Informatics

20 pages, 2595 KiB

Open AccessFeature PaperArticle

Computational Thinking and Down Syndrome: An Exploratory Study Using the KIBO Robot

by Carina S. González-González, Erika Herrera-González, Lorenzo Moreno-Ruiz, Nuria Reyes-Alonso, Selene Hernández-Morales, María D. Guzmán-Franco and Alfonso Infante-Moro

Informatics 2019, 6(2), 25; https://doi.org/10.3390/informatics6020025 - 20 Jun 2019

Cited by 37 | Viewed by 8614

Abstract

Computational thinking and coding are key competencies in the 21st century. People with Down syndrome need to be part of this new literacy. For this reason, in this work, we present an exploratory study carried out with students with Down syndrome with cognitive [...] Read more.

Computational thinking and coding are key competencies in the 21st century. People with Down syndrome need to be part of this new literacy. For this reason, in this work, we present an exploratory study carried out with students with Down syndrome with cognitive ages of 3–6 years old using a tangible robot We applied the observational method during the sessions to analyze the participants’ emotional states, engagement, and comprehension of the programming sequences. Results show that people with cognitive disabilities can acquire basic programming and computational skills using tangible robots such as KIBO. Full article

(This article belongs to the Collection Promotion of Computational Thinking and Informatics Education in Pre-University Studies)

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36 pages, 1944 KiB

Open AccessFeature PaperArticle

Improving the Translation Environment for Professional Translators

by Vincent Vandeghinste, Tom Vanallemeersch, Liesbeth Augustinus, Bram Bulté, Frank Van Eynde, Joris Pelemans, Lyan Verwimp, Patrick Wambacq, Geert Heyman, Marie-Francine Moens, Iulianna van der Lek-Ciudin, Frieda Steurs, Ayla Rigouts Terryn, Els Lefever, Arda Tezcan, Lieve Macken, Véronique Hoste, Joke Daems, Joost Buysschaert, Sven Coppers, Jan Van den Bergh and Kris Luyten Show full author list Hide full author list

Informatics 2019, 6(2), 24; https://doi.org/10.3390/informatics6020024 - 20 Jun 2019

Cited by 7 | Viewed by 12248

Abstract

When using computer-aided translation systems in a typical, professional translation workflow, there are several stages at which there is room for improvement. The SCATE (Smart Computer-Aided Translation Environment) project investigated several of these aspects, both from a human-computer interaction point of view, as [...] Read more.

When using computer-aided translation systems in a typical, professional translation workflow, there are several stages at which there is room for improvement. The SCATE (Smart Computer-Aided Translation Environment) project investigated several of these aspects, both from a human-computer interaction point of view, as well as from a purely technological side. This paper describes the SCATE research with respect to improved fuzzy matching, parallel treebanks, the integration of translation memories with machine translation, quality estimation, terminology extraction from comparable texts, the use of speech recognition in the translation process, and human computer interaction and interface design for the professional translation environment. For each of these topics, we describe the experiments we performed and the conclusions drawn, providing an overview of the highlights of the entire SCATE project. Full article

(This article belongs to the Special Issue Advances in Computer-Aided Translation Technology)

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16 pages, 1546 KiB

Open AccessArticle

Frame-Based Elicitation of Mid-Air Gestures for a Smart Home Device Ecosystem

by Panagiotis Vogiatzidakis and Panayiotis Koutsabasis

Informatics 2019, 6(2), 23; https://doi.org/10.3390/informatics6020023 - 5 Jun 2019

Cited by 20 | Viewed by 6926

Abstract

If mid-air interaction is to be implemented in smart home environments, then the user would have to exercise in-air gestures to address and manipulate multiple devices. This paper investigates a user-defined gesture vocabulary for basic control of a smart home device ecosystem, consisting [...] Read more.

If mid-air interaction is to be implemented in smart home environments, then the user would have to exercise in-air gestures to address and manipulate multiple devices. This paper investigates a user-defined gesture vocabulary for basic control of a smart home device ecosystem, consisting of 7 devices and a total of 55 referents (commands for device) that can be grouped to 14 commands (that refer to more than one device). The elicitation study was conducted in a frame (general scenario) of use of all devices to support contextual relevance; also, the referents were presented with minimal affordances to minimize widget-specific proposals. In addition to computing agreement rates for all referents, we also computed the internal consistency of user proposals (single-user agreement for multiple commands). In all, 1047 gestures from 18 participants were recorded, analyzed, and paired with think-aloud data. The study reached to a mid-air gesture vocabulary for a smart-device ecosystem, which includes several gestures with very high, high and medium agreement rates. Furthermore, there was high consistency within most of the single-user gesture proposals, which reveals that each user developed and applied her/his own mental model about the whole set of interactions with the device ecosystem. Thus, we suggest that mid-air interaction support for smart homes should not only offer a built-in gesture set but also provide for functions of identification and definition of personalized gesture assignments to basic user commands. Full article

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12 pages, 2024 KiB

Open AccessArticle

Teaching HCI Skills in Higher Education through Game Design: A Study of Students’ Perceptions

by Pedro C. Santana-Mancilla, Miguel A. Rodriguez-Ortiz, Miguel A. Garcia-Ruiz, Laura S. Gaytan-Lugo, Silvia B. Fajardo-Flores and Juan Contreras-Castillo

Informatics 2019, 6(2), 22; https://doi.org/10.3390/informatics6020022 - 14 May 2019

Cited by 16 | Viewed by 9561

Abstract

Human-computer interaction (HCI) is an area with a wide range of concepts and knowledge. Therefore, a need to innovate in the teaching-learning processes to achieve an effective education arises. This article describes a proposal for teaching HCI through the development of projects that [...] Read more.

Human-computer interaction (HCI) is an area with a wide range of concepts and knowledge. Therefore, a need to innovate in the teaching-learning processes to achieve an effective education arises. This article describes a proposal for teaching HCI through the development of projects that allow students to acquire higher education competencies through the design and evaluation of computer games. Finally, an empirical validation (questionnaires and case study) with 40 undergraduate students (studying their fifth semester of software engineering) was applied at the end of the semester. The results indicated that this teaching method provides the students with the HCI skills (psychology of everyday things, involving users, task-centered system design, models of human behavior, creativity and metaphors, and graphical screen design) and, more importantly, they have a positive perception on the efficacy of the use of videogame design in a higher education course. Full article

(This article belongs to the Special Issue Gamification and Advanced Technology to Enhance Motivation in Education)

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14 pages, 1493 KiB

Open AccessArticle

A New Co-Evolution Binary Particle Swarm Optimization with Multiple Inertia Weight Strategy for Feature Selection

by Jingwei Too, Abdul Rahim Abdullah and Norhashimah Mohd Saad

Informatics 2019, 6(2), 21; https://doi.org/10.3390/informatics6020021 - 8 May 2019

Cited by 70 | Viewed by 8454

Abstract

Feature selection is a task of choosing the best combination of potential features that best describes the target concept during a classification process. However, selecting such relevant features becomes a difficult matter when large number of features are involved. Therefore, this study aims [...] Read more.

Feature selection is a task of choosing the best combination of potential features that best describes the target concept during a classification process. However, selecting such relevant features becomes a difficult matter when large number of features are involved. Therefore, this study aims to solve the feature selection problem using binary particle swarm optimization (BPSO). Nevertheless, BPSO has limitations of premature convergence and the setting of inertia weight. Hence, a new co-evolution binary particle swarm optimization with a multiple inertia weight strategy (CBPSO-MIWS) is proposed in this work. The proposed method is validated with ten benchmark datasets from UCI machine learning repository. To examine the effectiveness of proposed method, four recent and popular feature selection methods namely BPSO, genetic algorithm (GA), binary gravitational search algorithm (BGSA) and competitive binary grey wolf optimizer (CBGWO) are used in a performance comparison. Our results show that CBPSO-MIWS can achieve competitive performance in feature selection, which is appropriate for application in engineering, rehabilitation and clinical areas. Full article

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23 pages, 7026 KiB

Open AccessArticle

Conceptualization and Non-Relational Implementation of Ontological and Epistemic Vagueness of Information in Digital Humanities

by Patricia Martin-Rodilla and Cesar Gonzalez-Perez

Informatics 2019, 6(2), 20; https://doi.org/10.3390/informatics6020020 - 6 May 2019

Cited by 17 | Viewed by 7864

Abstract

Research in the digital humanities often involves vague information, either because our objects of study lack clearly defined boundaries, or because our knowledge about them is incomplete or hypothetical, which is especially true in disciplines about our past (such as history, archaeology, and [...] Read more.

Research in the digital humanities often involves vague information, either because our objects of study lack clearly defined boundaries, or because our knowledge about them is incomplete or hypothetical, which is especially true in disciplines about our past (such as history, archaeology, and classical studies). Most techniques used to represent data vagueness emerged from natural sciences, and lack the expressiveness that would be ideal for humanistic contexts. Building on previous work, we present here a conceptual framework based on the ConML modelling language for the expression of information vagueness in digital humanities. In addition, we propose an implementation on non-relational data stores, which are becoming popular within the digital humanities. Having clear implementation guidelines allow us to employ search engines or big data systems (commonly implemented using non-relational approaches) to handle the vague aspects of information. The proposed implementation guidelines have been validated in practice, and show how we can query a vagueness-aware system without a large penalty in analytical and processing power. Full article

(This article belongs to the Collection Uncertainty in Digital Humanities)

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21 pages, 1385 KiB

Open AccessArticle

Improving Semantic Similarity with Cross-Lingual Resources: A Study in Bangla—A Low Resourced Language

by Rajat Pandit, Saptarshi Sengupta, Sudip Kumar Naskar, Niladri Sekhar Dash and Mohini Mohan Sardar

Informatics 2019, 6(2), 19; https://doi.org/10.3390/informatics6020019 - 5 May 2019

Cited by 12 | Viewed by 7169

Abstract

Semantic similarity is a long-standing problem in natural language processing (NLP). It is a topic of great interest as its understanding can provide a look into how human beings comprehend meaning and make associations between words. However, when this problem is looked at [...] Read more.

Semantic similarity is a long-standing problem in natural language processing (NLP). It is a topic of great interest as its understanding can provide a look into how human beings comprehend meaning and make associations between words. However, when this problem is looked at from the viewpoint of machine understanding, particularly for under resourced languages, it poses a different problem altogether. In this paper, semantic similarity is explored in Bangla, a less resourced language. For ameliorating the situation in such languages, the most rudimentary method (path-based) and the latest state-of-the-art method (Word2Vec) for semantic similarity calculation were augmented using cross-lingual resources in English and the results obtained are truly astonishing. In the presented paper, two semantic similarity approaches have been explored in Bangla, namely the path-based and distributional model and their cross-lingual counterparts were synthesized in light of the English WordNet and Corpora. The proposed methods were evaluated on a dataset comprising of 162 Bangla word pairs, which were annotated by five expert raters. The correlation scores obtained between the four metrics and human evaluation scores demonstrate a marked enhancement that the cross-lingual approach brings into the process of semantic similarity calculation for Bangla. Full article

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18 pages, 21322 KiB

Open AccessArticle

The Effects of Motion Artifacts on Self-Avatar Agency

by Alexandros Koilias, Christos Mousas and Christos-Nikolaos Anagnostopoulos

Informatics 2019, 6(2), 18; https://doi.org/10.3390/informatics6020018 - 29 Apr 2019

Cited by 27 | Viewed by 7385

Abstract

One way of achieving self-agency in virtual environments is by using a motion capture system and retargeting user’s motion to the virtual avatar. In this study, we investigated whether the self-agency is affected when motion artifacts appear on top of the baseline motion [...] Read more.

One way of achieving self-agency in virtual environments is by using a motion capture system and retargeting user’s motion to the virtual avatar. In this study, we investigated whether the self-agency is affected when motion artifacts appear on top of the baseline motion capture data assigned to the self-avatar. For this experiment, we implemented four artifacts: noise, latency, motion jump, and offset rotation of joints. The data provided directly from the motion capture system formed the baseline of the study. We developed three observation tasks to assess self-agency: self-observation, observation through a virtual mirror, and observation during locomotion. A questionnaire was adopted and used to capture the self-agency of participants. We analyzed the collected responses of participants to determine whether the motion artifacts significantly altered the participants’ sense of self-agency. The obtained results indicated that participants are not always sensitive to the motion artifacts assigned to the self-avatar, but the sense of self-agency is dependent on the observation task they were asked to perform. Implications for further research are discussed. Full article

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Graphical abstract

Graphical abstract
Full article ">Figure 1
The different self-avatars designed and used in this experiment. Each participant was responsible for choosing the avatar that best represented him/her. The gender of the avatar was based on the gender identification part of the demographics form. Full article ">Figure 2
The virtual environment developed for this experiment. The mirror and the indicators on the ground were switched on or off by the experimenter depending on the task at different stages of the experiment. Full article ">Figure 3
A participant observing his motion retargeted to the self-avatar that embodies him for the three developed tasks during the baseline condition. Full article ">Figure 4
Participants’ responses to questions on body ownership for each of the five conditions of the experiment. Full article ">Figure 5
Participants’ responses to questions on self-agency for each task performed. Full article ">Figure 6
Participants’ responses for the self-agency and impact of the observation task from the conducted experiment. SO, self-observation; MO, observation through a virtual mirror; LO, observation during locomotion. Full article ">

14 pages, 2289 KiB

Open AccessArticle

The Effect of Evidence Transfer on Latent Feature Relevance for Clustering

by Athanasios Davvetas, Iraklis A. Klampanos, Spiros Skiadopoulos and Vangelis Karkaletsis

Informatics 2019, 6(2), 17; https://doi.org/10.3390/informatics6020017 - 25 Apr 2019

Cited by 1 | Viewed by 6226

Abstract

Evidence transfer for clustering is a deep learning method that manipulates the latent representations of an autoencoder according to external categorical evidence with the effect of improving a clustering outcome. Evidence transfer’s application on clustering is designed to be robust when introduced with [...] Read more.

Evidence transfer for clustering is a deep learning method that manipulates the latent representations of an autoencoder according to external categorical evidence with the effect of improving a clustering outcome. Evidence transfer’s application on clustering is designed to be robust when introduced with a low quality of evidence, while increasing the effectiveness of the clustering accuracy during relevant corresponding evidence. We interpret the effects of evidence transfer on the latent representation of an autoencoder by comparing our method to the information bottleneck method. Information bottleneck is an optimisation problem of finding the best tradeoff between maximising the mutual information of data representations and a task outcome while at the same time being effective in compressing the original data source. We posit that the evidence transfer method has essentially the same objective regarding the latent representations produced by an autoencoder. We verify our hypothesis using information theoretic metrics from feature selection in order to perform an empirical analysis over the information that is carried through the bottleneck of the latent space. We use the relevance metric to compare the overall mutual information between the latent representations and the ground truth labels before and after their incremental manipulation, as well as, to study the effects of evidence transfer regarding the significance of each latent feature. Full article

(This article belongs to the Special Issue Feature Selection Meets Deep Learning)

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A comparison of the Relevance metric from feature selection with Unsupervised Accuracy (ACC) and Normalised Mutual Information used for clustering prediction evaluation: We compare both approaches of Relevance (Mutual Information and F-test). To interpret the effects of evidence transfer, we analyse the behaviour of these metrics in five different scenarios. Each subfigure represents a single scenario, and the comparison of the metrics is performed individually on each scenario. For visualisation purposes, we normalise all four metrics using the max norm. We observe similar trends in the behaviour of all these metrics for all predefined experiments and configurations. In subfigure (e), we plot the results of configurations involving three sources of evidence and, hence, the differences in shape compared to the other subfigures. Full article ">Figure 1 Cont.
A comparison of the Relevance metric from feature selection with Unsupervised Accuracy (ACC) and Normalised Mutual Information used for clustering prediction evaluation: We compare both approaches of Relevance (Mutual Information and F-test). To interpret the effects of evidence transfer, we analyse the behaviour of these metrics in five different scenarios. Each subfigure represents a single scenario, and the comparison of the metrics is performed individually on each scenario. For visualisation purposes, we normalise all four metrics using the max norm. We observe similar trends in the behaviour of all these metrics for all predefined experiments and configurations. In subfigure (e), we plot the results of configurations involving three sources of evidence and, hence, the differences in shape compared to the other subfigures. Full article ">Figure 2
A comparison between the Rank Variation and Relevance metric (Mutual Information estimation): For visualisation purposes, we normalise all four metrics using the max norm. Individual latent feature significances in cases of of real corresponding evidence seem to be correlated with the overall relevance measurements. In some cases of low quality evidence, inconsistencies in the behaviour of the ranking variation on the individual latent feature level are observed, which mostly represent swapping rankings between two or four features due to incremental reconstruction training. Full article ">

23 pages, 17081 KiB

Open AccessArticle

RadViz++: Improvements on Radial-Based Visualizations

by Lucas de Carvalho Pagliosa and Alexandru C. Telea

Informatics 2019, 6(2), 16; https://doi.org/10.3390/informatics6020016 - 9 Apr 2019

Cited by 14 | Viewed by 7890

Abstract

RadViz is one of the few methods in Visual Analytics able to project high-dimensional data and explain formed structures in terms of data variables. However, RadViz methods have several limitations in terms of scalability in the number of variables, ambiguities created in the [...] Read more.

RadViz is one of the few methods in Visual Analytics able to project high-dimensional data and explain formed structures in terms of data variables. However, RadViz methods have several limitations in terms of scalability in the number of variables, ambiguities created in the projection by the placement of variables along the circular design space, and ability to segregate similar instances into visual clusters. To address these limitations, we propose RadViz++, a set of techniques for interactive exploration of high-dimensional data using a RadViz-type metaphor. We demonstrate the added value of our method by comparing it with existing high-dimensional visualization methods, and also by analyzing a complex real-world dataset having over a hundred variables. Full article

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22 pages, 365 KiB

Open AccessFeature PaperArticle

Understanding the EMR-Related Experiences of Pregnant Japanese Women to Redesign Antenatal Care EMR Systems

by Samar Helou, Victoria Abou-Khalil, Goshiro Yamamoto, Eiji Kondoh, Hiroshi Tamura, Shusuke Hiragi, Osamu Sugiyama, Kazuya Okamoto, Masayuki Nambu and Tomohiro Kuroda

Informatics 2019, 6(2), 15; https://doi.org/10.3390/informatics6020015 - 4 Apr 2019

Cited by 4 | Viewed by 8103

Abstract

Woman-centered antenatal care necessitates Electronic Medical Record (EMR) systems that respect women’s preferences. However, women’s preferences regarding EMR systems in antenatal care remain unknown. This work aims to understand the EMR-related experiences that pregnant Japanese women want. First, we conducted a field-based observational [...] Read more.

Woman-centered antenatal care necessitates Electronic Medical Record (EMR) systems that respect women’s preferences. However, women’s preferences regarding EMR systems in antenatal care remain unknown. This work aims to understand the EMR-related experiences that pregnant Japanese women want. First, we conducted a field-based observational study at an antenatal care clinic at a Japanese university hospital. We analyzed the data following a thematic analysis approach and found multiple EMR-related experiences that pregnant women encounter during antenatal care. Based on the observations’ findings, we administered a web survey to 413 recently pregnant Japanese women to understand their attitudes regarding the EMR-related experiences. Our results show that pregnant Japanese women want accessible, exchangeable, and biopsychosocial EMRs. They also want EMR-enabled explanations and summaries. Interestingly, differences in their demographics and stages of pregnancy affected their attitudes towards some EMR-related experiences. To respect their preferences, we propose amplifying the roles of EMR systems as tools that promote communication and woman-centeredness in antenatal care. We also propose expanding the EMR design mindset from a biomedical to a biopsychosocial-oriented one. Finally, to accommodate the differences in individual needs and preferences, we propose the design of adaptable person-centered EMR systems. Full article

(This article belongs to the Special Issue Data-Driven Healthcare Research)

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Informatics, Volume 6, Issue 2 (June 2019) – 11 articles

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