Prospectives of monitoring biological activity in a red-legged partridge incubator with a carbon dioxide probe

This study focuses on the relationship between CO2 production and the ultimate hatchability of the incubation. A total amount of 43316 eggs of red-legged partridge (Alectoris rufa) were supervised during five actual incubations: three in 2012 and two in 2013. The CO2 concentration inside the incubator was monitored over a 20-day period, showing sigmoidal growth from ambient level (428 ppm) up to 1700 ppm in the incubation with the highest hatchability. Two sigmoid growth models (logistic and Gompertz) were used to describe the CO2 production by the eggs, with the result that the logistic model was a slightly better fit (r2=0.976 compared to r2=0.9746 for Gompertz). A coefficient of determination of 0.997 between the final CO2 estimation (ppm) using the logistic model and hatchability (%) was found.

A Model-Based Monitoring Architecture for Heterogeneous Enterprise Services and Information Systems

Runtime management of distributed information systems is a complex and costly activity. One of the main challenges that must be addressed is obtaining a complete and updated view of all the managed runtime resources. This article presents a monitoring architecture for heterogeneous and distributed information systems. It is composed of two elements: an information model and an agent infrastructure. The model negates the complexity and variability of these systems and enables the abstraction over non-relevant details. The infrastructure uses this information model to monitor and manage the modeled environment, performing and detecting changes in execution time. The agents infrastructure is further detailed and its components and the relationships between them are explained. Moreover, the proposal is validated through a set of agents that instrument the JEE Glassfish application server, paying special attention to support distributed configuration scenarios.

A Light-Weight On-Chip Monitoring Network for Dynamic Adaptation and Calibration

Current nanometer technologies suffer within-die parameter uncertainties, varying workload conditions, aging, and temperature effects that cause a serious reduction on yield and performance. In this scenario, monitoring, calibration, and dynamic adaptation become essential, demanding systems with a collection of multi purpose monitors and exposing the need for light-weight monitoring networks. This paper presents a new monitoring network paradigm able to perform an early prioritization of the information. This is achieved by the introduction of a new hierarchy level, the threshing level. Targeting it, we propose a time-domain signaling scheme over a single-wire that minimizes the network switching activity as well as the routing requirements. To validate our approach, we make a thorough analysis of the architectural trade-offs and expose two complete monitoring systems that suppose an area improvement of 40% and a power reduction of three orders of magnitude compared to previous works.

On the monitoring of surface displacement in connection with volcano reactivation in Tenerife, Canary Islands, using space techniques

Geodetic volcano monitoring in Tenerife has mainly focused on the Las Cañadas Caldera, where a geodetic micronetwork and a levelling profile are located. A sensitivity test of this geodetic network showed that it should be extended to cover the whole island for volcano monitoring purposes. Furthermore, InSAR allowed detecting two unexpected movements that were beyond the scope of the traditional geodetic network. These two facts prompted us to design and observe a GPS network covering the whole of Tenerife that was monitored in August 2000. The results obtained were accurate to one centimetre, and confirm one of the deformations, although they were not definitive enough to confirm the second one. Furthermore, new cases of possible subsidence have been detected in areas where InSAR could not be used to measure deformation due to low coherence. A first modelling attempt has been made using a very simple model and its results seem to indicate that the deformation observed and the groundwater level variation in the island may be related. Future observations will be necessary for further validation and to study the time evolution of the displacements, carry out interpretation work using different types of data (gravity, gases, etc) and develop models that represent the island more closely. The results obtained are important because they might affect the geodetic volcano monitoring on the island, which will only be really useful if it is capable of distinguishing between displacements that might be linked to volcanic activity and those produced by other causes. One important result in this work is that a new geodetic monitoring system based on two complementary techniques, InSAR and GPS, has been set up on Tenerife island. This the first time that the whole surface of any of the volcanic Canary Islands has been covered with a single network for this purpose. This research has displayed the need for further similar studies in the Canary Islands, at least on the islands which pose a greater risk of volcanic reactivation, such as Lanzarote and La Palma, where InSAR techniques have been used already.

Statistical Machine Learning for Automatic Assessment of Physical Activity Intensity Using Multi-axial Accelerometry and Heart Rate

This work explores the automatic recognition of physical activity intensity patterns from multi-axial accelerometry and heart rate signals. Data collection was carried out in free-living conditions and in three controlled gymnasium circuits, for a total amount of 179.80 h of data divided into: sedentary situations (65.5%), light-to-moderate activity (17.6%) and vigorous exercise (16.9%). The proposed machine learning algorithms comprise the following steps: time-domain feature definition, standardization and PCA projection, unsupervised clustering (by k-means and GMM) and a HMM to account for long-term temporal trends. Performance was evaluated by 30 runs of a 10-fold cross-validation. Both k-means and GMM-based approaches yielded high overall accuracy (86.97% and 85.03%, respectively) and, given the imbalance of the dataset, meritorious F-measures (up to 77.88%) for non-sedentary cases. Classification errors tended to be concentrated around transients, what constrains their practical impact. Hence, we consider our proposal to be suitable for 24 h-based monitoring of physical activity in ambulatory scenarios and a first step towards intensity-specific energy expenditure estimators

On-Chip Thermal Monitoring: Design, Placement and Interconnection of Temperature Sensors

La temperatura es una preocupación que juega un papel protagonista en el diseño de circuitos integrados modernos. El importante aumento de las densidades de potencia que conllevan las últimas generaciones tecnológicas ha producido la aparición de gradientes térmicos y puntos calientes durante el funcionamiento normal de los chips. La temperatura tiene un impacto negativo en varios parámetros del circuito integrado como el retardo de las puertas, los gastos de disipación de calor, la fiabilidad, el consumo de energía, etc. Con el fin de luchar contra estos efectos nocivos, la técnicas de gestión dinámica de la temperatura (DTM) adaptan el comportamiento del chip en función en la información que proporciona un sistema de monitorización que mide en tiempo de ejecución la información térmica de la superficie del dado. El campo de la monitorización de la temperatura en el chip ha llamado la atención de la comunidad científica en los últimos años y es el objeto de estudio de esta tesis. Esta tesis aborda la temática de control de la temperatura en el chip desde diferentes perspectivas y niveles, ofreciendo soluciones a algunos de los temas más importantes. Los niveles físico y circuital se cubren con el diseño y la caracterización de dos nuevos sensores de temperatura especialmente diseñados para los propósitos de las técnicas DTM. El primer sensor está basado en un mecanismo que obtiene un pulso de anchura variable dependiente de la relación de las corrientes de fuga con la temperatura. De manera resumida, se carga un nodo del circuito y posteriormente se deja flotando de tal manera que se descarga a través de las corrientes de fugas de un transistor; el tiempo de descarga del nodo es la anchura del pulso. Dado que la anchura del pulso muestra una dependencia exponencial con la temperatura, la conversión a una palabra digital se realiza por medio de un contador logarítmico que realiza tanto la conversión tiempo a digital como la linealización de la salida. La estructura resultante de esta combinación de elementos se implementa en una tecnología de 0,35 _m. El sensor ocupa un área muy reducida, 10.250 nm2, y consume muy poca energía, 1.05-65.5nW a 5 muestras/s, estas cifras superaron todos los trabajos previos en el momento en que se publicó por primera vez y en el momento de la publicación de esta tesis, superan a todas las implementaciones anteriores fabricadas en el mismo nodo tecnológico. En cuanto a la precisión, el sensor ofrece una buena linealidad, incluso sin calibrar; se obtiene un error 3_ de 1,97oC, adecuado para tratar con las aplicaciones de DTM. Como se ha explicado, el sensor es completamente compatible con los procesos de fabricación CMOS, este hecho, junto con sus valores reducidos de área y consumo, lo hacen especialmente adecuado para la integración en un sistema de monitorización de DTM con un conjunto de monitores empotrados distribuidos a través del chip. Las crecientes incertidumbres de proceso asociadas a los últimos nodos tecnológicos comprometen las características de linealidad de nuestra primera propuesta de sensor. Con el objetivo de superar estos problemas, proponemos una nueva técnica para obtener la temperatura. La nueva técnica también está basada en las dependencias térmicas de las corrientes de fuga que se utilizan para descargar un nodo flotante. La novedad es que ahora la medida viene dada por el cociente de dos medidas diferentes, en una de las cuales se altera una característica del transistor de descarga |la tensión de puerta. Este cociente resulta ser muy robusto frente a variaciones de proceso y, además, la linealidad obtenida cumple ampliamente los requisitos impuestos por las políticas DTM |error 3_ de 1,17oC considerando variaciones del proceso y calibrando en dos puntos. La implementación de la parte sensora de esta nueva técnica implica varias consideraciones de diseño, tales como la generación de una referencia de tensión independiente de variaciones de proceso, que se analizan en profundidad en la tesis. Para la conversión tiempo-a-digital, se emplea la misma estructura de digitalización que en el primer sensor. Para la implementación física de la parte de digitalización, se ha construido una biblioteca de células estándar completamente nueva orientada a la reducción de área y consumo. El sensor resultante de la unión de todos los bloques se caracteriza por una energía por muestra ultra baja (48-640 pJ) y un área diminuta de 0,0016 mm2, esta cifra mejora todos los trabajos previos. Para probar esta afirmación, se realiza una comparación exhaustiva con más de 40 propuestas de sensores en la literatura científica. Subiendo el nivel de abstracción al sistema, la tercera contribución se centra en el modelado de un sistema de monitorización que consiste de un conjunto de sensores distribuidos por la superficie del chip. Todos los trabajos anteriores de la literatura tienen como objetivo maximizar la precisión del sistema con el mínimo número de monitores. Como novedad, en nuestra propuesta se introducen nuevos parámetros de calidad aparte del número de sensores, también se considera el consumo de energía, la frecuencia de muestreo, los costes de interconexión y la posibilidad de elegir diferentes tipos de monitores. El modelo se introduce en un algoritmo de recocido simulado que recibe la información térmica de un sistema, sus propiedades físicas, limitaciones de área, potencia e interconexión y una colección de tipos de monitor; el algoritmo proporciona el tipo seleccionado de monitor, el número de monitores, su posición y la velocidad de muestreo _optima. Para probar la validez del algoritmo, se presentan varios casos de estudio para el procesador Alpha 21364 considerando distintas restricciones. En comparación con otros trabajos previos en la literatura, el modelo que aquí se presenta es el más completo. Finalmente, la última contribución se dirige al nivel de red, partiendo de un conjunto de monitores de temperatura de posiciones conocidas, nos concentramos en resolver el problema de la conexión de los sensores de una forma eficiente en área y consumo. Nuestra primera propuesta en este campo es la introducción de un nuevo nivel en la jerarquía de interconexión, el nivel de trillado (o threshing en inglés), entre los monitores y los buses tradicionales de periféricos. En este nuevo nivel se aplica selectividad de datos para reducir la cantidad de información que se envía al controlador central. La idea detrás de este nuevo nivel es que en este tipo de redes la mayoría de los datos es inútil, porque desde el punto de vista del controlador sólo una pequeña cantidad de datos |normalmente sólo los valores extremos| es de interés. Para cubrir el nuevo nivel, proponemos una red de monitorización mono-conexión que se basa en un esquema de señalización en el dominio de tiempo. Este esquema reduce significativamente tanto la actividad de conmutación sobre la conexión como el consumo de energía de la red. Otra ventaja de este esquema es que los datos de los monitores llegan directamente ordenados al controlador. Si este tipo de señalización se aplica a sensores que realizan conversión tiempo-a-digital, se puede obtener compartición de recursos de digitalización tanto en tiempo como en espacio, lo que supone un importante ahorro de área y consumo. Finalmente, se presentan dos prototipos de sistemas de monitorización completos que de manera significativa superan la características de trabajos anteriores en términos de área y, especialmente, consumo de energía. Abstract Temperature is a first class design concern in modern integrated circuits. The important increase in power densities associated to recent technology evolutions has lead to the apparition of thermal gradients and hot spots during run time operation. Temperature impacts several circuit parameters such as speed, cooling budgets, reliability, power consumption, etc. In order to fight against these negative effects, dynamic thermal management (DTM) techniques adapt the behavior of the chip relying on the information of a monitoring system that provides run-time thermal information of the die surface. The field of on-chip temperature monitoring has drawn the attention of the scientific community in the recent years and is the object of study of this thesis. This thesis approaches the matter of on-chip temperature monitoring from different perspectives and levels, providing solutions to some of the most important issues. The physical and circuital levels are covered with the design and characterization of two novel temperature sensors specially tailored for DTM purposes. The first sensor is based upon a mechanism that obtains a pulse with a varying width based on the variations of the leakage currents on the temperature. In a nutshell, a circuit node is charged and subsequently left floating so that it discharges away through the subthreshold currents of a transistor; the time the node takes to discharge is the width of the pulse. Since the width of the pulse displays an exponential dependence on the temperature, the conversion into a digital word is realized by means of a logarithmic counter that performs both the timeto- digital conversion and the linearization of the output. The structure resulting from this combination of elements is implemented in a 0.35_m technology and is characterized by very reduced area, 10250 nm2, and power consumption, 1.05-65.5 nW at 5 samples/s, these figures outperformed all previous works by the time it was first published and still, by the time of the publication of this thesis, they outnumber all previous implementations in the same technology node. Concerning the accuracy, the sensor exhibits good linearity, even without calibration it displays a 3_ error of 1.97oC, appropriate to deal with DTM applications. As explained, the sensor is completely compatible with standard CMOS processes, this fact, along with its tiny area and power overhead, makes it specially suitable for the integration in a DTM monitoring system with a collection of on-chip monitors distributed across the chip. The exacerbated process fluctuations carried along with recent technology nodes jeop-ardize the linearity characteristics of the first sensor. In order to overcome these problems, a new temperature inferring technique is proposed. In this case, we also rely on the thermal dependencies of leakage currents that are used to discharge a floating node, but now, the result comes from the ratio of two different measures, in one of which we alter a characteristic of the discharging transistor |the gate voltage. This ratio proves to be very robust against process variations and displays a more than suficient linearity on the temperature |1.17oC 3_ error considering process variations and performing two-point calibration. The implementation of the sensing part based on this new technique implies several issues, such as the generation of process variations independent voltage reference, that are analyzed in depth in the thesis. In order to perform the time-to-digital conversion, we employ the same digitization structure the former sensor used. A completely new standard cell library targeting low area and power overhead is built from scratch to implement the digitization part. Putting all the pieces together, we achieve a complete sensor system that is characterized by ultra low energy per conversion of 48-640pJ and area of 0.0016mm2, this figure outperforms all previous works. To prove this statement, we perform a thorough comparison with over 40 works from the scientific literature. Moving up to the system level, the third contribution is centered on the modeling of a monitoring system consisting of set of thermal sensors distributed across the chip. All previous works from the literature target maximizing the accuracy of the system with the minimum number of monitors. In contrast, we introduce new metrics of quality apart form just the number of sensors; we consider the power consumption, the sampling frequency, the possibility to consider different types of monitors and the interconnection costs. The model is introduced in a simulated annealing algorithm that receives the thermal information of a system, its physical properties, area, power and interconnection constraints and a collection of monitor types; the algorithm yields the selected type of monitor, the number of monitors, their position and the optimum sampling rate. We test the algorithm with the Alpha 21364 processor under several constraint configurations to prove its validity. When compared to other previous works in the literature, the modeling presented here is the most complete. Finally, the last contribution targets the networking level, given an allocated set of temperature monitors, we focused on solving the problem of connecting them in an efficient way from the area and power perspectives. Our first proposal in this area is the introduction of a new interconnection hierarchy level, the threshing level, in between the monitors and the traditional peripheral buses that applies data selectivity to reduce the amount of information that is sent to the central controller. The idea behind this new level is that in this kind of networks most data are useless because from the controller viewpoint just a small amount of data |normally extreme values| is of interest. To cover the new interconnection level, we propose a single-wire monitoring network based on a time-domain signaling scheme that significantly reduces both the switching activity over the wire and the power consumption of the network. This scheme codes the information in the time domain and allows a straightforward obtention of an ordered list of values from the maximum to the minimum. If the scheme is applied to monitors that employ TDC, digitization resource sharing is achieved, producing an important saving in area and power consumption. Two prototypes of complete monitoring systems are presented, they significantly overcome previous works in terms of area and, specially, power consumption.

Novel system for bite-force sensing and monitoring based on magnetic eear field communication

Intraoral devices for bite-force sensing have several applications in odontology and maxillofacial surgery, as bite-force measurements provide additional information to help understand the characteristics of bruxism disorders and can also be of help for the evaluation of post-surgical evolution and for comparison of alternative treatments. A new system for measuring human bite forces is proposed in this work. This system has future applications for the monitoring of bruxism events and as a complement for its conventional diagnosis. Bruxism is a pathology consisting of grinding or tight clenching of the upper and lower teeth, which leads to several problems such as lesions to the teeth, headaches, orofacial pain and important disorders of the temporomandibular joint. The prototype uses a magnetic field communication scheme similar to low-frequency radio frequency identification (RFID) technology (NFC). The reader generates a low-frequency magnetic field that is used as the information carrier and powers the sensor. The system is notable because it uses an intra-mouth passive sensor and an external interrogator, which remotely records and processes information regarding a patient?s dental activity. This permits a quantitative assessment of bite-force, without requiring intra-mouth batteries, and can provide supplementary information to polysomnographic recordings, current most adequate early diagnostic method, so as to initiate corrective actions before irreversible dental wear appears. In addition to describing the system?s operational principles and the manufacture of personalized prototypes, this report will also demonstrate the feasibility of the system and results from the first in vitro and in vivo trials.

Monitoring leafy vegetables through packaging films with

Fresh-cut or minimally processed fruit and vegetables have been physically modified from its original form (by peeling, trimming, washing and cutting) to obtain a 100% edible product that is subsequently packaged (usually under modified atmosphere packaging –MAP) and kept in refrigerated storage. In fresh-cut products, physiological activity and microbiological spoilage, determine their deterioration and shelf-life. The major preservation techniques applied to delay spoilage are chilling storage and MAP, combined with chemical treatments antimicrobial solutions antibrowning, acidulants, antioxidants, etc.). The industry looks for safer alternatives. Consequently, the sector is asking for innovative, fast, cheap and objective techniques to evaluate the overall quality and safety of fresh-cut products in order to obtain decision tools for implementing new packaging materials and procedures. In recent years, hyperspectral imaging technique has been regarded as a tool for analyses conducted for quality evaluation of food products in research, control and industries. The hyperspectral imaging system allows integrating spectroscopic and imaging techniques to enable direct identification of different components or quality characteristics and their spatial distribution in the tested sample. The objective of this work is to develop hyperspectral image processing methods for the supervision through plastic films of changes related to quality deterioration in packed readyto-use leafy vegetables during shelf life. The evolutions of ready-to-use spinach and watercress samples covered with three different common transparent plastic films were studied. Samples were stored at 4 ºC during the monitoring period (until 21 days). More than 60 hyperspectral images (from 400 to 1000 nm) per species were analyzed using ad hoc routines and commercial toolboxes of MatLab®. Besides common spectral treatments for removing additive and multiplicative effects, additional correction, previously to any other correction, was performed in the images of leaves in order to avoid the modification in their spectra due to the presence of the plastic transparent film. Findings from this study suggest that the developed images analysis system is able to deal with the effects caused in the images by the presence of plastic films in the supervision of shelf-life in leafy vegetables, in which different stages of quality has been identified.

Combining Wireless Sensor Networks and Semantic Middleware for an Internet of Things-Based Sportsman/Woman Monitoring Application.

Wireless Sensor Networks (WSNs) are spearheading the efforts taken to build and deploy systems aiming to accomplish the ultimate objectives of the Internet of Things. Due to the sensors WSNs nodes are provided with, and to their ubiquity and pervasive capabilities, these networks become extremely suitable for many applications that so-called conventional cabled or wireless networks are unable to handle. One of these still underdeveloped applications is monitoring physical parameters on a person. This is an especially interesting application regarding their age or activity, for any detected hazardous parameter can be notified not only to the monitored person as a warning, but also to any third party that may be helpful under critical circumstances, such as relatives or healthcare centers. We propose a system built to monitor a sportsman/woman during a workout session or performing a sport-related indoor activity. Sensors have been deployed by means of several nodes acting as the nodes of a WSN, along with a semantic middleware development used for hardware complexity abstraction purposes. The data extracted from the environment, combined with the information obtained from the user, will compose the basis of the services that can be obtained.

Atmospheric and remote sensing surveys evaluated at the natural analogue "Campo de Calatrava" and its relation with isotopic Radon activity and CO2 flux as strategy for CCS projects

C0 capture and storage (CCS) projects are presently developed to reduce the emission of anthropogenic co2 into the atmosphere. CCS technologies are expected to account for the 20% of the C0 reduction by 2050.The results of this paper are referred to the OXYCFB300 Compostilla Project (European Energy Program for Recover). Since the detection and control of potential leakage from storage formation is mandatory in a project of capture and geological storage of C02 (CCS), geophysical , ground deformation and geochemical monitoring have been carried out to detect potentialleakage, and, in the event that this occurs, identify and quantify it. This monitoring needs to be developed prior, during and after the injection stage. For a correct interpretation and quantification of the leakage, it is essential to establish a pre-injection characterization (baseline)of the area affected by the C02 storage at reservoir level as well as at shallow depth, surface and atmosphere, via soil gas measurements.

Computer workstation vetting by supply current monitoring

It is our goal within this project to develop a powerful electronic system capable to claim, with high certainty, that a malicious software is running (or not) along with the workstations’ normal activity. The new product will be based on measurement of the supply current taken by a workstation from the grid. Unique technique is proposed within these proceedings that analyses the supply current to produce information about the state of the workstation and to generate information of the presence of malicious software running along with the rightful applications. The testing is based on comparison of the behavior of a fault-free workstation (established i advance) and the behavior of the potentially faulty device.

Human activity recognition by inertial signals obtained from a smartphone

Human Activity Recognition (HAR) is an emerging research field with the aim to identify the actions carried out by a person given a set of observations and the surrounding environment. The wide growth in this research field inside the scientific community is mainly explained by the high number of applications that are arising in the last years. A great part of the most promising applications are related to the healthcare field, where it is possible to track the mobility of patients with motor dysfunction as also the physical activity in patients with cardiovascular risk. Until a few years ago, by using distinct kind of sensors, a patient follow-up was possible. However, far from being a long-term solution and with the smartphone irruption, that monitoring can be achieved in a non-invasive way by using the embedded smartphone’s sensors. For these reasons this Final Degree Project arises with the main target to evaluate new feature extraction techniques in order to carry out an activity and user recognition, and also an activity segmentation. The recognition is done thanks to the inertial signals integration obtained by two widespread sensors in the greater part of smartphones: accelerometer and gyroscope. In particular, six different activities are evaluated walking, walking-upstairs, walking-downstairs, sitting, standing and lying. Furthermore, a segmentation task is carried out taking into account the activities performed by thirty users. This can be done by using Hidden Markov Models and also a set of tools tested satisfactory in speech recognition: HTK (Hidden Markov Model Toolkit).