of medical equipment and hygiene conditions constitute the core of eHealth projects nowadays. In this study, an assistant, smart nightstand near patient's bed and a novel platform are presented, which have the ability to take vital signs in time via sensors which are connected with the patient and simultaneously the data are sent in the central nursing station. The platform has also an interactive role with patients as it will also contribute to their entertainment. Also, the sterilization of objects with UV lamps has been widely introduced in our daily life, mainly due to Covid-19 and other viruses and bacteria that exist in hospitals and patients are at risk of infection. Thus, we have constructed in our nightstand a disinfection area for the patient's personal hygiene items. Last but not least, we have introduced a construction of drug dispenser which will alert the patient to the drop of his medication.
医院患者监测设备数量和种类的指数级增长,以及医疗设备和卫生条件的改善构成了当今电子健康项目的核心。本研究提出了一种助手、病人床边的智能床头柜和一种新颖的平台,通过与病人连接的传感器及时采集病人的生命体征,同时将数据发送到中央护理站。该平台还与患者互动,因为它也将有助于他们的娱乐。此外,在我们的日常生活中也广泛引入了紫外线灯对物体的消毒,主要是因为医院和患者存在Covid-19等病毒和细菌感染的风险。因此,我们在床头柜里建了一个消毒区,用来存放病人的个人卫生用品。最后但并非最不重要的是,我们介绍了一种药物分配器的结构,它将提醒病人他的药物滴下。
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引用次数: 1
Virtual Reality Escape Rooms for STEM Education in Industry 4.0: Greek Teachers Perspectives 工业4.0中STEM教育的虚拟现实逃生室:希腊教师的观点
Pub Date : 2021-09-24 DOI: 10.1109/SEEDA-CECNSM53056.2021.9566265
S. Mystakidis, George Papantzikos, C. Stylios
Science, Technology, Engineering and Mathematics (STEM) skills comprise a crucial meta-discipline for success in the 21st century. Education in the industry 4.0 era can be enhanced by adopting Virtual (VR), Mixed (MR), and Augmented (AR). VR can support creative student-centered teaching and learning methods in STEM, such as playful learning, gameful learning (gamification), and serious games. Serious escape rooms are digital interactive, live adventure breakout games with a pedagogical rationale. This paper examines the perceptions of K-12 school education teachers towards digital educational escape rooms for STEM education in VR environments. Twenty-eight Greek teachers responded to a questionnaire after having experienced a cost-effective science-themed digital escape room. Results indicate that teachers reacted positively to the VR escape room, appreciating its value for learning. Moreover, they are eager to engage in professional development activities and embrace gameful learning methods.
科学、技术、工程和数学(STEM)技能构成了21世纪成功的关键元学科。工业4.0时代的教育可以通过采用虚拟(VR)、混合(MR)和增强(AR)来增强。VR可以在STEM中支持创造性的以学生为中心的教学方法,如好玩的学习、游戏化的学习和严肃的游戏。严肃的密室逃生游戏是一款基于教学原理的数字化互动实时冒险游戏。本文研究了K-12学校教育教师对VR环境中STEM教育的数字教育逃生室的看法。28名希腊教师在体验了一间经济实惠的科学主题数字密室后,对一份问卷进行了回答。结果表明,教师对虚拟现实逃生室的反应是积极的,他们欣赏虚拟现实逃生室的学习价值。此外,他们渴望参与专业发展活动,并接受游戏式的学习方法。
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引用次数: 12
Investigating Parody from Social Media Accounts 调查社交媒体账户中的恶搞行为
Pub Date : 2021-09-24 DOI: 10.1109/SEEDA-CECNSM53056.2021.9566233
Muhammad Abu Talha, Adeel Zafar
Parody is a widespread comic on different social media platforms. As the usage of social media increases, the number of parody accounts increases as well. The main purpose of parody accounts is to spread fake news or to criticize someone in comic ways. In this paper, we investigate parody for different social media accounts. For this study, a customized tweets dataset is created related to different Pakistani personalities and companies. The experiment is carried out using different machine learning and deep learning methods. Our results indicate an accuracy of 92% using RoBERTa.
恶搞是一种在不同社交媒体平台上流行的漫画。随着社交媒体的使用增加,恶搞账号也在增加。恶搞账号的主要目的是传播假新闻或以滑稽的方式批评某人。在本文中,我们研究了不同的社交媒体帐户恶搞。在这项研究中,创建了一个与不同巴基斯坦人物和公司相关的定制推文数据集。实验使用不同的机器学习和深度学习方法进行。我们的结果表明,使用RoBERTa的准确率为92%。
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引用次数: 1
Neural Network-Based approach for Hemiplegia Detection via Accelerometer Signals 基于加速度计信号的偏瘫检测方法
Pub Date : 2021-09-24 DOI: 10.1109/SEEDA-CECNSM53056.2021.9566216
Vasileios Christou, Alexandros Bantaloukas-Arjmand, D. Dimopoulos, D. Varvarousis, A. Tzallas, Ch Gogos, M. Tsipouras, A. Ploumis, N. Giannakeas
This article introduces a method that can automatically classify the hemiplegia type (right or left side of the body is paralyzed) between healthy and non-healthy subjects. The proposed method utilizes the data taken from the accelerometer sensor of the RehaGait mobile gait analysis system. These data undergo a pre-processing and feature extraction stage before being sent as input to a scaled conjugate gradient backpropagation (SCG-BP) trained neural network. The proposed system is tested using a custom-created dataset containing 10 healthy and 20 patients suffering from hemiplegia (right or left). The experimental part of the system utilized 7 sensors placed on the left and right foot, the left and right shank, the left and right thigh, and the hip of each subject. Each sensor captured a 3-dimensional (3D) signal from 3 different device types: accelerometer, magnetometer, and gyroscope. The system utilized and split into 2-second windows only the accelerometer data, achieving a classification accuracy of 87.71%.
本文介绍了一种能够在健康和非健康受试者之间自动分类偏瘫类型(右侧或左侧身体瘫痪)的方法。该方法利用了RehaGait移动步态分析系统加速度计传感器的数据。这些数据经过预处理和特征提取阶段,然后作为输入发送到缩放共轭梯度反向传播(SCG-BP)训练的神经网络。该系统使用一个定制的数据集进行测试,该数据集包含10名健康患者和20名偏瘫患者(右偏瘫或左偏瘫)。系统的实验部分使用了7个传感器,分别放置在每个受试者的左右脚、左右小腿、左右大腿和臀部。每个传感器捕获3种不同设备类型的三维(3D)信号:加速度计,磁力计和陀螺仪。该系统仅利用加速度计数据并将其分割为2秒窗口,分类准确率达到87.71%。
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引用次数: 1
Using IoT Data-Driven Analysis of Water Consumption to support Design for Sustainable Behaviour during the COVID-19 Pandemic 利用物联网数据驱动的用水量分析,支持2019冠状病毒病大流行期间的可持续行为设计
Pub Date : 2021-09-24 DOI: 10.1109/SEEDA-CECNSM53056.2021.9566237
Marco Zecchini, Alessandra Anna Griesi, I. Chatzigiannakis, I. Mavrommati, Dimitrios Amaxilatis, O. Akrivopoulos
Aquatic environments are cornerstone for the existence of life, while water scarcity and unsafe water supply are major global issues affecting citizens [37]. Recently, the deployment of Internet of Things over water distribution networks has indicated ways to address some of these issues. Yet, policies for sustainable and efficient use of the aquatic resources depend largely on citizen's engagement. The use of data arriving from water metering and water quality sensors in educational environments as a mean to educate citizens and inspire environmental friendly behaviours has not been studied throughly in the past, mainly due to the lack of real-world data. Towards this end, real-world data collected by smart water meters can become a powerful tool to bridge digital and physical environments to support design for sustainable behaviour. A data-driven approach is adopted here that evaluates the effect of human actions related to the consumption of water within an educational setting. The data used in this study is collected from a pilot deployment of a 24 months period and is analyzed on weekly, daily and hourly basis to identify usage patterns. The examined period also includes the restrictions imposed by the local authorities as a response to the COVID-19 emergency taking place during the first quarter of 2020. The evaluation of water consumption before, during and after the lockdown period highlights the impact of human actions within the educational environment. The paper investigates how to design educational activities for sustainable behaviour based on the analysis of the data collected from the smart water grid.
水生环境是生命生存的基石,而水资源短缺和不安全供水是影响公民的重大全球性问题[37]。最近,在配水网络上部署物联网为解决其中一些问题指明了途径。然而,可持续和有效利用水生资源的政策在很大程度上取决于公民的参与。在教育环境中使用来自水计量和水质传感器的数据作为教育公民和激励环境友好行为的手段,过去没有进行过全面的研究,主要是由于缺乏实际数据。为此,智能水表收集的真实世界数据可以成为连接数字和物理环境的强大工具,以支持可持续行为的设计。这里采用了一种数据驱动的方法来评估与教育环境中用水有关的人类行为的影响。本研究使用的数据是从为期24个月的试点部署中收集的,并以每周、每天和每小时为基础进行分析,以确定使用模式。所审查的期间还包括地方当局为应对2020年第一季度发生的COVID-19紧急情况而实施的限制。对封锁之前、期间和之后的用水量进行的评估突出了人类活动对教育环境的影响。本文研究了如何在分析智能水网收集的数据的基础上设计可持续行为的教育活动。
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引用次数: 2
System dynamics modelling to study the impact of digital technologies on regional development 系统动力学建模,研究数字技术对区域发展的影响
Pub Date : 2021-09-24 DOI: 10.1109/SEEDA-CECNSM53056.2021.9566262
Anastasios Andronikidis, E. Samara, Ioannis Bakouros, N. Komninos, Efthymios Katsoras
The use of Smart Technologies in Regional Innovation Systems (RIS) for Regional Development is the main topic of this study. A dynamic model has been created that depicts the contribution of smart technologies to the actors of a Regional Innovation System. In this paper we analyse the first three out of five stages of system dynamics structure approach, namely we start by identifying the problem recognition, we move on to the description of the system and we conclude with the qualitative analysis which demonstrates the causal-loop diagram of the Regional Innovation System.
智能技术在区域创新系统(RIS)中的应用是本研究的主要主题。创建了一个动态模型,描述了智能技术对区域创新系统参与者的贡献。在本文中,我们分析了系统动力学结构方法的五个阶段中的前三个阶段,即我们从识别问题识别开始,我们转向系统描述,我们以定性分析结束,展示了区域创新系统的因果循环图。
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引用次数: 0
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