Recent Advances in Multi Robot Systems

To design a team of robots which is able to perform given tasks is a great concern of many members of robotics community. There are many problems left to be solved in order to have the fully functional robot team. Robotics community is trying hard to solve such problems (navigation, task allocation, communication, adaptation, control, ...). This book represents the contributions of the top researchers in this field and will serve as a valuable tool for professionals in this interdisciplinary field. It is focused on the challenging issues of team architectures, vehicle learning and adaptation, heterogeneous group control and cooperation, task selection, dynamic autonomy, mixed initiative, and human and robot team interaction. The book consists of 16 chapters introducing both basic research and advanced developments. Topics covered include kinematics, dynamic analysis, accuracy, optimization design, modelling, simulation and control of multi robot systems

Integrated Architecture for Configuration and Service Management in MANET Environments

Esta tesis nos ha permitido trasladar algunos conceptos teóricos de la computación ubicua a escenarios reales, identificando las necesidades específicas de diferentes tipos de aplicaciones. Con el fin de alcanzar este objetivo, proponemos dos prototipos que proporcionan servicios sensibles al contexto en diferentes entornos, tales como conferencias o salas de recuperación en hospitales. Estos prototipos experimentales explotan la tecnología Bluetooth para ofrecer información basada en las preferencias del usuario. En ambos casos, hemos llevado a cabo algunos experimentos con el fin de evaluar el comportamiento de los sistemas y su rendimento. También abordamos en esta tesis el problema de la autoconfiguración de redes MANET basadas en el estándar 802.11 a través de dos soluciones novedosas. La primera es una solución centralizada que se basa en la tecnología Bluetooth, mientras la segunda es una solución distribuida que no necesita recurrir a ninguna tecnología adicional, ya que se basa en el uso del parámetro SSID. Ambos métodos se han diseñado para permitir que usuarios no expertos puedan unirse a una red MANET de forma transparente, proporcionando una configuración automática, rápida, y fiable de los terminales. Los resultados experimentales en implementaciones reales nos han permitido evaluar el rendimiento de las soluciones propuestas y demostrar que las estaciones cercanas se pueden configurar en pocos segundos. Además, hemos comparado ambas soluciones entre sí para poner de manifiesto las diferentes ventajas y desventajas en cuanto a rendimento. La principal contribución de esta tesis es EasyMANET, una plataforma ampliable y configurable cuyo objetivo es automatizar lo máximo posible las tareas que afectan a la configuración y puesta en marcha de redes MANET, de modo que su uso sea más simple y accesible.Cano Reyes, J. (2012). Integrated Architecture for Configuration and Service Management in MANET Environments [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/14675Palanci

The Impact of Digital Technologies on Public Health in Developed and Developing Countries

This open access book constitutes the refereed proceedings of the 18th International Conference on String Processing and Information Retrieval, ICOST 2020, held in Hammamet, Tunisia, in June 2020.* The 17 full papers and 23 short papers presented in this volume were carefully reviewed and selected from 49 submissions. They cover topics such as: IoT and AI solutions for e-health; biomedical and health informatics; behavior and activity monitoring; behavior and activity monitoring; and wellbeing technology. *This conference was held virtually due to the COVID-19 pandemic

Improving Access and Mental Health for Youth Through Virtual Models of Care

The overall objective of this research is to evaluate the use of a mobile health smartphone application (app) to improve the mental health of youth between the ages of 14–25 years, with symptoms of anxiety/depression. This project includes 115 youth who are accessing outpatient mental health services at one of three hospitals and two community agencies. The youth and care providers are using eHealth technology to enhance care. The technology uses mobile questionnaires to help promote self-assessment and track changes to support the plan of care. The technology also allows secure virtual treatment visits that youth can participate in through mobile devices. This longitudinal study uses participatory action research with mixed methods. The majority of participants identified themselves as Caucasian (66.9%). Expectedly, the demographics revealed that Anxiety Disorders and Mood Disorders were highly prevalent within the sample (71.9% and 67.5% respectively). Findings from the qualitative summary established that both staff and youth found the software and platform beneficial

MDFRCNN: Malware Detection using Faster Region Proposals Convolution Neural Network

Technological advancement of smart devices has opened up a new trend: Internet of Everything (IoE), where all devices are connected to the web. Large scale networking benefits the community by increasing connectivity and giving control of physical devices. On the other hand, there exists an increased ‘Threat’ of an ‘Attack’. Attackers are targeting these devices, as it may provide an easier ‘backdoor entry to the users’ network’.MALicious softWARE (MalWare) is a major threat to user security. Fast and accurate detection of malware attacks are the sine qua non of IoE, where large scale networking is involved. The paper proposes use of a visualization technique where the disassembled malware code is converted into gray images, as well as use of Image Similarity based Statistical Parameters (ISSP) such as Normalized Cross correlation (NCC), Average difference (AD), Maximum difference (MaxD), Singular Structural Similarity Index Module (SSIM), Laplacian Mean Square Error (LMSE), MSE and PSNR. A vector consisting of gray image with statistical parameters is trained using a Faster Region proposals Convolution Neural Network (F-RCNN) classifier. The experiment results are promising as the proposed method includes ISSP with F-RCNN training. Overall training time of learning the semantics of higher-level malicious behaviors is less. Identification of malware (testing phase) is also performed in less time. The fusion of image and statistical parameter enhances system performance with greater accuracy. The benchmark database from Microsoft Malware Classification challenge has been used to analyze system performance, which is available on the Kaggle website. An overall average classification accuracy of 98.12% is achieved by the proposed method

The Impact of Digital Technologies on Public Health in Developed and Developing Countries

This open access book constitutes the refereed proceedings of the 18th International Conference on String Processing and Information Retrieval, ICOST 2020, held in Hammamet, Tunisia, in June 2020.* The 17 full papers and 23 short papers presented in this volume were carefully reviewed and selected from 49 submissions. They cover topics such as: IoT and AI solutions for e-health; biomedical and health informatics; behavior and activity monitoring; behavior and activity monitoring; and wellbeing technology. *This conference was held virtually due to the COVID-19 pandemic

Lateralization of the visual word form area in patients with alexia after stroke

Background Knowledge of the process by which visual information is integrated into the brain reading system promotes a better understanding of writing and reading models. Objective This study aimed to use functional Magnetic Resonance Imaging (fMRI) to explore whether the Blood-oxygen-level dependent (BOLD) contrast imaging patterns, of putative cortical region of the Visual Word Form Area (VWFA), are distinct in aphasia patients with moder- ate and severe alexia. Methods Twelve chronic stroke patients (5 patients with severe alexia and 7 pa- tients with moderate alexia) were included. A word categorization task was used to examine responses in the VWFA and its right homolog re- gion. Patients performed a semantic decision task in which words were contrasted with non-verbal fonts to assess the lateralization of reading ability in the ventral occipitotemporal region. Results A fixed effects (FFX) general linear model (GLM) multi-study from the contrast of patients with moderate alexia and those with severe alexia (FDR, p = 0.05, corrected for multiples comparisons using a Threshold Estimator plugin (1000 Monte Carlo simulations), was per- formed. Activation of the left VWFA was robust in patients with mod- erate alexia. Aphasia patients with severe reading deficits also activated the right homolog VWFA. Conclusions This bilateral activation pattern only in patients with severe alexia could be interpreted as a result of reduced recruitment of the left VWFA for reading tasks due to the severe reading deficit. This study provides some new insights about reading pathways and possible neuroplasti- city mechanisms in aphasia patients with alexia. Additional reports could explore the predictive value of right VWFA activation for reading recovery and aid language therapy in patients with aphasia.N/

Journal of Telecommunications and Information Technology, 2011, nr 2

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