1,854 research outputs found

    Report on the Information Retrieval Festival (IRFest2017)

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    The Information Retrieval Festival took place in April 2017 in Glasgow. The focus of the workshop was to bring together IR researchers from the various Scottish universities and beyond in order to facilitate more awareness, increased interaction and reflection on the status of the field and its future. The program included an industry session, research talks, demos and posters as well as two keynotes. The first keynote was delivered by Prof. Jaana Kekalenien, who provided a historical, critical reflection of realism in Interactive Information Retrieval Experimentation, while the second keynote was delivered by Prof. Maarten de Rijke, who argued for more Artificial Intelligence usage in IR solutions and deployments. The workshop was followed by a "Tour de Scotland" where delegates were taken from Glasgow to Aberdeen for the European Conference in Information Retrieval (ECIR 2017

    Google earth forensics on IOS 10’s location service

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    The easy access and common usage of GNSS systems has provided a wealth of evidential information that may be accessed by a digital forensic investigator. Google Earth is commonly used on all manner of devices for geolocation services and consequently has a wide range of tools that will relate real time and stored GNSS data to maps. As an aid to investigation Google Earth forensics is available for use. An investigator can use it by downloading geolocation data from devices and placing it on Google Earth maps, place geolocation data on historical archival maps, or by direct usage of the application in a device. In this paper we review the Google Earth forensics tool and use a simplistic scenario to demonstrate the power of the application for courtroom walk-throughs. The entry-level tool is free and can be used effectively to enhance the presentation of geolocation data

    Computer Vision for Multimedia Geolocation in Human Trafficking Investigation: A Systematic Literature Review

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    The task of multimedia geolocation is becoming an increasingly essential component of the digital forensics toolkit to effectively combat human trafficking, child sexual exploitation, and other illegal acts. Typically, metadata-based geolocation information is stripped when multimedia content is shared via instant messaging and social media. The intricacy of geolocating, geotagging, or finding geographical clues in this content is often overly burdensome for investigators. Recent research has shown that contemporary advancements in artificial intelligence, specifically computer vision and deep learning, show significant promise towards expediting the multimedia geolocation task. This systematic literature review thoroughly examines the state-of-the-art leveraging computer vision techniques for multimedia geolocation and assesses their potential to expedite human trafficking investigation. This includes a comprehensive overview of the application of computer vision-based approaches to multimedia geolocation, identifies their applicability in combating human trafficking, and highlights the potential implications of enhanced multimedia geolocation for prosecuting human trafficking. 123 articles inform this systematic literature review. The findings suggest numerous potential paths for future impactful research on the subject

    System Development for Geolocation in Harsh Environments

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    Wireless sensor networks (WSN) consist of a set of distributed devices equipped with multiple sensors, which can be employed in different environments of varying characteristics. Nowadays, node localization has become one of their most basic and important requirements. Due to the nature of certain environments, typical positioning systems, such as Global Navigation Satellite System (GNSS), cannot be employed. Therefore, in recent years several alternative positioning mechanisms have risen. ROMOVI is a project which has as its main goal the development of low cost autonomous robots capable of monitoring and perform logistic tasks on the steep slopes of the Douro river vineyards. Integrated in this project, this dissertation proposes the development of a full-custom wireless communication system for geolocation purposes in harsh environments. Using a Symmetric Double Sided Two Way Ranging (SDS-TWR) algorithm, it is possible to achieve ranging measures between nodes, thus providing accurate relative positioning. This work focuses mainly on the study of the SDS-TWR algorithm and its major error sources, such as those due to digital clock drift, among others. A preamble based on Frank-Zadoff-Chu sequence was developed and, due to its good periodic autocorrelation properties, a system employing the transmission and reception of this preamble was implemented in hardware, through a field programmable gate array (FPGA). By employing an embedded logic processor, the Altera Nios II, control over the complete procedure of the aforementioned algorithm is possible, to perform and analyze the main advantages of the SDS-TWR algorithm. Finally, a medium access control (MAC) layer frame format was defined, in order to enable future development of communication among multiple nodes, to enhance the original algorithm and, as such, provide the capability of trilateration

    PinMe: Tracking a Smartphone User around the World

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    With the pervasive use of smartphones that sense, collect, and process valuable information about the environment, ensuring location privacy has become one of the most important concerns in the modern age. A few recent research studies discuss the feasibility of processing data gathered by a smartphone to locate the phone's owner, even when the user does not intend to share his location information, e.g., when the Global Positioning System (GPS) is off. Previous research efforts rely on at least one of the two following fundamental requirements, which significantly limit the ability of the adversary: (i) the attacker must accurately know either the user's initial location or the set of routes through which the user travels and/or (ii) the attacker must measure a set of features, e.g., the device's acceleration, for potential routes in advance and construct a training dataset. In this paper, we demonstrate that neither of the above-mentioned requirements is essential for compromising the user's location privacy. We describe PinMe, a novel user-location mechanism that exploits non-sensory/sensory data stored on the smartphone, e.g., the environment's air pressure, along with publicly-available auxiliary information, e.g., elevation maps, to estimate the user's location when all location services, e.g., GPS, are turned off.Comment: This is the preprint version: the paper has been published in IEEE Trans. Multi-Scale Computing Systems, DOI: 0.1109/TMSCS.2017.275146

    An Overview of Massive MIMO Research at the University of Bristol

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    Massive MIMO has rapidly gained popularity as a technology crucial to the capacity advances required for 5G wireless systems. Since its theoretical conception six years ago, research activity has grown exponentially, and there is now a developing industrial interest to commercialise the technology. For this to happen effectively, we believe it is crucial that further pragmatic research is conducted with a view to establish how reality differs from theoretical ideals. This paper presents an overview of the massive MIMO research activities occurring within the Communication Systems & Networks Group at the University of Bristol centred around our 128-antenna real-time testbed, which has been developed through the BIO programmable city initiative in collaboration with NI and Lund University. Through recent preliminary trials, we achieved a world first spectral efficiency of 79.4 bits/s/Hz, and subsequently demonstrated that this could be increased to 145.6 bits/s/Hz. We provide a summary of this work here along with some of our ongoing research directions such as large-scale array wave-front analysis, optimised power control and localisation techniques.Comment: Presented at the IET Radio Propagation and Technologies for 5G Conference (2016). 5 page
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