1,721,063 research outputs found
Smartphone assisted pedestrian localization within buildings
No full textLocation based services are becoming an indispensable part of our life. The wide adoption of satellite based positioning - Global Positioning System (GPS) has practically solved the problem of outdoor localization for a wide range of scenarios. Unfortunately, satellite based positioning is not possible indoors because of weak radio signals and loss of the direct line of sight from the satellites. Therefore, significant efforts have been motivated towards finding a practical solution for indoor localization especially in regards to localizing pedestrian. Certainly the topic of indoor pedestrian positioning does not lack research, there have been several research studies also various commercial solutions have been developed. What is common for all of them is that no approach has yet made a big impact within this area (e.g. GPS for outdoor localization). The reason behind this is that they either need an expensive infrastructure deployment (e.g. Wi-Fi access points) or have specialised hardware needs (e.g. network card), or have low accuracy and low reliability or have privacy issues such that pedestrians’ location is continuously monitored without their consent. There is also a trade-off between accuracy and cost. Sensing infrastructures (e.g. Wi-Fi) involving higher investments provide better accuracy where as those involving lower investments (e.g. QR codes) provide lower accuracy. Even worse, systems could not logically localize a pedestrian that is whether they are on this room or the adjoining room separated by a dividing wall and somehow if they do, they require large amounts of infrastructure to be installed into the environment. Smartphones are little less to ubiquitous. Thus, this thesis investigates an alternative approach to indoor pedestrian localization that uses smartphones to provide accurate, reliable, low cost logical localization. A significant emphasis is given on user privacy and minimal usage of infrastructure or none at all. It is demonstrated that how the information from smartphone sensors can be used for positioning in an infrastructure free environment by means of a case study. An extension to the well-studied inertial navigation technique is implemented using smartphone mounted on a toy vehicle over an artificial testbed – Scalextric track. Having learnt that infrastructure free positioning is possible using only the inertial navigation sensors embedded in smartphone, off the shelf stride estimation methods (foot step detection techniques and stride length estimation models) are applied to investigate the most suitable stride estimation method for smartphone based pedestrian dead reckoning (PDR) positioning system. Unfortunately, what was most noticeable in all the methods was that their performance was user specific and importantly, dependent on heuristic parameters. In addition, the position error grows overtime because of slowly accumulating errors in the measurement of inertial sensor. To reduce the dependency on heuristic parameters we investigate the statistical approach – ‘Kalman filter’ to get a better estimate of the stride lengths. Nevertheless, drifts are mitigated by enforcing constraints from map using map matching technique – multiple uncertain routes engine (MURE). MURE is an extension to the Kalman filter that allows location to be described using multiple discrete Gaussian distributions bound to a map. The developed map aided pedestrian dead reckoning (PDR) system was field tested in different buildings. It yielded accurate matching results as well as a significant enhancement in positioning accuracy. Experimental results demonstrate that the mean absolute position error is less than 1.3 m and 95% confidence interval is between -3.16 m to 3.32 m. To further improvise the performance of map aided PDR system an extension to map based positioning is proposed via using landmarks. Landmark based positioning uses human as a sensor to sense proximity to landmarks. Landmarks are nothing specific as such but objects that are unique enough in comparison to the adjacent items e.g. quick response (QR) codes. Experimental results demonstrate that when map based positioning is used in addition to landmark based positioning the mean absolute position error is less than 1.0 m and 95% confidence interval is between -2.0 m to 2.0 m. Smartphones are mostly held in hands however these can be used as a lieu to dedicated wearable gadgets e.g. smart glasses that contain the similar set of sensors as smartphones. Hence, we investigate a scenario similar to smart glasses via smartphone mounted on helmet. The thesis concludes that in principle it is possible to logically localize a pedestrian within buildings using the inertial sensors embedded in smartphone. The algorithms developed in this thesis are suited to cases in which it is impossible or impractical to install large amounts of fixed infrastructure into the environment in advance. Also, methods proposed in this thesis are applicable in indoor tracking applications
Meta-Analysis and Machine Learning Models to Optimize the Efficiency of Self-Healing Capacity of Cementitious Material
Full text linkConcrete and cement-based materials inherently possess an autogenous self-healing capacity. Despite the huge amount of literature on the topic, self-healing concepts still fail to consistently enter design strategies able to effectively quantify their benefits on structural performance. This study aims to develop quantitative relationships through statistical models and artificial neural network (ANN) by establishing a correlation between the mix proportions, exposure type and time, and width of the initial crack against suitably defined self-healing indices (SHI), quantifying the recovery of material performance. Furthermore, it is intended to pave the way towards consistent incorporation of self-healing concepts into durability-based design approaches for reinforced concrete structures, aimed at quantifying, with reliable confidence, the benefits in terms of slower degradation of the structural performance and extension of the service lifespan. It has been observed that the exposure type, crack width and presence of healing stimulators such as crystalline admixtures has the most significant effect on enhancing SHI and hence self-healing efficiency. However, other parameters, such as the amount of fibers and Supplementary Cementitious Materials have less impact on the autogenous self-healing. The study proposes, through suitably built design charts and ANN analysis, a straightforward input–output model to quickly predict and evaluate, and hence “design”, the self-healing efficiency of cement-based materials
Data Mining Strategies to Handle State of Art Knowledge on Self-healing Capacity of Cementitious Materials
No full textConcrete and cement-based materials inherently possess an autogenous self-healing capacity, which is even high in High and Ultra-High-Performance Concretes because of the high amount of cement and supplementary cementitious materials (SCM) and low water/cementitious material (w/c) ratio. Despite the huge amount of literature on the topic self-healing concepts still fail to consistently enter design strategies to effectively quantify their benefits on the structural performance. In this study, quantitative relationships have been developed through design charts and artificial neural network (ANN) models. The employed approaches aimed at establishing a correlation between the mix proportions, exposure time, the width of the initial crack, and volume of fibers against suitably defined self-healing indices (SHI), quantifying the recovery of material performances which can be of interest for intended applications. Therefore, this study provides, for the first time in the literature to the authors’ knowledge, a holistic investigation on the autogenous self-healing capacity of cement-based materials based on extensive articles focused on the literature data mining. The design charts are developed to pave the way towards consistent incorporation of self-healing concepts into durability-based design approaches for reinforced concrete structures, aimed at quantifying, with reliable confidence, the benefits in terms of slower degradation of the structural performance and extension of the service lifespan. Finally, through ANN, a straightforward input-output model is developed to quickly predict and evaluate the self-healing efficiency of cement-based materials which can significantly reduce, in the design stage, the time, money, and efforts of laboratory investigation
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
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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