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Developing Teams by Visualizing Their Communication Structures in Online Meetings 通过可视化在线会议中的沟通结构来发展团队
Q2 Computer Science Pub Date : 2023-10-19 DOI: 10.3390/mti7100100
Thomas Spielhofer, Renate Motschnig
This research pursues the question of how the computer-generated analysis and visualization of communication can foster collaboration in teams that work together online. The audio data of regular online video meetings of three different teams were analyzed. Structural information regarding their communication was visualized in a communication report, and then, discussed with the teams in so-called digitally supported coaching (DSC) sessions. The aim of the DSC is to improve team collaboration by discerning helpful and less helpful patterns in the teams’ communication. This report allows us to recognize individual positions within the teams, as well as communication structures, such as conversational turn taking, that are relevant for group intelligence, as other research has shown. The findings pertaining to the team members during the DSC were gathered via questionnaires. These qualitative data were then matched with the quantitative data derived from the calls, particularly social network analysis (SNA). The SNA was inferred using the average number of interactions between the participants as measured in the calls. The qualitative findings of the teams were then cross-checked with the quantitative analysis. As a result, the assessment of team members’ roles was highly coherent with the SNA. Furthermore, all teams managed to derive concrete measures for improving their collaboration based on the reflection in the DSC.
本研究探讨的问题是计算机生成的通信分析和可视化如何促进在线团队的协作。对三个不同团队定期在线视频会议的音频数据进行了分析。关于他们沟通的结构信息在沟通报告中可视化,然后在所谓的数字支持指导(DSC)会议上与团队讨论。DSC的目的是通过识别团队沟通中有用和不太有用的模式来改善团队协作。这个报告让我们认识到团队中的个人位置,以及沟通结构,比如对话的轮流,这与团队智力有关,正如其他研究表明的那样。在DSC期间,有关团队成员的调查结果通过问卷收集。然后将这些定性数据与来自电话的定量数据相匹配,特别是社会网络分析(SNA)。SNA是使用在呼叫中测量的参与者之间的平均交互次数来推断的。然后,这些小组的定性研究结果与定量分析进行了交叉检验。因此,对团队成员作用的评估与国民核算体系高度一致。此外,所有团队都设法根据DSC中的反映得出具体的措施来改善他们的合作。
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引用次数: 0
A Universal Volumetric Haptic Actuation Platform 一种通用体积触觉驱动平台
Q2 Computer Science Pub Date : 2023-10-17 DOI: 10.3390/mti7100099
Patrick Coe, Grigori Evreinov, Mounia Ziat, Roope Raisamo
In this paper, we report a method of implementing a universal volumetric haptic actuation platform which can be adapted to fit a wide variety of visual displays with flat surfaces. This platform aims to enable the simulation of the 3D features of input interfaces. This goal is achieved using four readily available stepper motors in a diagonal cross configuration with which we can quickly change the position of a surface in a manner that can render these volumetric features. In our research, we use a Microsoft Surface Go tablet placed on the haptic enhancement actuation platform to replicate the exploratory features of virtual keyboard keycaps displayed on the touchscreen. We ask seven participants to explore the surface of a virtual keypad comprised of 12 keycaps. As a second task, random key positions are announced one at a time, which the participant is expected to locate. These experiments are used to understand how and with what fidelity the volumetric feedback could improve performance (detection time, track length, and error rate) of detecting the specific keycaps location with haptic feedback and in the absence of visual feedback. Participants complete the tasks with great success (p < 0.05). In addition, their ability to feel convex keycaps is confirmed within the subjective comments.
在本文中,我们报告了一种实现通用体积触觉驱动平台的方法,该平台可以适应各种平面视觉显示。该平台旨在实现输入界面三维特征的仿真。这一目标是使用四个现成的步进电机在对角线交叉配置,我们可以快速改变一个表面的位置,以一种方式,可以渲染这些体积特征。在我们的研究中,我们使用放置在触觉增强驱动平台上的Microsoft Surface Go平板电脑来复制触摸屏上显示的虚拟键盘键帽的探索功能。我们要求7名参与者探索由12个键帽组成的虚拟键盘的表面。作为第二个任务,随机的关键位置一次宣布一个,参与者需要找到。这些实验被用来理解在没有视觉反馈和触觉反馈的情况下,体积反馈如何以及以何种保真度提高检测特定键帽位置的性能(检测时间、轨迹长度和错误率)。参与者非常成功地完成了任务(p <0.05)。此外,他们感觉凸键帽的能力在主观评论中得到了证实。
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引用次数: 0
Immersive Unit Visualization with Augmented Reality 沉浸式单元可视化与增强现实
Q2 Computer Science Pub Date : 2023-10-17 DOI: 10.3390/mti7100098
Ana Beatriz Marques, Vasco Branco, Rui Costa, Nina Costa
Immersive Unit Visualization is an emergent form of visualization that arose from Immersive Analytics where, unlike traditional visualizations, each data point is represented by an individual visual mark in an immersive virtual environment. This practice has focused almost exclusively on virtual reality, excluding augmented reality (AR). This article develops and tests a prototype of an Immersive Unit Visualization (Floating Companies II) with two AR devices: head-mounted display (HMD) and hand-held display (HHD). Results from the testing sessions with 20 users were analyzed through qualitative research analysis and thematic coding indicating that, while the HHD enabled a first contact with AR visualization on a familiar device, HMD improved the perception of hybrid space by supporting greater stability of virtual content, wider field of view, improved spatial perception, increased sense of immersion, and more realistic simulation, which had an impact on information reading and sense-making. The materialization of abstract quantitative values into concrete reality through its simulation in the real environment and the ludic dimension stand out as important opportunities for this type of visualization. This paper investigates the aspects distinguishing two experiences regarding data visualization in hybrid space, and characterizes ways of seeing information with AR, identifying opportunities to advance information design research.
沉浸式单元可视化是一种新兴的可视化形式,起源于沉浸式分析,与传统的可视化不同,每个数据点都由沉浸式虚拟环境中的单个视觉标记表示。这种做法几乎只关注虚拟现实,不包括增强现实(AR)。本文使用头戴式显示器(HMD)和手持显示器(HHD)两种AR设备开发并测试了沉浸式单元可视化(Floating Companies II)的原型。通过定性研究分析和专题编码,对20名用户的测试结果进行了分析,结果表明,HHD使用户在熟悉的设备上首次接触AR可视化,而HMD通过支持更大的虚拟内容稳定性、更广阔的视野、改善的空间感知、增强的沉浸感和更逼真的模拟来改善混合空间的感知,从而对信息阅读和意义构建产生影响。通过在真实环境中的模拟,将抽象的定量值物质化为具体的现实,以及滑稽的维度是这种可视化的重要机会。本文研究了在混合空间中区分数据可视化的两种经验的方面,并描述了使用AR查看信息的方式,确定了推进信息设计研究的机会。
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引用次数: 0
Evolution and Trends in Sign Language Avatar Systems: Unveiling a 40-Year Journey via Systematic Review 手语化身系统的演变和趋势:通过系统回顾揭示40年的历程
Q2 Computer Science Pub Date : 2023-10-16 DOI: 10.3390/mti7100097
Maryam Aziz, Achraf Othman
Sign language (SL) avatar systems aid communication between the hearing and deaf communities. Despite technological progress, there is a lack of a standardized avatar development framework. This paper offers a systematic review of SL avatar systems spanning from 1982 to 2022. Using PRISMA guidelines, we shortlisted 47 papers from an initial 1765, focusing on sign synthesis techniques, corpora, design strategies, and facial expression methods. We also discuss both objective and subjective evaluation methodologies. Our findings highlight key trends and suggest new research avenues for improving SL avatars.
手语(SL)化身系统有助于听力社区和聋人社区之间的交流。尽管技术进步了,但仍缺乏标准化的角色开发框架。本文对1982年至2022年的SL化身系统进行了系统回顾。使用PRISMA指南,我们从最初的1765篇论文中选出了47篇论文,重点关注符号合成技术、语料库、设计策略和面部表情方法。我们还讨论了客观和主观的评价方法。我们的研究结果突出了主要趋势,并提出了改进SL虚拟形象的新研究途径。
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引用次数: 0
Metaverse and Extended Realities in Immersive Journalism: A Systematic Literature Review 沉浸式新闻中的虚拟世界和扩展现实:系统的文献综述
Q2 Computer Science Pub Date : 2023-10-12 DOI: 10.3390/mti7100096
Alberto Sanchez-Acedo, Alejandro Carbonell-Alcocer, Manuel Gertrudix, Jose Luis Rubio-Tamayo
Immersive journalism is a new form of media communication that uses extended reality systems to produce its content. Despite the possibilities it offers, its use is still limited in the media due to the lack of systematised and scientific knowledge regarding its application. This is a problem because it is a very powerful technology that changes the way audiences receive information and can be used both for new forms of storytelling that generate greater user engagement and for very sophisticated disinformation, which is why it is really important to study it. This study analyses articles published in the last 5 years that cover the use of extended technologies and the metaverse applied to immersive journalism. A systematic literature review applying PRISMA was carried out to identify literature within Web of Science, Scopus and Google Scholar (n = 61). Quantitative and qualitative analyses were conducted on the data collection techniques, the type of the data and the analysis techniques used. The results show a low level of methodological maturity, with research that is fundamentally descriptive and not very formalised, which limits the scope of its results and, therefore, the transfer of knowledge for its application in the configuration of new immersive journalistic products. The metaverse and extended technologies are considered independently and with distinct applications. It is concluded that research in this area is still in an initial exploratory and generalist stage that offers results that are not yet applicable to the promotion of this type of media format.
沉浸式新闻是一种新的媒体传播形式,它使用扩展现实系统来生产其内容。尽管它提供了可能性,但由于缺乏关于其应用的系统和科学知识,它在媒体中的使用仍然有限。这是一个问题,因为它是一种非常强大的技术,它改变了观众接受信息的方式,既可以用于新形式的讲故事,产生更大的用户参与度,也可以用于非常复杂的虚假信息,这就是为什么研究它真的很重要。本研究分析了过去5年发表的文章,这些文章涵盖了扩展技术和虚拟世界在沉浸式新闻中的应用。应用PRISMA进行系统文献综述,在Web of Science、Scopus和Google Scholar中识别文献(n = 61)。对数据收集技术、数据类型和使用的分析技术进行了定量和定性分析。结果显示,方法成熟度较低,研究基本上是描述性的,不是很形式化,这限制了其结果的范围,因此,在新的沉浸式新闻产品配置中应用知识的转移。元技术和扩展技术被视为独立的,具有不同的应用程序。结论是,该领域的研究仍处于初步探索和通才阶段,其结果尚不适用于推广这种类型的媒体格式。
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引用次数: 0
Current Trends, Challenges, and Future Research Directions of Hybrid and Deep Learning Techniques for Motor Imagery Brain–Computer Interface 运动图像脑机接口混合深度学习技术的发展趋势、挑战及未来研究方向
Q2 Computer Science Pub Date : 2023-10-12 DOI: 10.3390/mti7100095
Emmanouil Lionakis, Konstantinos Karampidis, Giorgos Papadourakis
The field of brain–computer interface (BCI) enables us to establish a pathway between the human brain and computers, with applications in the medical and nonmedical field. Brain computer interfaces can have a significant impact on the way humans interact with machines. In recent years, the surge in computational power has enabled deep learning algorithms to act as a robust avenue for leveraging BCIs. This paper provides an up-to-date review of deep and hybrid deep learning techniques utilized in the field of BCI through motor imagery. It delves into the adoption of deep learning techniques, including convolutional neural networks (CNNs), autoencoders (AEs), and recurrent structures such as long short-term memory (LSTM) networks. Moreover, hybrid approaches, such as combining CNNs with LSTMs or AEs and other techniques, are reviewed for their potential to enhance classification performance. Finally, we address challenges within motor imagery BCIs and highlight further research directions in this emerging field.
脑机接口(brain - computer interface, BCI)使我们能够在人脑和计算机之间建立一条通路,在医疗和非医疗领域都有应用。脑机接口可以对人类与机器交互的方式产生重大影响。近年来,计算能力的激增使深度学习算法成为利用脑机接口的强大途径。本文提供了通过运动意象在脑机接口领域中使用的深度和混合深度学习技术的最新综述。它深入研究了深度学习技术的采用,包括卷积神经网络(cnn)、自动编码器(ae)和循环结构,如长短期记忆(LSTM)网络。此外,混合方法,如将cnn与lstm或ae等技术相结合,对其提高分类性能的潜力进行了综述。最后,我们讨论了运动图像脑机接口面临的挑战,并强调了这一新兴领域的进一步研究方向。
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引用次数: 0
Safe City: A Study of Channels for Public Warnings for Emergency Communication in Finland, Germany, and Greece 平安城市:芬兰、德国和希腊公共预警应急通信渠道研究
Q2 Computer Science Pub Date : 2023-10-10 DOI: 10.3390/mti7100094
Sari Yli-Kauhaluoma, Milt Statheropoulos, Anne Zygmanowski, Osmo Anttalainen, Hanna Hakulinen, Maria Theodora Kontogianni, Matti Kuula, Johannes Pernaa, Paula Vanninen
Public warning systems are an essential element of safe cities. However, the functionality of neither traditional nor digital emergency warnings is understood well enough from the perspective of citizens. This study examines smart city development from the perspective of safety by exploring citizens’ viewpoints. It investigates people’s perceptions of the ways in which they obtain warnings and information about emergencies involving health risks. Data were collected in the form of focus group interviews and semi-structured interviews in Finland, Germany, and Greece. The results suggest that people place a lot of trust in their social network, receiving text messages, and their ability to use web-based search engines in order to obtain public warnings. The study discusses the challenges identified by citizens in the use of conventional radio and television transmissions and sirens for public warnings. Based on the results, citizens demonstrate informed ignorance about existing mobile emergency applications. Our results imply that it is not sufficient to build emergency communication infrastructure: the development of smart, safe cities requires continuous work and the integration of both hard and soft infrastructure-oriented strategies, i.e., technological infrastructure development including digitalisation and education, advancement of knowledge, and participation of people. Both strategic aspects are essential to enable people to take advantage of novel digital applications in emergency situations.
公共预警系统是安全城市的重要组成部分。然而,从公民的角度来看,传统和数字紧急警报的功能都没有得到足够的理解。本研究通过探索市民的观点,从安全的角度审视智慧城市的发展。它调查了人们对获取涉及健康风险的紧急情况的警告和信息的方式的看法。在芬兰、德国和希腊以焦点小组访谈和半结构化访谈的形式收集数据。研究结果表明,人们对自己的社交网络、接收短信以及使用基于网络的搜索引擎获取公共警告的能力非常信任。该研究讨论了公民在使用传统广播和电视传输以及公共警报警报器时所发现的挑战。根据结果,公民对现有的移动应急应用程序表现出知情无知。我们的研究结果表明,仅仅建设应急通信基础设施是不够的:智慧、安全城市的发展需要持续的工作和软硬基础设施战略的整合,即包括数字化和教育在内的技术基础设施发展、知识进步和人们的参与。这两个战略方面对于使人们能够在紧急情况下利用新的数字应用至关重要。
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引用次数: 0
Identifying Which Relational Cues Users Find Helpful to Allow Tailoring of e-Coach Dialogues 确定用户发现哪些关系线索有助于定制电子教练对话
Q2 Computer Science Pub Date : 2023-10-02 DOI: 10.3390/mti7100093
Sana Salman, Deborah Richards, Mark Dras
Relational cues are extracts from actual verbal dialogues that help build the therapist–patient working alliance and stronger bond through the depiction of empathy, respect and openness. ECAs (Embodied conversational agents) are human-like virtual agents that exhibit verbal and non-verbal behaviours. In the digital health space, ECAs act as health coaches or experts. ECA dialogues have previously been designed to include relational cues to motivate patients to change their current behaviours and encourage adherence to a treatment plan. However, there is little understanding of who finds specific relational cues delivered by an ECA helpful or not. Drawing the literature together, we have categorised relational cues into empowering, working alliance, affirmative and social dialogue. In this study, we have embedded the dialogue of Alex, an ECA, to encourage healthy behaviours with all the relational cues (empathic Alex) or with none of the relational cues (neutral Alex). A total of 206 participants were randomly assigned to interact with either empathic or neutral Alex and were also asked to rate the helpfulness of selected relational cues. We explore if the perceived helpfulness of the relational cues is a good predictor of users’ intention to change the recommended health behaviours and/or development of a working alliance. Our models also investigate the impact of individual factors, including gender, age, culture and personality traits of the users. The idea is to establish whether a certain group of individuals having similarities in terms of individual factors found a particular cue or group of cues helpful. This will establish future versions of Alex and allow Alex to tailor its dialogue to specific groups, as well as help in building ECAs with multiple personalities and roles.
关系线索是从实际的口头对话中提取出来的,通过对移情、尊重和开放的描述,有助于建立治疗师与患者的工作联盟和更强的联系。eca(具体化会话代理)是一种具有语言和非语言行为的类人虚拟代理。在数字健康领域,eca扮演着健康教练或专家的角色。ECA对话以前被设计为包括关系提示,以激励患者改变他们目前的行为并鼓励遵守治疗计划。然而,对于谁认为ECA提供的特定关系线索有帮助或没有帮助,人们知之甚少。结合文献,我们将关系线索分为授权、工作联盟、肯定和社会对话。在本研究中,我们嵌入了ECA Alex的对话,以鼓励具有所有关系线索(共情Alex)或没有任何关系线索(中立Alex)的健康行为。共有206名参与者被随机分配到与移情或中立的亚历克斯互动,并被要求对选定的关系线索的帮助程度进行评分。我们探讨如果感知的有用性的关系线索是一个很好的预测器用户的意图改变建议的健康行为和/或发展的工作联盟。我们的模型还研究了个体因素的影响,包括用户的性别、年龄、文化和人格特征。这个想法是为了确定一组在个体因素方面具有相似性的个体是否会发现一个或一组线索有帮助。这将建立Alex的未来版本,并允许Alex为特定的群体定制对话,以及帮助构建具有多重个性和角色的eca。
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引用次数: 0
A New Technological Model on Investigating the Utilization of Mobile Learning Applications: Extending the TAM 研究移动学习应用程序使用的新技术模型:TAM的扩展
Q2 Computer Science Pub Date : 2023-09-20 DOI: 10.3390/mti7090092
Rima Shishakly, Mohammed Amin Almaiah, Shaha Al-Otaibi, Abdalwali Lutfi, Mahmaod Alrawad, Ahmed Almulhem
Mobile learning has become increasingly important for higher education due to its numerous advantages and transformative potential. The aim of this study is to investigate how students perceive and utilize mobile learning (m-learning) services in universities. To achieve this objective, a conceptual model was developed, combining the TAM with additional new determinants, including perceived security, perceived trust, perceived risk, and service quality. The primary goal of this model is to assess the adoption of m-learning apps among users in university settings. To evaluate the proposed model, SEM was utilized to test the research model. The findings of the study highlight the critical roles of perceived security, perceived trust, and service quality in promoting the adoption of m-learning apps. Moreover, the results indicate that perceived risk negatively impacts both students’ trust and their attitudes towards using mobile learning services. The study reveals that the perceived trust, and service quality factors positively influence students’ attitudes towards adopting m-learning apps. These research findings hold significant implications for universities and academia, offering valuable insights to devise effective strategies for increasing the utilization of m- learning services among students. By gaining a deeper understanding of students’ perceptions and acceptance, universities can optimize their m-learning offerings to cater to students’ needs and preferences more effectively.
由于其众多优势和变革潜力,移动学习对高等教育变得越来越重要。本研究的目的是调查学生如何感知和利用大学中的移动学习(m-learning)服务。为了实现这一目标,开发了一个概念模型,将TAM与其他新决定因素结合起来,包括感知安全、感知信任、感知风险和服务质量。该模型的主要目标是评估大学用户对移动学习应用程序的采用情况。为了评价所提出的模型,利用扫描电镜对研究模型进行了检验。研究结果强调了感知安全、感知信任和服务质量在促进移动学习应用程序采用方面的关键作用。此外,研究结果表明,感知风险对学生的信任和使用移动学习服务的态度都有负向影响。研究发现,感知信任和服务质量因素正向影响学生采用移动学习应用程序的态度。这些研究结果对大学和学术界具有重要意义,为制定有效的策略以提高学生对移动学习服务的利用提供了有价值的见解。通过更深入地了解学生的看法和接受程度,大学可以优化他们的移动学习产品,更有效地满足学生的需求和偏好。
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引用次数: 0
Semantic Interest Modeling and Content-Based Scientific Publication Recommendation Using Word Embeddings and Sentence Encoders 基于词嵌入和句子编码器的语义兴趣建模和基于内容的科学出版物推荐
Q2 Computer Science Pub Date : 2023-09-15 DOI: 10.3390/mti7090091
Mouadh Guesmi, Mohamed Amine Chatti, Lamees Kadhim, Shoeb Joarder, Qurat Ul Ain
The fast growth of data in the academic field has contributed to making recommendation systems for scientific papers more popular. Content-based filtering (CBF), a pivotal technique in recommender systems (RS), holds particular significance in the realm of scientific publication recommendations. In a content-based scientific publication RS, recommendations are composed by observing the features of users and papers. Content-based recommendation encompasses three primary steps, namely, item representation, user modeling, and recommendation generation. A crucial part of generating recommendations is the user modeling process. Nevertheless, this step is often neglected in existing content-based scientific publication RS. Moreover, most existing approaches do not capture the semantics of user models and papers. To address these limitations, in this paper we present a transparent Recommendation and Interest Modeling Application (RIMA), a content-based scientific publication RS that implicitly derives user interest models from their authored papers. To address the semantic issues, RIMA combines word embedding-based keyphrase extraction techniques with knowledge bases to generate semantically-enriched user interest models, and additionally leverages pretrained transformer sentence encoders to represent user models and papers and compute their similarities. The effectiveness of our approach was assessed through an offline evaluation by conducting extensive experiments on various datasets along with user study (N = 22), demonstrating that (a) combining SIFRank and SqueezeBERT as an embedding-based keyphrase extraction method with DBpedia as a knowledge base improved the quality of the user interest modeling step, and (b) using the msmarco-distilbert-base-tas-b sentence transformer model achieved better results in the recommendation generation step.
学术领域数据的快速增长使得科学论文推荐系统更加普及。基于内容的过滤(CBF)是推荐系统(RS)中的一项关键技术,在科学出版物推荐领域具有特殊的意义。在基于内容的科学出版物RS中,通过观察用户和论文的特征来组成推荐。基于内容的推荐包括三个主要步骤,即项目表示、用户建模和推荐生成。生成推荐的一个关键部分是用户建模过程。然而,在现有的基于内容的科学出版物RS中,这一步经常被忽略。此外,大多数现有方法都没有捕获用户模型和论文的语义。为了解决这些限制,在本文中,我们提出了一个透明的推荐和兴趣建模应用程序(RIMA),这是一个基于内容的科学出版物RS,它隐含地从用户撰写的论文中派生用户兴趣模型。为了解决语义问题,RIMA将基于词嵌入的关键短语提取技术与知识库相结合,生成语义丰富的用户兴趣模型,并利用预训练的转换句子编码器来表示用户模型和论文并计算它们的相似性。通过在各种数据集上进行大量实验和用户研究(N = 22)进行离线评估,评估了我们方法的有效性,结果表明(a)结合SIFRank和SqueezeBERT作为基于嵌入的关键词提取方法,以DBpedia为知识库,提高了用户兴趣建模步骤的质量,(b)使用msmarco-distilbert-base- as-b句子转换器模型在推荐生成步骤中取得了更好的效果。
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引用次数: 0
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Multimodal Technologies and Interaction
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