Instantaneous threat detection based on a semantic representation of activities, zones and trajectories

Threat detection is a challenging problem, because threats appear in many variations and differences to normal behaviour can be very subtle. In this paper, we consider threats on a parking lot, where theft of a truck’s cargo occurs. The threats range from explicit, e.g. a person attacking the truck driver, to implicit, e.g. somebody loitering and then fiddling with the exterior of the truck in order to open it. Our goal is a system that is able to recognize a threat instantaneously as they develop. Typical observables of the threats are a person’s activity, presence in a particular zone and the trajectory. The novelty of this paper is an encoding of these threat observables in a semantic, intermediate-level representation, based on low-level visual features that have no intrinsic semantic meaning themselves. The aim of this representation was to bridge the semantic gap between the low-level tracks and motion and the higher-level notion of threats. In our experiments, we demonstrate that our semantic representation is more descriptive for threat detection than directly using low-level features. We find that a person’s activities are the most important elements of this semantic representation, followed by the person’s trajectory. The proposed threat detection system is very accurate: 96.6 % of the tracks are correctly interpreted, when considering the temporal context.

A cross layer protocol for energy aware and critical data delivered applications using Wireless Sensor Networks

Environment monitoring applications using Wireless Sensor Networks (WSNs) have had a lot of attention in recent years. In much of this research tasks like sensor data processing, environment states and events decision making and emergency message sending are done by a remote server. A proposed cross layer protocol for two different applications where, reliability for delivered data, delay and life time of the network need to be considered, has been simulated and the results are presented in this paper. A WSN designed for the proposed applications needs efficient MAC and routing protocols to provide a guarantee for the reliability of the data delivered from source nodes to the sink. A cross layer based on the design given in [1] has been extended and simulated for the proposed applications, with new features, such as routes discovery algorithms added. Simulation results show that the proposed cross layer based protocol can conserve energy for nodes and provide the required performance such as life time of the network, delay and reliability.

A cross layer protocol based on mac and routing protocols for healthcare applications using Wireless Sensor Networks

Using Wireless Sensor Networks (WSNs) in healthcare systems has had a lot of attention in recent years. In much of this research tasks like sensor data processing, health states decision making and emergency message sending are done by a remote server. Many patients with lots of sensor data consume a great deal of communication resources, bring a burden to the remote server and delay the decision time and notification time. A healthcare application for elderly people using WSN has been simulated in this paper. A WSN designed for the proposed healthcare application needs efficient MAC and routing protocols to provide a guarantee for the reliability of the data delivered from the patients to the medical centre. Based on these requirements, A cross layer based on the modified versions of APTEEN and GinMAC has been designed and implemented, with new features, such as a mobility module and routes discovery algorithms have been added. Simulation results show that the proposed cross layer based protocol can conserve energy for nodes and provide the required performance such as life time of the network, delay and reliability for the proposed healthcare application.

MAC protocols and mobility management module for healthcare applications using Wireless Sensor Networks

Using Wireless Sensor Networks (WSNs) in healthcare systems has had a lot of attention in recent years. In much of this research tasks like sensor data processing, health states decision making and emergency message sending are done by a remote server. Many patients with lots of sensor data consume a great deal of communication resources, bring a burden to the remote server and delay the decision time and notification time. A healthcare application for elderly people using WSN has been simulated in this paper. A WSN designed for the proposed healthcare application needs efficient Medium Access Control (MAC) and routing protocols to provide a guarantee for the reliability of the data delivered from the patients to the medical centre. Based on these requirements, the GinMAC protocol including a mobility module has been chosen, to provide the required performance such as reliability for data delivery and energy saving. Simulation results show that this modification to GinMAC can offer the required performance for the proposed healthcare application.

MAC protocols and mobility management module for healthcare applications using wireless sensor networks

Using Wireless Sensor Networks (WSNs) in healthcare systems has had a lot of attention in recent years. In much of this research tasks like sensor data processing, health states decision making and emergency message sending are done by a remote server. Many patients with lots of sensor data consume a great deal of communication resources, bring a burden to the remote server and delay the decision time and notification time. A healthcare application for elderly people using WSN has been simulated in this paper. A WSN designed for the proposed healthcare application needs efficient MAC and routing protocols to provide a guarantee for the reliability of the data delivered from the patients to the medical centre. Based on these requirements, the GinMAC protocol including a mobility module has been chosen, to provide the required performance such as reliability for data delivery and energy saving. Simulation results show that this modification to GinMAC can offer the required performance for the proposed healthcare application.

PETS 2015: datasets and challenge

This paper presents the two datasets (ARENA and P5) and the challenge that form a part of the PETS 2015 workshop. The datasets consist of scenarios recorded by us- ing multiple visual and thermal sensors. The scenarios in ARENA dataset involve different staged activities around a parked vehicle in a parking lot in UK and those in P5 dataset involve different staged activities around the perimeter of a nuclear power plant in Sweden. The scenarios of each dataset are grouped into ‘Normal’, ‘Warning’ and ‘Alarm’ categories. The Challenge specifically includes tasks that account for different steps in a video understanding system: Low-Level Video Analysis (object detection and tracking), Mid-Level Video Analysis (‘atomic’ event detection) and High-Level Video Analysis (‘complex’ event detection). The evaluation methodology used for the Challenge includes well-established measures.

PETS 2014: dataset and challenge

This paper describes the dataset and vision challenges that form part of the PETS 2014 workshop. The datasets are multisensor sequences containing different activities around a parked vehicle in a parking lot. The dataset scenarios were filmed from multiple cameras mounted on the vehicle itself and involve multiple actors. In PETS2014 workshop, 22 acted scenarios are provided of abnormal behaviour around the parked vehicle. The aim in PETS 2014 is to provide a standard benchmark that indicates how detection, tracking, abnormality and behaviour analysis systems perform against a common database. The dataset specifically addresses several vision challenges corresponding to different steps in a video understanding system: Low-Level Video Analysis (object detection and tracking), Mid-Level Video Analysis (‘simple’ event detection: the behaviour recognition of a single actor) and High-Level Video Analysis (‘complex’ event detection: the behaviour and interaction recognition of several actors).

My generation(s): cycles, branding and renewal in E4’s 'Skins'

In an era of fragmenting audience and diversified viewing platforms, youth television needs to move fast and make a lot of noise in order to capture and maintain the attention of the teenage viewer. British ensemble youth drama Skins (E4, 2007-2013) calls attention to itself with its high doses of drugs, chaotic parties and casual attitudes towards sexuality. It also moves quickly, shedding its cast every two seasons as they graduate from school, then renewing itself with a fresh generation of 16 year old characters - three cycles in total. This essay will explore the challenges of maintaining audience connections whilst resetting the narrative clock with each cycle. I suggest that the development of the Skins brand was key to the programme’s success. Branding is particularly important for an audience demographic who increasingly consume their television outside of broadcast flow and essential for a programme which renews its cast every two years. The Skins brand operate as a framework, as the central audience draw, have the strength to maintain audience connections when it ‘graduates’ those characters they identify with at the close of each cycle and starts again from scratch. This essay will explore how the Skins brand constructs a cohesive identity across its multiple generations, yet also consider how the cyclic form poses challenges for the programme’s representations and narratives. This cyclic form allows Skins to repeatedly reach out to a new audience who comes of age alongside each new generation and to reflect shifts in British youth culture. Thus Skins remains ever-youthful, seeking to maintain an at times painfully hip identity. Yet the programme has a somewhat schizophrenic identity, torn between its roots in British realist drama and surrealist comedy and an escapist aspirational glamour that shows the influence of US Teen TV. This combination results in a tendency towards a heightened melodrama at odds with Skins claims for authenticity - its much vaunted teenage advisors and young writers - with the cyclic structure serving to amplify the programme’s excessive tendencies. Each cycle wrestles with a need for continuity and familiarity - partly maintained through brand, aesthetic and setting - yet a desire for freshness and originality, to assert difference from what has gone before. I suggest that the inevitable need for each cycle to ‘top’ what has gone before results in a move away from character-based intimacy and the everyday to high-stakes drama and violence which sits uncomfortably within British youth television.

Efficiency of evolutionary algorithms in water network pipe sizing

The pipe sizing of water networks via evolutionary algorithms is of great interest because it allows the selection of alternative economical solutions that meet a set of design requirements. However, available evolutionary methods are numerous, and methodologies to compare the performance of these methods beyond obtaining a minimal solution for a given problem are currently lacking. A methodology to compare algorithms based on an efficiency rate (E) is presented here and applied to the pipe-sizing problem of four medium-sized benchmark networks (Hanoi, New York Tunnel, GoYang and R-9 Joao Pessoa). E numerically determines the performance of a given algorithm while also considering the quality of the obtained solution and the required computational effort. From the wide range of available evolutionary algorithms, four algorithms were selected to implement the methodology: a PseudoGenetic Algorithm (PGA), Particle Swarm Optimization (PSO), a Harmony Search and a modified Shuffled Frog Leaping Algorithm (SFLA). After more than 500,000 simulations, a statistical analysis was performed based on the specific parameters each algorithm requires to operate, and finally, E was analyzed for each network and algorithm. The efficiency measure indicated that PGA is the most efficient algorithm for problems of greater complexity and that HS is the most efficient algorithm for less complex problems. However, the main contribution of this work is that the proposed efficiency ratio provides a neutral strategy to compare optimization algorithms and may be useful in the future to select the most appropriate algorithm for different types of optimization problems.

Otherworlds: fantasy and history in medieval literature

This book offers a new perspective on the otherworlds of medieval literature. These fantastical realms are among the most memorable places in medieval writing, by turns beautiful and monstrous, alluring and terrifying. Passing over a river or sea, or entering into a hollow hill, heroes come upon strange and magical realms. These places are often very beautiful, filled with sweet music and adorned with precious stones and rich materials. There is often no darkness, time may pass at a different pace, and the people who dwell there are usually supernatural. Sometimes such a place is exactly what it appears to be-the land of heart's desire-but, the otherworld can also have a sinister side, trapping humans and keeping them there against their will. Otherworlds: Fantasy and History in Medieval Literature takes a fresh look at how medieval writers understood these places and why they found them so compelling. It focuses on texts from England, but places this material in the broader context of literary production in medieval Britain and Ireland. The narratives examined in this book tell a rather surprising story about medieval notions of these fantastical places. Otherworlds are actually a lot less 'other' than they might initially seem. Authors often use the idea of the otherworld to comment on very serious topics. It is not unusual for otherworld depictions to address political issues in the historical world. Most intriguing of all are those texts where locations in the real world are re-imagined as otherworlds. The regions on which this book focuses, Britain, Ireland and the surrounding islands, prove particularly susceptible to this characterization.

The evolution and heterogeneity of outward foreign direct investment from Latin America

The PhD dissertation investigates the rise of emerging country multinationals (EMNEs), a phenomenon that has opened up a series of research themes and debates. The main debate in this field is the extent to which the theories/frameworks on foreign direct investment (FDI), which have been developed from investigations on multinationals from developed countries, is relevant in explaining outward FDI from EMNEs. This debate is sparked by research suggesting that EMNEs supposedly do not hold the characteristics that are seen as a prerequisite to engaging in FDI. The underlying theme in this PhD is that the field should move away from a one size fit all categorisation of EMNEs, and explore the heterogeneity within EMNEs. Collecting data through various databases, archival articles and annual reports, there was an examination of the internationalisation process of 136 Latin American Multinationals (LAMNEs). The research explores the differences in internationalisation trajectories and global strategies and classifies firms into one of four categories. The four categories that LAMNEs fall into are: Natural-Resource Vertical Integrator, which are firms that are in resource seeking sectors; Accelerated Global, which depict firms that have become global over a very short period of time; Traditional Global, which are EMNEs that have internationalised at the same pace as developed country MNEs and Local Optimisers that only acquire or internationalise to developing countries. The analysis also looks at which decade LAMNEs engaged in FDI, to see if LAMNEs that internationalised during the 1970s and 1980s, during a time when Latin America had a closed economy, was different to LAMNEs that internationalised during the Washington consensus era of the 1990s or to firms that have only just internationalised within the last decade. The findings show that LAMNEs that internationalised before 1990 were more likely to adopt Local Optimiser strategies. However, more LAMNEs that started to internationalise during the 1990s started to adopt Traditional Global strategies, although Local Optimisers were the most prominent strategy. From 2002, there was more prominence of Accelerated Global strategies and a lot more heterogeneity among LAMNEs. Natural-Resource Vertical Integrator LAMNEs, tended to start to internationalisation process during the 1970s/1980s. Despite the rise of EMNEs, and by extension LAMNEs opting to use cross border merger and acquisitions (M&A), there is little research on whether this entry mode has been successful. Contrary to the argument that EMNEs are “internationalising successfully” through this strategy, the findings show that these firms are highly geared and are running less efficiently against their Western competitors. In comparison, LAMNEs internationalising through a more gradual approach, are outperforming their Western competitors on efficiency and are not highly geared- i.e. do not hold a lot of debt. The conclusion of the thesis is the emphasis of moving away from evaluating firms from their country or region of origin, but rather through the global strategy they are using. This will give a more a robust firm level of analysis, and help develop the understanding of EMNEs and international business theory.

The role of big data in governance: a regulatory and legal perspective of analytics in global financial services

This paper discusses how global financial institutions are using big data analytics within their compliance operations. A lot of previous research has focused on the strategic implications of big data, but not much research has considered how such tools are entwined with regulatory breaches and investigations in financial services. Our work covers two in-depth qualitative case studies, each addressing a distinct type of analytics. The first case focuses on analytics which manage everyday compliance breaches and so are expected by managers. The second case focuses on analytics which facilitate investigation and litigation where serious unexpected breaches may have occurred. In doing so, the study focuses on the micro/data to understand how these tools are influencing operational risks and practices. The paper draws from two bodies of literature, the social studies of information systems and finance to guide our analysis and practitioner recommendations. The cases illustrate how technologies are implicated in multijurisdictional challenges and regulatory conflicts at each end of the operational risk spectrum. We find that compliance analytics are both shaping and reporting regulatory matters yet often firms may have difficulties in recruiting individuals with relevant but diverse skill sets. The cases also underscore the increasing need for financial organizations to adopt robust information governance policies and processes to ease future remediation efforts.

Internal and External Time Conflicts in Adolescents: Sleep Characteristics and Interventions

Daytime fatigue and lack of sleep seem to increase throughout adolescent years. Several environmental, psychological, and biological factors have been associated with the development of sleep across adolescence. The aim of the present article is to summarize these factors and to give examples of various outcomes in sleep patterns among adolescents studied in different cultural settings. It is obvious from earlier work that many adolescents have displaced circadian rhythms and lack of adaptation to school hours due to an early school start or additional burdens for work. Several interventions have aimed to help the adaptation process by supporting sleep processes and changing scheduling, in this way promoting classroom alertness. In summary, adolescents worldwide shorten their sleep due to schoolwork hours and additional work, especially by disturbing their sleep due to circadian misalignment.

A novel approach for distributed application scheduling based on prediction of communication events

The evolution of commodity computing lead to the possibility of efficient usage of interconnected machines to solve computationally-intensive tasks, which were previously solvable only by using expensive supercomputers. This, however, required new methods for process scheduling and distribution, considering the network latency, communication cost, heterogeneous environments and distributed computing constraints. An efficient distribution of processes over such environments requires an adequate scheduling strategy, as the cost of inefficient process allocation is unacceptably high. Therefore, a knowledge and prediction of application behavior is essential to perform effective scheduling. In this paper, we overview the evolution of scheduling approaches, focusing on distributed environments. We also evaluate the current approaches for process behavior extraction and prediction, aiming at selecting an adequate technique for online prediction of application execution. Based on this evaluation, we propose a novel model for application behavior prediction, considering chaotic properties of such behavior and the automatic detection of critical execution points. The proposed model is applied and evaluated for process scheduling in cluster and grid computing environments. The obtained results demonstrate that prediction of the process behavior is essential for efficient scheduling in large-scale and heterogeneous distributed environments, outperforming conventional scheduling policies by a factor of 10, and even more in some cases. Furthermore, the proposed approach proves to be efficient for online predictions due to its low computational cost and good precision. (C) 2009 Elsevier B.V. All rights reserved.

Prediction of dynamical, nonlinear, and unstable process behavior

Process scheduling techniques consider the current load situation to allocate computing resources. Those techniques make approximations such as the average of communication, processing, and memory access to improve the process scheduling, although processes may present different behaviors during their whole execution. They may start with high communication requirements and later just processing. By discovering how processes behave over time, we believe it is possible to improve the resource allocation. This has motivated this paper which adopts chaos theory concepts and nonlinear prediction techniques in order to model and predict process behavior. Results confirm the radial basis function technique which presents good predictions and also low processing demands show what is essential in a real distributed environment.