Mobilized ad-hoc networks: A reinforcement learning approach

Research in mobile ad-hoc networks has focused on situations in which nodes have no control over their movements. We investigate an important but overlooked domain in which nodes do have control over their movements. Reinforcement learning methods can be used to control both packet routing decisions and node mobility, dramatically improving the connectivity of the network. We first motivate the problem by presenting theoretical bounds for the connectivity improvement of partially mobile networks and then present superior empirical results under a variety of different scenarios in which the mobile nodes in our ad-hoc network are embedded with adaptive routing policies and learned movement policies.

Work on the Move: mobile and nomadic working methodologies.

‘Work on the move’ is a design, process-driven methodology, which uses multiple locations within an outdoors setting and movement between locations, all of which function as learning places, confined to a specified time period. Between 2012 and 2015, a team of international Higher Education product design educators (all members of Carousel, a co-operation of Erasmus members in Zwolle, Edinburgh, Nantes, Rome, Kortrijk and Oslo), industry professionals and product design students developed and tested four case studies. Each case study was conducted in a different international location and was constructed with a different focus, to help define and refine a definitive working methodology. ‘Work on the move’ explores the influence of ‘place’ upon design, in terms of the impact it has on productivity and creative problem-solving, when working away from the traditional studio/office-based environment. It also explores the significance of shared place, when working directly with a client in situ, and experiencing the place-based influences upon their businesses. While identifying location as part of the design process, the study also seeks to understand the effects of time restriction and working in transit upon creativity and productivity, within the context of specific projects.

Endocrine Inspired Modulation of Artificial Neural Networks for Mobile Robotics

Sauze, C and Neal, M. 'Endocrine Inspired Modulation of Artificial Neural Networks for Mobile Robotics', Dynamics of Learning Behavior and Neuromodulation Workshop, European Conference on Artifical Life 2007, Lisbon, Portugal, September 10th-14th 2007.

SOVEREIGN: An Autonomous Neural System for Incrementally Learning Planned Action Sequence to Navigate Towards a Rewarded Goal

How do reactive and planned behaviors interact in real time? How are sequences of such behaviors released at appropriate times during autonomous navigation to realize valued goals? Controllers for both animals and mobile robots, or animats, need reactive mechanisms for exploration, and learned plans to reach goal objects once an environment becomes familiar. The SOVEREIGN (Self-Organizing, Vision, Expectation, Recognition, Emotion, Intelligent, Goaloriented Navigation) animat model embodies these capabilities, and is tested in a 3D virtual reality environment. SOVEREIGN includes several interacting subsystems which model complementary properties of cortical What and Where processing streams and which clarify similarities between mechanisms for navigation and arm movement control. As the animat explores an environment, visual inputs are processed by networks that are sensitive to visual form and motion in the What and Where streams, respectively. Position-invariant and sizeinvariant recognition categories are learned by real-time incremental learning in the What stream. Estimates of target position relative to the animat are computed in the Where stream, and can activate approach movements toward the target. Motion cues from animat locomotion can elicit head-orienting movements to bring a new target into view. Approach and orienting movements are alternately performed during animat navigation. Cumulative estimates of each movement are derived from interacting proprioceptive and visual cues. Movement sequences are stored within a motor working memory. Sequences of visual categories are stored in a sensory working memory. These working memories trigger learning of sensory and motor sequence categories, or plans, which together control planned movements. Predictively effective chunk combinations are selectively enhanced via reinforcement learning when the animat is rewarded. Selected planning chunks effect a gradual transition from variable reactive exploratory movements to efficient goal-oriented planned movement sequences. Volitional signals gate interactions between model subsystems and the release of overt behaviors. The model can control different motor sequences under different motivational states and learns more efficient sequences to rewarded goals as exploration proceeds.

Unsupervised Neural Network for the Control of a Mobile Robot

This article introduces an unsupervised neural architecture for the control of a mobile robot. The system allows incremental learning of the plant during robot operation, with robust performance despite unexpected changes of robot parameters such as wheel radius and inter-wheel distance. The model combines Vector associative Map (VAM) learning and associate learning, enabling the robot to reach targets at arbitrary distances without knowledge of the robot kinematics and without trajectory recording, but relating wheel velocities with robot movements.

Examining the post-adoptive infusion of mobile technology in a healthcare domain: determinants and outcomes

The healthcare industry is beginning to appreciate the benefits which can be obtained from using Mobile Health Systems (MHS) at the point-of-care. As a result, healthcare organisations are investing heavily in mobile health initiatives with the expectation that users will employ the system to enhance performance. Despite widespread endorsement and support for the implementation of MHS, empirical evidence surrounding the benefits of MHS remains to be fully established. For MHS to be truly valuable, it is argued that the technological tool be infused within healthcare practitioners work practices and used to its full potential in post-adoptive scenarios. Yet, there is a paucity of research focusing on the infusion of MHS by healthcare practitioners. In order to address this gap in the literature, the objective of this study is to explore the determinants and outcomes of MHS infusion by healthcare practitioners. This research study adopts a post-positivist theory building approach to MHS infusion. Existing literature is utilised to develop a conceptual model by which the research objective is explored. Employing a mixed-method approach, this conceptual model is first advanced through a case study in the UK whereby propositions established from the literature are refined into testable hypotheses. The final phase of this research study involves the collection of empirical data from a Canadian hospital which supports the refined model and its associated hypotheses. The results from both phases of data collection are employed to develop a model of MHS infusion. The study contributes to IS theory and practice by: (1) developing a model with six determinants (Availability, MHS Self-Efficacy, Time-Criticality, Habit, Technology Trust, and Task Behaviour) and individual performance-related outcomes of MHS infusion (Effectiveness, Efficiency, and Learning), (2) examining undocumented determinants and relationships, (3) identifying prerequisite conditions that both healthcare practitioners and organisations can employ to assist with MHS infusion, (4) developing a taxonomy that provides conceptual refinement of IT infusion, and (5) informing healthcare organisations and vendors as to the performance of MHS in post-adoptive scenarios.

Conservative Interventions for mobile Pes Planus in Adults: a systematic review

Antecedentes. Pes Adulto planus (pie plano) es un problema común encontrado por muchos profesionales de la salud. A pesar de la percepción de que el pie plano puede causar dolor y deteriorar su función, la disponibilidad y el uso generalizado de diversos tratamientos, no hay consenso sobre la estrategia óptima de tratamiento. Objetivo. Evaluar la efectividad de las intervenciones conservadoras (no quirúrgicos) para pie plano en los adultos. Método. Se realizó una búsqueda sistemática de la literatura. Esto incluye: el Registro Cochrane Central de Ensayos Controlados; los Juicios CMSG Especializados Registro; una búsqueda electrónica se realizó utilizando MEDLINE (1960 a junio de 2012), EMBASE (1980 a junio de 2012), y CINAHL (1982 - junio de 2012). Revistas especializadas, listas de referencias de ensayos y artículos de revisión se realizaron búsquedas manuales. Criterios de selección: Ensayos aleatorios o cuasialeatorios de intervenciones de tratamiento para el pie plano en los adultos. Se excluyeron los ensayos que incluyeron patologías específicas como el dolor plantar del talón, las fracturas por sobrecarga de los metatarsianos, disfunción del tendón tibial posterior-, fracturas de tobillo, patologías del pie reumatoide, enfermedades neuromusculares y las complicaciones del pie diabético. Recopilación y análisis de datos: Dos autores seleccionaron de forma independiente los resultados de la búsqueda para identificar a aquellos que satisfacen los criterios de inclusión y evaluaron la calidad de los incluidos mediante una lista de control basado en la Evaluación de la Colaboración Cochrane de Riesgo. Esta herramienta se centró en el riesgo de la selección, el rendimiento, la detección, la heterogeneidad y el sesgo de notificación. Resultados. Cuatro ensayos, con 140 sujetos, cumplieron los criterios de inclusión para la revisión. Los cuatro fueron juzgados como de alto riesgo de sesgo en al menos un área, y también estaban en riesgo de sesgo incierto en al menos otra zona. Todos anotaron altamente en relación al sesgo de deserción, debido al corto seguimiento tiempos y diseños experimentales utilizados. Los datos no se agruparon debido al alto nivel de heterogeneidad identificada en las intervenciones evaluadas, los participantes seleccionados y medir los resultados. Los resultados de un estudio sugieren que después de cuatro semanas de uso ortesis puede resultar en una mejora significativa en vaivén lateral medio, y pueden resultar en una mejor, aunque no significativa, en general relacionados con la calidad de vida de los pies (Roma 2004). Un estudio (Redmond 2009) sugiere que su efecto sobre la distribución de la presión plantar en el pie puede no depender de si son personalizados o dispositivos prefabricados. Aunque este estudio se identificaron cambios significativos en algunas variables de presión plantar tanto con la costumbre y dispositivos prefabricados, otro (Esterman 2005) no encontró ningún efecto significativo de longitud ¾ ortesis prefabricadas sobre el dolor, la incidencia de lesiones, salud pie o de calidad de vida en un grupo de reclutas de la fuerza aérea. El cuarto estudio (Jung 2009) sugiere que el ejercicio de los músculos intrínsecos del pie puede mejorar el efecto de las ortesis. A pesar de estos resultados, ya que cada estudio incurrió riesgo de sesgo en al menos un área no se pueden sacar conclusiones

Using location-aware technology for learning Geography in a real digital space outside the classroom

The use of new mobile technologies is still in its infancy in many secondary schools and there is limited evidence of the educational and pedagogical benefits on pupils’ learning in the formal school context. This qualitative study focuses on the use of handheld devices to teach a topic in geography to an examination class. Action research combined with pupil observations and focus group interviews are used to capture the pupils’ experiences of using mediascapes. Activity Theory is used as a lens to structure the analysis of the data and to report on the cognitive and affective impact of m-learning on pupils’ academic performance in the topic. Increased attainment and the development of wider skills for lifelong learning were identified in the study. The adaptability of the majority of pupils to the technology resulted in increased levels of willingness to learn in this novel context.

Contingency Learning and Reactivity in Preterm and Full-Term Infants at 3 Months

Learning difficulties in preterm infants are thought to reflect impairment in arousal regulation. We examined relationships among gestational age, learning speed, and behavioral and physiological reactivity in 55 preterm and 49 full-term infants during baseline, contingency, and nonreinforcement phases of a conjugate mobile paradigm at 3 months corrected age. For all infants, negative affect, looking duration, and heart rate levels increased during contingency and nonreinforcement phases, whereas respiratory sinus arrhythmia (RSA, an index of parasympathetic activity) decreased and cortisol did not change. Learners showed greater RSA suppression and less negative affect than nonlearners. This pattern was particularly evident in the preterm group. Overall, preterm infants showed less learning, spent less time looking at the mobile, and had lower cortisol levels than full-term infants. Preterm infants also showed greater heart rate responses to contingency and dampened heart rate responses to nonreinforcement compared to full-term infants. Findings underscore differences in basal and reactivity measures in preterm compared to full-term infants and suggest that the capacity to regulate parasympathetic activity during a challenge enhances learning in preterm infants.

Cortisol, contingency learning, and memory in preterm and full-term infants

Cortisol plays an important role in learning and memory. An inverted-U shaped function has been proposed to account for the positive and negative effects of cortisol on cognitive performance and memory in adults, such that too little or too much impair but moderate amounts facilitate performance. Whether such relationships between cortisol and mental function apply to early infancy, when cortisol secretion, learning, and memory undergo rapid developmental changes, is unknown. We compared relationships between learning/memory and cortisol in preterm and full-term infants and examined whether a greater risk for adrenal insufficiency associated with prematurity produces differential cortisol-memory relationships. Learning in three-month old (corrected for gestational age) preterm and full-term infants was evaluated using a conjugate reinforcement mobile task. Memory was tested by repeating the same task 24h later. Salivary cortisol samples were collected before and 20 min after the presentation of the mobile. We found that preterm infants had lower cortisol levels and smaller cortisol responses than full-term infants. This is consistent with relative adrenal insufficiency reported in the neonatal period. Infants who showed increased cortisol levels from 0 to 20 min on Day 1 had significantly better memory, regardless of prematurity, than infants who showed decreased cortisol levels.

Android Malware Detection Using Parallel Machine Learning Classifiers

Mobile malware has continued to grow at an alarming rate despite on-going mitigation efforts. This has been much more prevalent on Android due to being an open platform that is rapidly overtaking other competing platforms in the mobile smart devices market. Recently, a new generation of Android malware families has emerged with advanced evasion capabilities which make them much more difficult to detect using conventional methods. This paper proposes and investigates a parallel machine learning based classification approach for early detection of Android malware. Using real malware samples and benign applications, a composite classification model is developed from parallel combination of heterogeneous classifiers. The empirical evaluation of the model under different combination schemes demonstrates its efficacy and potential to improve detection accuracy. More importantly, by utilizing several classifiers with diverse characteristics, their strengths can be harnessed not only for enhanced Android malware detection but also quicker white box analysis by means of the more interpretable constituent classifiers.

English Language Education at University: Trends and Challenges in Teaching and Learning Academic Discourse in the UK

This chapter discusses English Language Education at university and highlights a number of trends and their associated challenges in teaching and learning academic discourse. Academic discourse refers to the ways in which language is used by participants in academia. It encompasses written discourse, from article and book publishing, PhD theses to course assignments; spoken discourse, from study groups, tutorials, conference presentations to inaugural lectures; and more recently, computer-mediated discourse, from asynchronous text-based conferencing to academic blogs. The role of English language educators in preparing students and academics for successful participation in these academic events, or the academy, in English is not to be underestimated. Academic communication is not only vital to an individual’s success at university, but to the maintenance and creation of academic communities and to scientific progress itself (Hyland, 2009). This chapter presents an overview of academic discourse and discusses recent issues which have an impact on teaching and learning English at university and discusses their associated challenges: first, the increasing internationalisation of universities. Second, the emergence of a mobile academe in its broadest sense, in which students and academics move across traditional geopolitical, institutional and disciplinary boundaries, is discussed. Third, the growth of UK transnational higher education is examined as a trend which sees academics and students vicariously or otherwise involved in English language teaching and learning. Fourth, the chapter delves into the rapid and ongoing development in technology assisted and online learning. While responding to trends can be difficult, they can also inspire ingenuity. Furthermore, such trends and challenges will not emerge in the same manner in different contexts. The discussion in this chapter is illustrated with examples from a UK context but the implications of the trends and challenges are such that they reach beyond borders.

High accuracy android malware detection using ensemble learning

With over 50 billion downloads and more than 1.3 million apps in Google’s official market, Android has continued to gain popularity amongst smartphone users worldwide. At the same time there has been a rise in malware targeting the platform, with more recent strains employing highly sophisticated detection avoidance techniques. As traditional signature based methods become less potent in detecting unknown malware, alternatives are needed for timely zero-day discovery. Thus this paper proposes an approach that utilizes ensemble learning for Android malware detection. It combines advantages of static analysis with the efficiency and performance of ensemble machine learning to improve Android malware detection accuracy. The machine learning models are built using a large repository of malware samples and benign apps from a leading antivirus vendor. Experimental results and analysis presented shows that the proposed method which uses a large feature space to leverage the power of ensemble learning is capable of 97.3 % to 99% detection accuracy with very low false positive rates.

virtX: ein Lehr- und Lernsystem für mobile Röntgengeräte zur Verbesserung der Ausbildung im Strahlenschutz

Hintergrund und Fragestellung: Die durch röntgentechnische Diagnoseverfahren in der Medizin entstehende Strahlenbelastung für Patient und Personal soll laut Strahlenschutzverordnung so gering wie möglich gehalten werden. Um dieses zu erreichen ist ein professioneller und bedachter Umgang mit den Röntgengeräten unabdingbar. Dieses Verhalten kann derzeit jedoch nur theoretisch vermittelt werden, da sich ein Üben mit realer Strahlung von selbst verbietet. Daher stellt sich die Frage wie man die Strahlenschutzausbildung durch eine verbesserte Vermittlung der komplexen Thematik unterstützen kann. Methoden: Das CBT-System (Computer Based Training) virtX, welches das Erlernen der korrekten Handhabung mobiler Röntgengeräte unterstützt, wurde um Aspekte aus dem Bereich des Strahlenschutzes erweitert. Es wurde eine prototypische Visualisierung der entstehenden Streustrahlung sowie die Darstellung des Nutzstrahlenganges integriert. Des Weiteren wurde die Berechnung und Anzeige der virtuellen Einfallsdosis für das durchstrahlte Volumen sowie für den Bereich des Bildverstärkers hinzugefügt. Für die Berechnung und Visualisierung all dieser Komponenten werden die in virtX parametrisierbaren C-Bogen-Einstellungen, z.B. Stellung der Blenden, Positionierung des Röntgengerätes zum durchstrahlten Volumen und Strahlenintensität, herangezogen. Das so erweiterte System wurde auf einem dreitägigen Kurs für OP-Personal mit über 120 Teilnehmern eingesetzt und auf der Basis von Fragebögen evaluiert. Ergebnisse: Von den Teilnehmern gaben 55 einen ausgefüllten Evaluations-Fragebogen ab (Responserate 82%). Das Durchschnittsalter der 39 weiblichen und 15 männlichen Teilnehmer (einer o.A.) lag bei 33±8 Jahren, die Berufserfahrung bei 9,37±7 Jahren. Die Erfahrung mit dem C-Bogen wurde von einem Teilnehmer (2%) mit „Keine oder bisher nur Einführung erhalten“, von acht Teilnehmern (14%) mit „bediene einen C-Bogen gelegentlich“ und von 46 (84%) mit „bediene einen C-Bogen regelmäßig“ angegeben. 45 (92%) der Teilnehmer gaben an, durch die Visualisierung der Streustrahlung etwas Neues zur Vermeidung unnötiger Strahlenbelastung dazugelernt zu haben. Schlussfolgerung: Trotz einer bislang nur prototypischen Visualisierung der Streustrahlung können mit virtX zentrale Aspekte und Verhaltensweisen zur Vermeidung unnötiger Strahlenbelastung erfolgreich vermittelt werden und so Lücken der traditionellen Strahlenschutzausbildung geschlossen werden.

Designing personalized video-based crossmedia informal learning environments beyond iTV

Tese de doutoramento, Informática (Engenharia Informática), Universidade de Lisboa, Faculdade de Ciências, 2014