Intelligent Sensor Networks

In the last decade, wireless or wired sensor networks have attracted much attention. However, most designs target general sensor network issues including protocol stack (routing, MAC, etc.) and security issues. This book focuses on the close integration of sensing, networking, and smart signal processing via machine learning. Based on their world-class research, the authors present the fundamentals of intelligent sensor networks. They cover sensing and sampling, distributed signal processing, and intelligent signal learning. In addition, they present cutting-edge research results from leading experts

CHORUS Deliverable 2.1: State of the Art on Multimedia Search Engines

Based on the information provided by European projects and national initiatives related to multimedia search as well as domains experts that participated in the CHORUS Think-thanks and workshops, this document reports on the state of the art related to multimedia content search from, a technical, and socio-economic perspective. The technical perspective includes an up to date view on content based indexing and retrieval technologies, multimedia search in the context of mobile devices and peer-to-peer networks, and an overview of current evaluation and benchmark inititiatives to measure the performance of multimedia search engines. From a socio-economic perspective we inventorize the impact and legal consequences of these technical advances and point out future directions of research

Ecology and Management of Stink Bugs (Hemiptera: Pentatomidae) in Southeastern Farmscapes

A three-year study (2009-2011) was conducted to examine the spatial and temporal dynamics of stink bugs in three commercial farmscapes in South Carolina and Georgia. Crops included wheat, Triticum aestivum (L.), corn, Zea mays (L.), soybean, Glycine max (L.), cotton, Gossypium hirsutum (L.), and peanuts, Arachis hypogaea (L.). Farmscapes were sampled weekly using whole-plant examinations for corn, with all other crops sampled using sweep nets. The predominant pest species of phytophagous stink bugs were the brown stink bug, Euschistus servus (Say), the green stink bug, Chinavia hilaris (Say), and the southern green stink bug, Nezara viridula (L.). Chi-square tests indicated a departure from a normal distribution in 77% of analyses of the variance to mean ratio, with 37% of slopes of Taylor\u27s power law and 30% of coefficient β of Iwao\u27s patchiness regression significantly greater than one, indicating aggregated distributions. SADIE indices indicated aggregated patterns of stink bugs in 18% of year-end totals and 42% of weekly counts, with 80% of adults and nymphs positively associated using the SADIE association tool. Peak stink bug densities were linked to crop phenology, following the fruiting pattern of crops in the farmscape. Stink bugs exhibited higher densities in crops adjacent to soybean in Barnwell and Lee Counties, SC, compared with crops adjacent to corn or fallow areas. Efficacy of applications of insecticide limited to the borders of fields to mitigate injury by stink bugs in cotton was evaluated from 2007 to 2011 in South Carolina and Georgia. Stink bug densities and boll injury were greater around the exterior compared with the interior portions of fields based on ANOVA models and interpolation maps of SADIE aggregation indices. Border and whole-field applications had no significant effect (P \u3e 0.05) on average numbers of stink bugs, but boll injury was significantly lower (P \u3c 0.05) in both border and whole-field insecticide treatments compared with untreated controls. No significant difference (P \u3e 0.05) was found between injury levels in fields receiving border or whole-field treatments. Fields receiving no insecticide treatments exceeded economic thresholds 55% of the time. Fields receiving whole-field and border applications of insecticide exceeded thresholds 41% and 30% of the time, respectively. Treated area was 4.4-fold smaller in fields receiving border applications than in fields receiving whole-field applications, indicating substantial savings in insecticide. Results suggested that border treatments of insecticides provided protection from stink bug injury similar to whole-field insecticide treatments, but with considerable savings in application costs. Studies of stink bugs in the field could be improved if movement could be monitored in real time. Harmonic radar tagging was investigated as a method for monitoring the movement of N. viridula. Because adhesive toxicity and tag weight limit the use of this technology, initial efforts focused on selection of the optimal adhesive and design of harmonic radar tags to reduce influence on movement of stink bugs. A design consisting of a 6-cm long 0.10-mm thick silver-plated copper monopole on the anode terminal of a three-contact Schottky barrier diode attached with a rubberized cyanoacrylate (Gorilla super glue) provided a compromise between unimpaired movement and tracking range, adding an additional 8% to the weight of the stink bug while not significantly (P \u3e 0.05) reducing walking or flying mobility in the laboratory. Recovery of tagged stink bugs in cotton and fallow fields ranged from 10-75% after 24 hours, while marked stink bugs were recovered at rates of 0-35% using sweep-net or drop-cloth sampling. The distance dispersed in the field was not influenced (P \u3e 0.05) by crop, tagged status, or gender of the insect. Future research should examine improvements to the harmonic radar transceiver and the wire antenna to decrease encumbrance. Laboratory studies were conducted to determine host preference of the tachinid parasitoid fly Trichopoda pennipes (F.) for E. servus and N. viridula. In choice and no-choice tests, 8-fold fewer eggs were laid on E. servus, compared with N. viridula. Twenty-four T. pennipes emerged from 100 N. viridula, whereas only two larvae emerged from 100 laboratory-parasitized E. servus. Post-mortem dissections of egg-bearing stink bugs without larval emergence revealed 20 T. pennipes larvae inside N. viridula but only one inside E. servus. These results confirmed that T. pennipes prefers N. viridula as a host and is likely an infrequent parasitoid of E. servus. While gathering T. pennipes for the selection trials, Cylindromyia euchenor (Walker), previously found in E. servus, was collected. Unlike most tachinids, which deposit eggs on or near the hosts, members of the genus Cylindromyia have an ovipositor formed from an abdominal sternite, which, assisted by serrated curved claspers, implants eggs directly into hosts. No research has been done on the behavior or host preferences of C. euchenor. My observations were limited to three females over approximately two weeks. Female parasitoids directly injected eggs into E. servus exclusively, ignoring N. viridula. The sequence of oviposition was recorded and described, demonstrating the ovipositional behavior for the first time and indicating a host preference for E. servus

Local user mapping via multi-modal fusion for social robots

User detection, recognition and tracking is at the heart of Human Robot Interaction, and yet, to date, no universal robust method exists for being aware of the people in a robot surroundings. The presented work aims at importing into existing social robotics platforms different techniques, some of them classical, and other novel, for detecting, recognizing and tracking human users. These algorithms are based on a variety of sensors, mainly cameras and depth imaging devices, but also lasers and microphones. The results of these parallel algorithms are then merged so as to obtain a modular, expandable and fast architecture. This results in a local user mapping thanks to multi-modal fusion. Thanks to this user awareness architecture, user detection, recognition and tracking capabilities can be easily and quickly given to any robot by re-using the modules that match its sensors and its processing performance. The architecture provides all the relevant information about the users around the robot, that can then be used for end-user applications that adapt their behavior to the users around the robot. The variety of social robots in which the architecture has been successfully implemented includes a car-like mobile robot, an articulated flower and a humanoid assistance robot. Some modules of the architecture are very lightweight but have a low reliability, others need more CPU but the associated confidence is higher. All configurations of modules are possible, and fit the range of possible robotics hardware configurations. All the modules are independent and highly configurable, therefore no code needs to be developed for building a new configuration, the user only writes a ROS launch file. This simple text file contains all wanted modules. The architecture has been developed with modularity and speed in mind. It is based on the Robot Operating System (ROS) architecture, a de facto software standard in robotics. The different people detectors comply with a common interface called PeoplePoseList Publisher, while the people recognition algorithms comply with an interface called PeoplePoseList Matcher. The fusion of all these different modules is based on Unscented Kalman Filter techniques. Extensive benchmarks of the sub-components and of the whole architecture, using both academic datasets and data acquired in our lab, and end-user application samples demonstrate the validity and interest of all levels of the architecture.La detección, el reconocimiento y el seguimiento de los usuarios es un problema clave para la Interacción Humano-Robot. Sin embargo, al día de hoy, no existe ningún método robusto universal para para lograr que un robot sea consciente de la gente que le rodea. Esta tesis tiene como objetivo implementar, dentro de robots sociales, varias técnicas, algunas clásicas, otras novedosas, para detectar, reconocer y seguir a los usuarios humanos. Estos algoritmos se basan en sensores muy variados, principalmente cámaras y fuentes de imágenes de profundidad, aunque también en láseres y micrófonos. Los resultados parciales, suministrados por estos algoritmos corriendo en paralelo, luego son mezcladas usando técnicas probabilísticas para obtener una arquitectura modular, extensible y rápida. Esto resulta en un mapa local de los usuarios, obtenido por técnicas de fusión de datos. Gracias a esta arquitectura, las habilidades de detección, reconocimiento y seguimiento de los usuarios podrían ser integradas fácil y rápidamente dentro de un nuevo robot, reusando los módulos que corresponden a sus sensores y el rendimiento de su procesador. La arquitectura suministra todos los datos útiles sobre los usuarios en el alrededor del robot y se puede usar por aplicaciones de más alto nivel en nuestros robots sociales de manera que el robot adapte su funcionamiento a las personas que le rodean. Los robots sociales en los cuales la arquitectura se pudo importar con éxito son: un robot en forma de coche, una flor articulada, y un robot humanoide asistencial. Algunos módulos de la arquitectura son muy ligeros pero con una fiabilidad baja, mientras otros requieren más CPU pero son más fiables. Todas las configuraciones de los módulos son posibles y se ajustan a las diferentes configuraciones hardware que puede tener el robot. Los módulos son independientes entre ellos y altamente configurables, por lo que no hay que desarrollar código para una nueva configuración. El usuario sólo tiene que escribir un fichero launch de ROS. Este sencillo fichero de texto contiene todos los módulos que se quieren lanzar. Esta arquitectura se desarrolló teniendo en mente que fuese modular y rápida. Se basa en la arquitectura Robot Operating System (ROS), un estándar software de facto en la robótica. Todos los detectores de personas tienen una interfaz común llamada PeoplePoseList Publisher, mientras los algoritmos de reconocimiento siguen una interfaz llamada PeoplePoseList Matcher. La fusión de todos estos módulos se basa en técnicas de filtros de Kalman no lineares (Unscented Kalman Filters). Se han realizado pruebas exhaustivas de precisión y de velocidad de cada componente y de la arquitectura completa (realizadas sobre ambos bases de datos académicas además de sobre datos grabados en nuestro laboratorio), así como prototipos sencillos de aplicaciones finales. Así se comprueba la validez y el interés de la arquitectura a todos los niveles.Programa Oficial de Doctorado en Ingeniería Eléctrica, Electrónica y AutomáticaPresidente: Fernando Torres Medina.- Secretario: María Dolores Blanco Rojas.- Vocal: Jorge Manuel Miranda Día

Automated Semantic Understanding of Human Emotions in Writing and Speech

Affective Human Computer Interaction (A-HCI) will be critical for the success of new technologies that will prevalent in the 21st century. If cell phones and the internet are any indication, there will be continued rapid development of automated assistive systems that help humans to live better, more productive lives. These will not be just passive systems such as cell phones, but active assistive systems like robot aides in use in hospitals, homes, entertainment room, office, and other work environments. Such systems will need to be able to properly deduce human emotional state before they determine how to best interact with people. This dissertation explores and extends the body of knowledge related to Affective HCI. New semantic methodologies are developed and studied for reliable and accurate detection of human emotional states and magnitudes in written and spoken speech; and for mapping emotional states and magnitudes to 3-D facial expression outputs. The automatic detection of affect in language is based on natural language processing and machine learning approaches. Two affect corpora were developed to perform this analysis. Emotion classification is performed at the sentence level using a step-wise approach which incorporates sentiment flow and sentiment composition features. For emotion magnitude estimation, a regression model was developed to predict evolving emotional magnitude of actors. Emotional magnitudes at any point during a story or conversation are determined by 1) previous emotional state magnitude; 2) new text and speech inputs that might act upon that state; and 3) information about the context the actors are in. Acoustic features are also used to capture additional information from the speech signal. Evaluation of the automatic understanding of affect is performed by testing the model on a testing subset of the newly extended corpus. To visualize actor emotions as perceived by the system, a methodology was also developed to map predicted emotion class magnitudes to 3-D facial parameters using vertex-level mesh morphing. The developed sentence level emotion state detection approach achieved classification accuracies as high as 71% for the neutral vs. emotion classification task in a test corpus of children’s stories. After class re-sampling, the results of the step-wise classification methodology on a test sub-set of a medical drama corpus achieved accuracies in the 56% to 84% range for each emotion class and polarity. For emotion magnitude prediction, the developed recurrent (prior-state feedback) regression model using both text-based and acoustic based features achieved correlation coefficients in the range of 0.69 to 0.80. This prediction function was modeled using a non-linear approach based on Support Vector Regression (SVR) and performed better than other approaches based on Linear Regression or Artificial Neural Networks

Semantic discovery and reuse of business process patterns

Patterns currently play an important role in modern information systems (IS) development and their use has mainly been restricted to the design and implementation phases of the development lifecycle. Given the increasing significance of business modelling in IS development, patterns have the potential of providing a viable solution for promoting reusability of recurrent generalized models in the very early stages of development. As a statement of research-in-progress this paper focuses on business process patterns and proposes an initial methodological framework for the discovery and reuse of business process patterns within the IS development lifecycle. The framework borrows ideas from the domain engineering literature and proposes the use of semantics to drive both the discovery of patterns as well as their reuse

Modern Telemetry

Telemetry is based on knowledge of various disciplines like Electronics, Measurement, Control and Communication along with their combination. This fact leads to a need of studying and understanding of these principles before the usage of Telemetry on selected problem solving. Spending time is however many times returned in form of obtained data or knowledge which telemetry system can provide. Usage of telemetry can be found in many areas from military through biomedical to real medical applications. Modern way to create a wireless sensors remotely connected to central system with artificial intelligence provide many new, sometimes unusual ways to get a knowledge about remote objects behaviour. This book is intended to present some new up to date accesses to telemetry problems solving by use of new sensors conceptions, new wireless transfer or communication techniques, data collection or processing techniques as well as several real use case scenarios describing model examples. Most of book chapters deals with many real cases of telemetry issues which can be used as a cookbooks for your own telemetry related problems