Representation Format Research Articles

Healthier Life with Digital Companions: Effects of Reflection-Level and Statement-Type of Messages on Behavior Change via a Perceived Companion

ABSTRACTQuantified-self tools track personal data as well as emotional and psychological scores, in real time, of people who use such tools. Such data have potential uses for initiating interactions to induce personal health-related behavior changes. However, notwithstanding this potential, not much benefit has been derived from the data tracked using various devices such as smartphones and fitness trackers. The main research goal of this study is to investigate how interactions of quantified-self tools should be designed for inducing user perception and behavior change. Particularly, this study uses two message representation formats (MRF) for users to perceive self-tracking tools as companion devices because the MRFs of smartphones and fitness trackers are important to interact with users in conversational interaction. This study developed a message expression algorithm, “Samantha,” to deliver personalized-messages automatically in real time about the values tracked by these devices to their users. The study studied the effect of the four message representation formats on the perception of companion and to induce behavior change.

Genres, media, and recontextualization practices

AbstractThe main argument put forward in this paper is that traditional linguistic genre theories neglect the importance of media and their modal affordances in the formation of new genres. It argues that media cannot be viewed as (passive) configurations of technical, semiotic, and cultural features which are chosen by actors/ rhetors in order to serve their communicative needs, but rather as mediators whose modal affordances actively influence communicators’ meaning making choices. In order to support this argument, it will be shown how forms of discourse representation gradually developed from a stylistic device in oral communication to a genre constitutive practice (e.g., in printed academic communication), and eventually became a genre of its own (as the practice of “sharing” content) in social media communication. In the analyses, the focus is on the interplay between modal affordances of the different media in which discourse representation formats are used, their formal properties, and pragmatic factors (like audience expectations in different communicative genres and situations). It is shown how innovative aspects of a medium influence formal features of discourse representation which in turn serve different communicative purposes in different genres.

Usability Evaluation of Visual Representation Formats for Emergency Department Records.

Background Integration of electronic information is a challenge for multitasking emergency providers, with implications for patient safety. Visual representations can assist sense-making of complex data sets; however, benefit and acceptability in emergency care is unproven. Objectives This article evaluates visually focused alternatives to lists or tabular formats, to better understand possible usability in Emergency Department Information System (EDIS). Methods A counterbalanced, repeated-measures experiment, satisfaction surveys, and narrative content analysis was conducted remotely by Web platform. Participants were 37 American emergency physicians; they completed 16 clinical cases comparing 4 visual designs to the control formats from a commercially available EDIS. They then evaluated two additional chart overview representations without controls. Results Visual designs provided benefit in several areas compared to controls. Task correctness (90% to 76%; p = 0.003) and completion time (median: 49–74 seconds; p < 0.001) were superior for a medication history timeline with class and schedule highlighting. Completion time (median: 45–60 seconds; p = 0.03) was superior for a past medical history design, using pertinent diagnosis codes in highlighting rules. Less mental effort was reported for visual allergy ( p = 0.04), past medical history ( p < 0.001), and medication timeline ( p < 0.001) designs. Most of the participants agreed with statements of likeability, preference, and benefit for visual designs; nonetheless, contrary opinions were seen, and more complex designs were viewed less favorably. Conclusion Physician performance with visual representations of clinical data can in some cases exceed standard formats, even in absence of training. Highlighting of priority clinical categories was rated easier-to-use on average than unhighlighted controls. Perceived complexity of timeline representations can limit desirability for a subset of users, despite potential benefit.

Local Frequency Interpretation and Non-Local Self-Similarity on Graph for Point Cloud Inpainting.

As 3D scanning devices and depth sensors mature, point clouds have attracted increasing attention as a format for 3D object representation, with applications in various fields such as tele-presence, navigation and heritage reconstruction. However, point clouds usually exhibit holes of missing data, mainly due to the limitation of acquisition techniques and complicated structure. Further, point clouds are defined on irregular non- Euclidean domains, which is challenging to address especially with conventional signal processing tools. Hence, leveraging on recent advances in graph signal processing, we propose an efficient point cloud inpainting method, exploiting both the local smoothness and the non-local self-similarity in point clouds. Specifically, we first propose a frequency interpretation in graph nodal domain, based on which we derive the smoothing and denoising properties of a graph-signal smoothness prior in order to describe the local smoothness of point clouds. Secondly, we explore the characteristics of non-local self-similarity, by globally searching for the most similar area to the missing region. The similarity metric between two areas is defined based on the direct component and the anisotropic graph total variation of normals in each area. Finally, we formulate the hole-filling step as an optimization problem based on the selected most similar area and regularized by the graph-signal smoothness prior. Besides, we propose voxelization and automatic hole detection methods for the point cloud prior to inpainting. Experimental results show that the proposed approach outperforms four competing methods significantly, both in objective and subjective quality.

JPEG column: 82nd JPEG meeting in Lisbon, Portugal

JPEG has been the most common representation format of digital images for more than 25 years. Other image representation formats have been standardised by JPEG committee like JPEG 2000 or more recently JPEG XS. Furthermore, JPEG has been extended with new functionalities like HDR or alpha plane coding with the JPEG XT standard, and more recently with a reference software. Another solutions have been also proposed by different players with limited success. The JPEG committee decided it is the time to create a new working item, named JPEG XL, that aims to develop an image coding standard with increased quality and flexibility combined with a better compression efficiency. The evaluation of the call for proposals responses had already confirmed the industry interest, and development of core experiments has now begun. Several functionalities will be considered, like support for lossless transcoding of images represented with JPEG standard.

Model execution tracing: a systematic mapping study

Model-Driven Engineering is a development paradigm that uses models instead of code as primary development artifacts. In this paper, we focus on executable models, which are used to abstract the behavior of systems for the purpose of verifying and validating (V&V) a system’s properties. Model execution tracing (i.e., obtaining and analyzing traces of model executions) is an important enabler for many V&V techniques including testing, model checking, and system comprehension. This may explain the increase in the number of proposed approaches on tracing model executions in the last years. Despite the increased attention, there is currently no clear understanding of the state of the art in this research field, making it difficult to identify research gaps and opportunities. The goal of this paper is to survey and classify existing work on model execution tracing, and identify promising future research directions. To achieve this, we conducted a systematic mapping study where we examined 64 primary studies out of 645 found publications. We found that the majority of model execution tracing approaches has been developed for the purpose of testing and dynamic analysis. Furthermore, most approaches target specific modeling languages and rely on custom trace representation formats, hindering the synergy among tools and exchange of data. This study also revealed that most existing approaches were not validated empirically, raising doubts as to their effectiveness in practice. Our results suggest that future research should focus on developing a common trace exchange format for traces, designing scalable trace representations, as well as conducting empirical studies to assess the effectiveness of proposed approaches.

The Influence of Business Process Representation on Performance of Different Task Types

ABSTRACTThe analysis of business processes is an integral part of audit methodology. In both auditing research and process modeling research, there is an ongoing debate on which representation format might be best suited to support analysis tasks. Most important in this context is the question of whether process models as visual representation might be superior to textual narratives. This paper investigates the affinity of different tasks with two process representational formats: textual narratives and visual diagrams (BPMN models). Our findings demonstrate that the representation format has an impact on task performance and that the direction of this impact depends upon the affinity of the tasks type with the representation format. This implies that auditors are best provided with different process representations, depending on the task they are performing. These findings have important implications for research on auditing tasks, and more broadly also for software engineering and information systems research.

The format of problem representation for in‐game learning supports

AbstractA promising method to support game‐based learning is to facilitate learners' externalization of cognitive and metacognitive processes. Externalizing Problem Representation (EPR) refers to a cognitive behaviour in which a learner constructs her own representations overtly. The purpose of this study is to investigate whether learning supports promoting EPR enhance qualitative understanding and quantitative proficiency in ratios and proportional relationships in a learning game (i.e., E‐Rebuild) context. Specifically, this study investigated the effects of representation format in problem representation on qualitative understanding and quantitative proficiency in a learning game context.The results of this study indicate that (a) symbolic learning supports better facilitate comprehension of math concepts and their relations than iconic learning supports in video game contexts, (b) symbolic learning supports better facilitate players' reflection for implicit understanding and promote their math problem‐solving skills, (c) participants in the symbolic learning support group increased significantly in qualitative understanding but not in quantitative proficiency after gameplay, and (d) participants in the iconic learning support group experienced significant growth in quantitative proficiency but not in qualitative understanding after gameplay.

The DialogBank: dialogues with interoperable annotations

This paper presents the DialogBank, a new language resource consisting of dialogues with gold standard annotations according to the ISO 24617-2 standard. Some of these dialogues have been taken from existing corpora and have been re-annotated, offering the possibility to compare annotations according to different schemes; others have been newly annotated directly according to the standard. The ISO standard annotations in the DialogBank make use of three alternative representation formats, which are shown to be interoperable. The (re-)annotation brought certain deficiencies and limitations of the ISO standard to light, which call for considering possible revisions and extensions, and for exploring the possible integration of dialogue act annotations with other semantic annotations.

Security Incident Information Exchange for Cloud Service Provisioning Chains

Online services are increasingly becoming a composition of different cloud services, making incident-handling difficult, as Cloud Service Providers (CSPs) with end-user customers need information from other providers about incidents that occur at upstream CSPs to inform their users. In this paper, we argue the need for commonly agreed-upon incident information exchanges between providers to improve accountability of CSPs, and present both such a format and a prototype implementing it. The solution can handle simple incident information natively as well as embed standard representation formats for incident-sharing, such as IODEF and STIX. Preliminary interviews show a desire for such a solution. The discussion considers both technical challenges and non-technical aspects related to improving the situation for incident response in cloud-computing scenarios. Our solution holds the potential of making incident-sharing more efficient.

Restricted Sensitive Attributes-based Sequential Anonymization (RSA-SA) approach for privacy-preserving data stream publishing

Data streams have become a widely-adopted data representation format in many real-world applications. This data streaming may be published for different scientific research, mining, or analysis purposes. However, such streams may contain personal-specific data that could be considered as sensitive about individuals. This makes the privacy preserving of data streams against privacy disclosure attacks, while maintaining their utilization, is a real challenge. Some studies have considered privacy-preserving publishing over data streams with only Single Sensitive Attribute, in which they do not protect the published streams from all possible privacy attacks. In this paper, we propose a novel Restricted Sensitive Attributes-based Sequential Anonymization (RSA-SA) approach for privacy-preserving data stream publishing. Besides, two new privacy restrictions are introduced to restrict the published Sensitive Attributes values: Semantic-diversity and Sensitivity-diversity. RSA-SA can protect the sensitive values of the published data streams against the related privacy attacks, including the attribute disclosure, skewness, similarity, and sensitivity attacks. In addition, RSA-SA handles data streams that have either single or multiple sensitive attributes with minimum information loss and delay time. Thus, the data utility of the published data streams is efficiently maintained to provide more accurate mining and analytical results, where robust invulnerability to privacy attacks is sustained.

Development of STEP AP224 Extractor for Interfacing Feature Based CAPP to STEP-NC (AP238)

Manufacturing features represent area of interest on the machinable surface of a part, which can provide a unique set of removable volumes from part. Feature description in standard for exchange of product (STEP) AP224 is an efficient neutral format for the development of feature based process planning. Process planning information of features can be converted to numerical control (NC) code to have complete manufacturing information of part. STEP-NC code provides an efficient manufacturing information model compared to G-M codes. In this work, an interface is developed for extraction of feature information available in AP224 (AIM) format and the ruled-based approach is used to select different process planning parameters. A graphical user interface (GUI) is developed for the interface for displaying features information as represented in AP224 file. Furthermore, the interface generates STEP-NC code in AP238 format. The developed interface has three modules. 1) Module I: Reading interface for STEP AP224 file and development of GUI. 2) Module II: Selection of feature based process planning parameters. 3) Module III: Writing interface for STEP-NC (AP238). The developed interface has been implemented in Java through Java standard data access interface (JSDAI™). The generated STEP-NC AP238 code for the test part has been successfully simulated on STEP-NC Machine™, an AP238 simulator. This article also provides an in-depth view of application interpreted model (AIM) representation format of STEP for AP224 and AP238.

UniLectin3D, a database of carbohydrate binding proteins with curated information on 3D structures and interacting ligands.

Lectins, and related receptors such as adhesins and toxins, are glycan-binding proteins from all origins that decipher the glycocode, i.e. the structural information encoded in the conformation of complex carbohydrates present on the surface of all cells. Lectins are still poorly classified and annotated, but since their functions are based on ligand recognition, their 3D-structures provide a solid foundation for characterization. UniLectin3D is a curated database that classifies lectins on origin and fold, with cross-links to literature, other databases in glycosciences and functional data such as known specificity. The database provides detailed information on lectins, their bound glycan ligands, and features their interactions using the Protein–Ligand Interaction Profiler (PLIP) server. Special care was devoted to the description of the bound glycan ligands with the use of simple graphical representation and numerical format for cross-linking to other databases in glycoscience. We conceived the design of the database architecture and the navigation tools to account for all organisms, as well as to search for oligosaccharide epitopes complexed within specified binding sites. UniLectin3D is accessible at https://www.unilectin.eu/unilectin3D.

RDF Data Storage and Query Processing Schemes

The Resource Description Framework (RDF) represents a main ingredient and data representation format for Linked Data and the Semantic Web. It supports a generic graph-based data model and data representation format for describing things, including their relationships with other things. As the size of RDF datasets is growing fast, RDF data management systems must be able to cope with growing amounts of data. Even though physically handling RDF data using a relational table is possible, querying a giant triple table becomes very expensive because of the multiple nested joins required for answering graph queries. In addition, the heterogeneity of RDF Data poses entirely new challenges to database systems. This article provides a comprehensive study of the state of the art in handling and querying RDF data. In particular, we focus on data storage techniques, indexing strategies, and query execution mechanisms. Moreover, we provide a classification of existing systems and approaches. We also provide an overview of the various benchmarking efforts in this context and discuss some of the open problems in this domain.

Striped Data Server for Scalable Parallel Data Analysis

A columnar data representation is known to be an efficient way for data storage, specifically in cases when the analysis is often done based only on a small fragment of the available data structures. A data representation like Apache Parquet is a step forward from a columnar representation, which splits data horizontally to allow for easy parallelization of data analysis. Based on the general idea of columnar data storage, working on the FNAL LDRD Project FNAL-LDRD-2016-032, we have developed a striped data representation, which, we believe, is better suited to the needs of High Energy Physics data analysis. A traditional columnar approach allows for efficient data analysis of complex structures. While keeping all the benefits of columnar data representations, the striped mechanism goes further by enabling easy parallelization of computations without requiring special hardware. We will present an implementation and some performance characteristics of such a data representation mechanism using a distributed no-SQL database or a local file system, unified under the same API and data representation model. The representation is efficient and at the same time simple so that it allows for a common data model and APIs for wide range of underlying storage mechanisms such as distributed no-SQL databases and local file systems. Striped storage adopts Numpy arrays as its basic data representation format, which makes it easy and efficient to use in Python applications. The Striped Data Server is a web service, which allows to hide the server implementation details from the end user, easily exposes data to WAN users, and allows to utilize well known and developed data caching solutions to further increase data access efficiency. We are considering the Striped Data Server as the core of an enterprise scale data analysis platform for High Energy Physics and similar areas of data processing. We have been testing this architecture with a 2TB dataset from a CMS dark matter search and plan to expand it to multiple 100 TB or even PB scale. We will present the striped format, Striped Data Server architecture and performance test results.

Interactive 3D Exploration of RDF Graphs through Semantic Planes

This article presents Tarsier, a tool for the interactive 3D visualization of RDF graphs. Tarsier is mainly intended to support teachers introducing students to Semantic Web data representation formalisms and developers in the debugging of applications based on Semantic Web knowledge bases. The tool proposes the metaphor of semantic planes as a way to visualize an RDF graph. A semantic plane contains all the RDF terms sharing a common concept; it can be created, and further split into several planes, through a set of UI controls or through SPARQL 1.1 queries, with the full support of OWL and RDFS. Thanks to the 3D visualization, links between semantic planes can be highlighted and the user can navigate within the 3D scene to find the better perspective to analyze data. Data can be gathered from generic SPARQL 1.1 protocol services. We believe that Tarsier will enhance the human friendliness of semantic technologies by: (1) helping newcomers assimilate new data representation formats; and (2) increasing the capabilities of inspection to detect relevant situations even in complex RDF graphs.

JPEG column

During this meeting, JPEG had a final celebration of the 25th anniversary of its first JPEG standard, usually known as JPEG-1. This celebration coincides with two interesting facts. The first was the approval of a reference software for JPEG-1, "only" after 25 years. At the time of approval of the first JPEG standard a reference software was not considered, as it is common in recent image standards. However, the JPEG committee decided that was still important to provide a reference software, as current applications and standards can largely benefit on this specification. The second coincidence was the launch of a call for proposals for a next generation image coding standard, JPEG XL. This standard will define a new representation format for Photographic information, that includes the current technological developments, and can become an alternative to the 25 years old JPEG standard.

Improving the representation and conversion of mathematical formulae by considering their textual context.

Mathematical formulae represent complex semantic information in a concise form. Especially in Science, Technology, Engineering, and Mathematics, mathematical formulae are crucial for communicating information, e.g., in scientific papers, and to perform computations using computer algebra systems. Enabling computers to access the information encoded in mathematical formulae requires machine-readable formats that can represent both the presentation and content, i.e., the semantics, of formulae. Exchanging such information between systems additionally requires conversion methods for mathematical representation formats. We analyze how the semantic enrichment of formulae improves the format conversion process and show that considering the textual context of formulae reduces the error rate of such conversions. Our main contributions are: (1) providing an openly available benchmark dataset for the mathematical format conversion task consisting of a newly created test collection, an extensive, manually curated gold standard and task-specific evaluation metrics; (2) performing a quantitative evaluation of state-of-the-art tools for mathematical format conversions; (3) presenting a new approach that considers the textual context of formulae to reduce the error rate for mathematical format conversions. Our benchmark dataset facilitates future research on mathematical format conversions as well as research on many problems in mathematical information retrieval. Because we annotated and linked all components of formulae, e.g., identifiers, operators and other entities, to Wikidata entries, the gold standard can, for instance, be used to train methods for formula concept discovery and recognition. Such methods can then be applied to improve mathematical information retrieval systems, e.g., for semantic formula search, recommendation of mathematical content, or detection of mathematical plagiarism.

Explaining embodied emotions – with and without representations

Embodied accounts have offered a theoretical framework in which emotions are understood to be patterned embodied responses that are about core relational themes. Some authors argue that this intentionality should be understood in terms of some kind of non-conceptual representation format, while others suggest a radical enactivist framework that takes emotions to be intentional but not representational. In this paper I will argue that the abstract nature of the core relational themes emotions are about and the interrelatedness of emotions with each other and with other mental states speak in favor of emotions being representations.

Lossless coding of light field images based on minimum-rate predictors

Recent developments in light field acquisition and computational photography are driving new research efforts on light field encoding methods, capable of exploiting the specific features of this type of visual data. This paper presents a research study of lossless light field image compression, using Minimum-Rate Predictors (MRP) and mainstream image and video encoders. The research is focused on three light field representation formats: lenslet images, stack of sub-aperture images and epipolar images. The main contributions of this work are the ‘Spiral-blackend’ serialization method and the use of MRP for the lossless compression of light fields with joint encoding of RGB data. The results show that the lenslet format yields lower compression efficiencies than other formats. Furthermore, it is demonstrated that the MRP algorithm consistently outperforms HEVC-RExt, JPEG2000, JPEG-LS and CALIC when light fields are represented by either a stack of sub-aperture or epipolar images.