Detecting single-target changes in multiple object tracking: The case of peripheral vision

In the current study it is investigated whether peripheral vision can be used to monitor multi-ple moving objects and to detect single-target changes. For this purpose, in Experiment 1, a modified MOT setup with a large projection and a constant-position centroid phase had to be checked first. Classical findings regarding the use of a virtual centroid to track multiple ob-jects and the dependency of tracking accuracy on target speed could be successfully replicat-ed. Thereafter, the main experimental variations regarding the manipulation of to-be-detected target changes could be introduced in Experiment 2. In addition to a button press used for the detection task, gaze behavior was assessed using an integrated eye-tracking system. The anal-ysis of saccadic reaction times in relation to the motor response shows that peripheral vision is naturally used to detect motion and form changes in MOT because the saccade to the target occurred after target-change offset. Furthermore, for changes of comparable task difficulties, motion changes are detected better by peripheral vision than form changes. Findings indicate that capabilities of the visual system (e.g., visual acuity) affect change detection rates and that covert-attention processes may be affected by vision-related aspects like spatial uncertainty. Moreover, it is argued that a centroid-MOT strategy might reduce the amount of saccade-related costs and that eye-tracking seems to be generally valuable to test predictions derived from theories on MOT. Finally, implications for testing covert attention in applied settings are proposed.

Properties of seawater and particulate matter (fluorescence) from a WETLabs Eco-FL sensor mounted on the continuous surface water sampling system during the Tara Oceans expedition 2009-2013

The Tara Oceans Expedition (2009-2013) sampled the world oceans on board a 36 m long schooner, collecting environmental data and organisms from viruses to planktonic metazoans for later analyses using modern sequencing and state-of-the-art imaging technologies. Tara Oceans Data are particularly suited to study the genetic, morphological and functional diversity of plankton. The present data set provides continuous measurements made with a WETLabs Eco-FL sensor mounted on the flowthrough system between June 4th, 2011 and March 30th, 2012. Data was recorded approximately every 10s. Two issues affected the data: 1. Periods when the water 0.2µm filtered water were used as blanks and 2. Periods where fluorescence was affected by non-photochemical quenching (NPQ, chlorophyll fluorescence is reduced when cells are exposed to light, e.g. Falkowski and Raven, 1997). Median data and their standard deviation were binned to 5min bins with period of light/dark indicated by an added variable (so that NPQ affected data could be neglected if the user so chooses). Data was first calibrated using HPLC data collected on the Tara (there were 36 data within 30min of each other). Fewer were available when there was no evident NPQ and the resulting scale factor was 0.0106 mg Chl m-3/count. To increase the calibration match-ups we used the AC-S data which provided a robust estimate of Chlorophyll (e.g. Boss et al., 2013). Scale factor computed over a much larger range of values than HPLC was 0.0088 mg Chl m-3/count (compared to 0.0079 mg Chl m-3/count based on manufacturer). In the archived data the fluorometer data is merged with the TSG, raw data is provided as well as manufacturer calibration constants, blank computed from filtered measurements and chlorophyll calibrated using the AC-S. For a full description of the processing of the Eco-FL please see Taillandier, 2015.

Upper Limb Portable Motion Analysis System Based on Inertial Technology for Neurorehabilitation Purposes

Here an inertial sensor-based monitoring system for measuring and analyzing upper limb movements is presented. The final goal is the integration of this motion-tracking device within a portable rehabilitation system for brain injury patients. A set of four inertial sensors mounted on a special garment worn by the patient provides the quaternions representing the patient upper limb’s orientation in space. A kinematic model is built to estimate 3D upper limb motion for accurate therapeutic evaluation. The human upper limb is represented as a kinematic chain of rigid bodies with three joints and six degrees of freedom. Validation of the system has been performed by co-registration of movements with a commercial optoelectronic tracking system. Successful results are shown that exhibit a high correlation among signals provided by both devices and obtained at the Institut Guttmann Neurorehabilitation Hospital.

A UGV Navigation System for Large Outdoor Environments Including Virtual Obstacles for No-Go Zones

This work presents a navigation system for UGVs in large outdoor environments; virtual obstacles are added to the system in order to avoid zones that may present risks to the UGV or the elements in its surroundings. The platform, software architecture and the modifications necessary to handle the virtual obstacles are explained in detail. Several tests have been performed and their results show that the system proposed is capable of performing safe navigation in complex environments.

Detection and Tracking of Dynamic Objects. A MultiRobot approach to Critical Infrastructures Surveillance.

Despite that Critical Infrastructures (CIs) security and surveillance are a growing concern for many countries and companies, Multi Robot Systems (MRSs) have not been yet broadly used in this type of facilities. This dissertation presents a novel study of the challenges arisen by the implementation of this type of systems and proposes solutions to specific problems. First, a comprehensive analysis of different types of CIs has been carried out, emphasizing the influence of the different characteristics of the facilities in the design of a security and surveillance MRS. One of the most important needs for the surveillance of a CI is the detection of intruders. From a technical point of view this problem can be abstracted as equivalent to the Detection and Tracking of Mobile Objects (DATMO). This dissertation proposes algorithms to solve this specific problem in a CI environment. Using 3D range images of the environment as input data, two detection algorithms for ground robots have been developed. These detection algorithms provide a list of moving objects in the robot detection area. Direct image differentiation and computer vision techniques are used when the robot is static. Alternatively, multi-layer ground reconstructions are compared to detect the dynamic objects when the robot is moving. Since CIs usually spread over large areas, it is very useful to incorporate aerial vehicles in the surveillance MRS. Therefore, a moving object detection algorithm for aerial vehicles has been also developed. This algorithm compares the real optical flow obtained from a down-face oriented camera with an artificial optical flow computed using a RANSAC based homography matrix. Two tracking algorithms have been developed to follow the moving objects trajectories. These algorithms can efficiently handle occlusions and crossings, as well as exchange information among robots. The multirobot tracking can be applied to any type of communication structure: centralized, decentralized or a combination of both. Even more, the developed tracking algorithms are independent of the detection algorithms and could be potentially used with other detection procedures or even with static sensors, such as cameras. In addition, using the 3D point clouds available to the robots, a relative localization algorithm has been developed to improve the position estimation of a given robot with observations from other robots. All the developed algorithms have been extensively tested in different simulated CIs using the Webots robotics simulator. Furthermore, the algorithms have also been validated with real robots operating in real scenarios. In conclusion, this dissertation presents a multirobot approach to Critical Infrastructure Surveillance, mainly focusing on Detecting and Tracking Dynamic Objects.

Resolution limits to object tracking with subpixel accuracy

Subpixel methods increase the accuracy and efficiency of image detectors, processing units, and algorithms and provide very cost-effective systems for object tracking. Published methods achieve resolution increases up to three orders of magnitude. In this Letter, we demonstrate that this limit can be theoretically improved by several orders of magnitude, permitting micropixel and submicropixel accuracies. The necessary condition for movement detection is that one single pixel changes its status. We show that an appropriate target design increases the probability of a pixel change for arbitrarily small shifts, thus increasing the detection accuracy of a tracking system. The proposal does not impose severe restriction on the target nor on the sensor, thus allowing easy experimental implementation.

Novel online data cleaning protocols for data streams in trajectory, Wireless Sensor Networks

The promise of Wireless Sensor Networks (WSNs) is the autonomous collaboration of a collection of sensors to accomplish some specific goals which a single sensor cannot offer. Basically, sensor networking serves a range of applications by providing the raw data as fundamentals for further analyses and actions. The imprecision of the collected data could tremendously mislead the decision-making process of sensor-based applications, resulting in an ineffectiveness or failure of the application objectives. Due to inherent WSN characteristics normally spoiling the raw sensor readings, many research efforts attempt to improve the accuracy of the corrupted or "dirty" sensor data. The dirty data need to be cleaned or corrected. However, the developed data cleaning solutions restrict themselves to the scope of static WSNs where deployed sensors would rarely move during the operation. Nowadays, many emerging applications relying on WSNs need the sensor mobility to enhance the application efficiency and usage flexibility. The location of deployed sensors needs to be dynamic. Also, each sensor would independently function and contribute its resources. Sensors equipped with vehicles for monitoring the traffic condition could be depicted as one of the prospective examples. The sensor mobility causes a transient in network topology and correlation among sensor streams. Based on static relationships among sensors, the existing methods for cleaning sensor data in static WSNs are invalid in such mobile scenarios. Therefore, a solution of data cleaning that considers the sensor movements is actively needed. This dissertation aims to improve the quality of sensor data by considering the consequences of various trajectory relationships of autonomous mobile sensors in the system. First of all, we address the dynamic network topology due to sensor mobility. The concept of virtual sensor is presented and used for spatio-temporal selection of neighboring sensors to help in cleaning sensor data streams. This method is one of the first methods to clean data in mobile sensor environments. We also study the mobility pattern of moving sensors relative to boundaries of sub-areas of interest. We developed a belief-based analysis to determine the reliable sets of neighboring sensors to improve the cleaning performance, especially when node density is relatively low. Finally, we design a novel sketch-based technique to clean data from internal sensors where spatio-temporal relationships among sensors cannot lead to the data correlations among sensor streams.

The framework of the virtual laser tracker - A systematic approach to the assessment of error sources and uncertainty in laser tracker measurement

Laser trackers have been widely used in many industries to meet increasingly high accuracy requirements. In laser tracker measurement, it is complex and difficult to perform an accurate error analysis and uncertainty evaluation. This paper firstly reviews the working principle of single beam laser trackers and state-of- The- Art of key technologies from both industrial and academic efforts, followed by a comprehensive analysis of uncertainty sources. A generic laser tracker modelling method is formulated and the framework of the virtual tracker is proposed. The VLS can be used for measurement planning, measurement accuracy optimization and uncertainty evaluation. The completed virtual laser tracking system should take all the uncertainty sources affecting coordinate measurement into consideration and establish an uncertainty model which will behave in an identical way to the real system. © Springer-Verlag Berlin Heidelberg 2010.

Thermal Tracking and Estimation for Microprocessors

Due to increasing integration density and operating frequency of today's high performance processors, the temperature of a typical chip can easily exceed 100 degrees Celsius. However, the runtime thermal state of a chip is very hard to predict and manage due to the random nature in computing workloads, as well as the process, voltage and ambient temperature variability (together called PVT variability). The uneven nature (both in time and space) of the heat dissipation of the chip could lead to severe reliability issues and error-prone chip behavior (e.g. timing errors). Many dynamic power/thermal management techniques have been proposed to address this issue such as dynamic voltage and frequency scaling (DVFS), clock gating and etc. However, most of such techniques require accurate knowledge of the runtime thermal state of the chip to make efficient and effective control decisions. In this work we address the problem of tracking and managing the temperature of microprocessors which include the following sub-problems: (1) how to design an efficient sensor-based thermal tracking system on a given design that could provide accurate real-time temperature feedback; (2) what statistical techniques could be used to estimate the full-chip thermal profile based on very limited (and possibly noise-corrupted) sensor observations; (3) how do we adapt to changes in the underlying system's behavior, since such changes could impact the accuracy of our thermal estimation. The thermal tracking methodology proposed in this work is enabled by on-chip sensors which are already implemented in many modern processors. We first investigate the underlying relationship between heat distribution and power consumption, then we introduce an accurate thermal model for the chip system. Based on this model, we characterize the temperature correlation that exists among different chip modules and explore statistical approaches (such as those based on Kalman filter) that could utilize such correlation to estimate the accurate chip-level thermal profiles in real time. Such estimation is performed based on limited sensor information because sensors are usually resource constrained and noise-corrupted. We also took a further step to extend the standard Kalman filter approach to account for (1) nonlinear effects such as leakage-temperature interdependency and (2) varying statistical characteristics in the underlying system model. The proposed thermal tracking infrastructure and estimation algorithms could consistently generate accurate thermal estimates even when the system is switching among workloads that have very distinct characteristics. Through experiments, our approaches have demonstrated promising results with much higher accuracy compared to existing approaches. Such results can be used to ensure thermal reliability and improve the effectiveness of dynamic thermal management techniques.

Radiação Solar: Estudo e criação de plataforma de apoio a conceção de um sensor de radiação solar

Este trabalho introduz a teoria da instrumentação virtual descrevendo os principais componentes desta. É detalhada a implementação de um instrumento virtual e uma base de dados associada que permitem obter uma estimativa de variáveis ambientais para qualquer ponto do globo e qualquer altura do ano. Este instrumento - Environment simulator – permite fornecer dados ambientais necessários a simulação da radiação solar. Para explicar a implementação da plataforma de apoio introduzem-se noções relativas à radiação solar, à relação entre o planeta Terra e o sol. É considerada a radiação solar espectral bem como os principais componentes óticos atmosféricos que com ela interagem. Apresentam-se formulações e aproximações dos coeficientes de extinção e dispersão na atmosfera que levam ao cálculo da radiação solar espectral direta, difusa e global. Por fim, validam-se os resultados através da comparação com valores registados durante a campanha de observações ALEX2014.

Flow injection analysis of paracetamol using a biomimetic sensor as a sensitive and selective amperometric detector

This work describes the coupling of a biomimetic sensor to a flow injection system for the sensitive determination of paracetamol. The sensor was prepared as previously described in the literature (M. D. P. T. Sotomayor, A. Sigoli, M. R. V. Lanza, A. A. Tanaka and L. T. Kubota, J. Braz. Chem. Soc., 2008, 19, 734) by modifying a glassy carbon electrode surface with a Nafion (R) membrane doped with iron tetrapyridinoporphyrazine (FeTPyPz), a biomimetic catalyst of the P450 enzyme. The performance of the sensor for paracetamol detection was investigated and optimized in a flow injection system (FIA) using a wall jet electrochemical cell. Under optimized conditions a wide linear response range (1.0 x 10(-5) to 5.0 x 10(-2) mol L(-1)) was obtained, with a sensitivity of 2579 (+/- 129) mu A L mu mol(-1). The detection and quantification limits of the sensor for paracetamol in the FIA system were 1.0 and 3.5 mu mol L(-1), respectively. The analytical frequency was 51 samples h(-1), and over a period of five days (320 determinations) the biosensor maintained practically the same response. The system was successfully applied to paracetamol quantification in seven pharmaceutical formulations and in water samples from six rivers in Sao Paulo State, Brazil.

Robust Control of Flight Simulator Motion Base

The purpose of this study is to apply robust inverse dynamics control for a six-degree-of-freedom flight simulator motion system. From an implementation viewpoint, simplification of the inverse dynamics control law is introduced by assuming control law matrices as constants. The robust control strategy is applied in the outer loop of the inverse dynamic control to counteract the effects of imperfect compensation due this simplification. The control strategy is designed using the Lyapunov stability theory. Forward and inverse kinematics and a full dynamic model of a six-degree-of-freedom motion base driven by electromechanical actuators are briefly presented. A describing function, acceleration step response and some maneuvers computed from the washout filter were used to evaluate the performance of the controllers.

Swarm Intelligence applied in synthesis of hunting strategies in a three-dimensional environment

Systems of distributed artificial intelligence can be powerful tools in a wide variety of practical applications. Its most surprising characteristic, the emergent behavior, is also the most answerable for the difficulty in. projecting these systems. This work proposes a tool capable to beget individual strategies for the elements of a multi-agent system and thereof providing to the group means on obtaining wanted results, working in a coordinated and cooperative manner as well. As an application example, a problem was taken as a basis where a predators` group must catch a prey in a three-dimensional continuous ambient. A synthesis of system strategies was implemented of which internal mechanism involves the integration between simulators by Particle Swarm Optimization algorithm (PSO), a Swarm Intelligence technique. The system had been tested in several simulation settings and it was capable to synthesize automatically successful hunting strategies, substantiating that the developed tool can provide, as long as it works with well-elaborated patterns, satisfactory solutions for problems of complex nature, of difficult resolution starting from analytical approaches. (c) 2007 Elsevier Ltd. All rights reserved.

Cardiovascular Simulator Improvement: Pressure Versus Volume Loop Assessment

This article presents improvement on a physical cardiovascular simulator (PCS) system. Intraventricular pressure versus intraventricular volume (PxV) loop was obtained to evaluate performance of a pulsatile chamber mimicking the human left ventricle. PxV loop shows heart contractility and is normally used to evaluate heart performance. In many heart diseases, the stroke volume decreases because of low heart contractility. This pathological situation must be simulated by the PCS in order to evaluate the assistance provided by a ventricular assist device (VAD). The PCS system is automatically controlled by a computer and is an auxiliary tool for VAD control strategies development. This PCS system is according to a Windkessel model where lumped parameters are used for cardiovascular system analysis. Peripheral resistance, arteries compliance, and fluid inertance are simulated. The simulator has an actuator with a roller screw and brushless direct current motor, and the stroke volume is regulated by the actuator displacement. Internal pressure and volume measurements are monitored to obtain the PxV loop. Left chamber internal pressure is directly obtained by pressure transducer; however, internal volume has been obtained indirectly by using a linear variable differential transformer, which senses the diaphragm displacement. Correlations between the internal volume and diaphragm position are made. LabVIEW integrates these signals and shows the pressure versus internal volume loop. The results that have been obtained from the PCS system show PxV loops at different ventricle elastances, making possible the simulation of pathological situations. A preliminary test with a pulsatile VAD attached to PCS system was made.

Ant colony system based approach to single machine scheduling problems: weighted tardiness scheduling problem

The paper introduces an approach to solve the problem of generating a sequence of jobs that minimizes the total weighted tardiness for a set of jobs to be processed in a single machine. An Ant Colony System based algorithm is validated with benchmark problems available in the OR library. The obtained results were compared with the best available results and were found to be nearer to the optimal. The obtained computational results allowed concluding on their efficiency and effectiveness.