1,720,962 research outputs found
A Framework for Indoor Positioning Including Building Topology
Full text linkIn many application domains, position information is of fundamental importance. However, unlike the case of outdoor positioning, producing an accurate position estimation in the indoor setting turns out to be quite difficult. One of the most common localisation strategies makes use of fingerprinting. Research in this area has been faced with a number of challenges, leading to the proposal of a number of localisation algorithms, sampling strategies, benchmark datasets, and representations of building information. This proliferation made the modeling of the indoor positioning domain quite hard from both a theoretical and a practical point of view. In this paper, we propose a general and extensible framework, based on a relational database, that pairs fingerprints with building information. We show how the proposed system successfully deals with a number of problems that affect indoor positioning, supporting a large set of relevant tasks. The source code of the framework is available online, as well as an implementation of it, that provides an interactive open repository of indoor positioning data
An Information System for Biblical Manuscripts Paratexts: Modeling, Implementation, and Future Directions
Full text linkParatexts-such as prologues, summaries, prefaces, and annotations-shape the presentation, interpretation, and transmission of texts across audiences and periods. Their study provides critical insights into the historical, philological, and socio-cultural dimensions of manuscript production, use, and dissemination. Yet, a comprehensive analysis of Latin biblical paratexts remains lacking despite notable efforts on specific subsets, such as Marilena Maniaci's researches on Atlantic Bibles and Chiara Ruzzier's studies on 13th-century portable Bibles. This article takes part at addressing such a gap presenting an information system for managing paratexts in medieval Latin biblical manuscripts. Our contribution is twofold: (1) we propose a conceptual model of the domain of medieval Latin biblical manuscripts paratexts to standardize the field and support future research; and (2) we implement such a model through a relational database, which acts as the core of an information system for documenting and analyzing paratexts. Its open access prototype, already available, facilitates data organization and analysis, enabling prospective advanced applications, including artificial intelligence techniques
Towards interpretability in fingerprint based indoor positioning: May attention be with us
Full text linkIn a world increasingly pervaded by mobile and IoT devices, position-related information is gaining more and more importance. Highly accurate and standardized positioning techniques are not yet available for indoor scenarios, unlike for the outdoor case. The most commonly used method for indoor positioning is WiFi fingerprinting, which, despite its well-recognized advantages, still suffers from some notable limitations. Recently, approaches relying on deep learning showed promising results even though their lack of interpretability is still a significant drawback. In this paper, for the first time, we propose a domain-specific concept of interpretability, based on identifying the access points that are most relevant to a position estimate. The goal is to enhance the positioning process by gaining novel scientific knowledge and operational insights, without worsening the performance of the task. We show how it is possible to practically achieve both a local and a global notion of interpretability by means of a deep learning model equipped with an attention module, applied to a ranking based fingerprint representation. Since off-the-shelf application of attention does not guarantee to achieve a faithful nor plausible interpretation, we verified through a series of thoroughly designed quantitative and qualitative clustering based experiments the existence of a strong relationship between the obtained interpretations and the positioning domain. Finally, as by-product, we showed an example of how the new knowledge can be used in principle to improve positioning performance
Let's forget about exact signal strength: Indoor positioning based on access point ranking and recurrent neural networks
No full textPositioning is a key task in many different contexts. In the last decades, it has considerably evolved, but, while there are a lot of systems that offer a quite good performance in outdoor scenarios, the indoor realm is still under exploration. Among existing technologies and techniques for indoor positioning, the most popular one makes use of WiFi fingerprints. Such an approach has many advantages; however, its adoption as a standard for everyday life is limited due to issues like the (time) costly radio map construction, and radio signal strength fluctuations in indoor environments. In this paper, we present a novel solution for indoor positioning based on deep learning, that ignores as much as possible signal strengths, in order to reduce the adverse effects associated with their usage. It exploits signal strength only to generate a ranking-based representation of the access points associated with a fingerprint. By developing and testing two recurrent neural network models, we show that the proposed approach is able to achieve a positioning performance, based on access point ranking, comparable to the one achieved by state-of-the-art algorithms on multiple publicly available indoor datasets. As additional benefits, compared to existing ones, the developed solution is considerably more robust to signal fluctuations and simpler in terms of the considered data
A new similarity measure for low-sampling cellular fingerprint trajectories
No full textThe ability of determining and dealing with the trajectories followed by an object in a given (concrete or abstract) space turns out to be quite useful in a variety of contexts. This is the case, in particular, in positioning, where it can be exploited, for instance, for traffic control and user profiling. A key step in trajectory management is the evaluation of trajectory similarity. In many positioning applications, trajectories are built from Global Navigation Satellite System (GNSS) readings; however, in various scenarios, these coordinates are not available. In this paper, we focus on fingerprint positioning systems characterised by a low sampling frequency and a high heterogeneity of the observations. We start with a comprehensive analysis of well-known GNSS-based trajectory similarity measures, and show how some of them can actually be adapted to the fingerprinting setting. Then, we outline a novel approach that exploits multiple information, including both spatial and cellular identifiers with received signal strength. Finally, we make an extensive, experimental comparative evaluation of the various measures (adapted and novel ones) over a real-world fingerprint dataset
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Usage of Language Model for the Filling of Lacunae in Ancient Latin Inscriptions: A Case Study
No full textThis paper investigates the efficacy of LatinBERT in the task of infilling ancient Latin inscriptions. We contrast the baseline LatinBERT model with a version fine-tuned specifically for this task. A comprehensive experimental design evaluates the influence of various lacunae features, such as their length and relative position within the text, on the infilling process. In contrast to the results presented in LatinBERT’s original publication, our findings indicate suboptimal performance. Interestingly, a parallel study of Greek inscriptions using models like PYTHIA and Ithaca demonstrated vastly superior performance in similar tasks. This disparity underscores the need for the development of more proficient models tailored for Latin inscriptions. Moreover, our study emphasizes the importance of robust and systematic evaluation methodologies to accurately assess model performance
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