Tracking Procedure Research Articles

Re-Identification with Pre-Filtering by Image Quality for Multiple Objects Tracking

The paper considers multiple object tracking. Existing methods tend to be either resource-intensive or prone to high object densities errors failing to provide competitive performance at high frame rates without significant tracking disruptions and error accumulation. We formulate the multiple object tracking problem under the assumption of linearity and independence of the movement of objects. The factorization of the posterior distribution of objects' parameters provides proof of the equivalence of the initial problem and the tracking procedure containing two subtasks: track prediction and assignment of measurements and objects. A modification of the assignment cost is introduced to achieve the stability of assignments in challenging scenarios of tracking, such as multiple objects occlusions and missing detections. We consider adding a term that states to re-identification of the candidate by comparing its descriptor with descriptors from the track history. Given that track measurements are not equal in terms of usefulness for re-identification, we introduce the technique of track descriptor pre-filtering based on quality assessment in order to select the most relevant descriptors for re-identification and reduce method algorithmic complexity. Both known quality assessment methods and an alternative detector-based approach are taken into account. Computational experiments were conducted on MOT20-01, MOT20-02 datasets containing CCTVcameras data in order to compare the proposed method with other approaches. The results showed the computational efficiency of the proposed methods and the increased stability of tracking in complex scenarios.

Integrating critical chain project management with last planner system for linear scheduling of modular construction

PurposeThe purpose of this paper is to present a new method for project tracking and control of integrated offsite and onsite activities in modular construction considering practical characteristics associated with this type of construction.Design/methodology/approachThe design embraces building information modelling and integrates last planner system (LPS), linear scheduling method (LSM) and critical chain project management (CCPM) to develop tracking and control procedures for modular construction projects. The developed method accounts for constraints of resources continuity and uncertainties associated with activity duration. Features of proposed method are illustrated in a case example for tracking and control of modular projects.FindingsComparison between developed schedule and Monte Carlo simulation showed that baseline duration generated from simulation exceeds that produced by developed method by 12% and 10% for schedules with 50% and 90% confidence level, respectively. These percentages decrease based on interventions of members of project team in the LPS sessions. The case example results indicate that project is delayed 5% and experienced cost overrun of 2.5%.Originality/valueDeveloped method integrated LPS, LSM and CCPM while using metrics for reliability assessment of linear schedules, namely, critical percent plan complete (PPCcr) and buffer index (BI). PPCcr and BI measure percentage of plan completion for critical activities and buffer consumption, respectively. The developed method provides a systematic procedure for forecasting look-ahead schedules using forecasting correction factor Δt and a newly developed tracking and control procedure that uses PPCcr and BI. Quantitative cost analysis is also provided to forecast and monitor project costs to prove the robustness of proposed framework.

Motion artifacts assessment and correction using optical tracking in synchrotron radiation breast CT.

PurposeThe SYRMA‐3D collaboration is setting up a breast computed tomography (bCT) clinical program at the Elettra synchrotron radiation facility in Trieste, Italy. Unlike the few dedicated scanners available at hospitals, synchrotron radiation bCT requires the patient's rotation, which in turn implies a long scan duration (from tens of seconds to few minutes). At the same time, it allows the achievement of high spatial resolution. These features make synchrotron radiation bCT prone to motion artifacts. This article aims at assessing and compensating for motion artifacts through an optical tracking approach.MethodsIn this study, patients’ movements due to breathing have been first assessed on seven volunteers and then simulated during the CT scans of a breast phantom and a surgical specimen, by adding a periodic oscillatory motion (constant speed, 1 mm amplitude, 12 cycles/minute). CT scans were carried out at 28 keV with a mean glandular dose of 5 mGy. Motion artifacts were evaluated and a correction algorithm based on the optical tracking of fiducial marks was introduced. A quantitative analysis based on the structural similarity (SSIM) index and the normalized mean square error (nMSE) was performed on the reconstructed CT images.ResultsCT images reconstructed through the optical tracking procedure were found to be as good as the motionless reference image. Moreover, the analysis of SSIM and nMSE demonstrated that an uncorrected motion of the order of the system's point spread function (around 0.1 mm in the present case) can be tolerated.ConclusionsResults suggest that a motion correction procedure based on an optical tracking system would be beneficial in synchrotron radiation bCT.

A Motion Artifact Correction Procedure for fNIRS Signals Based on Wavelet Transform and Infrared Thermography Video Tracking.

Functional near infrared spectroscopy (fNIRS) is a neuroimaging technique that allows to monitor the functional hemoglobin oscillations related to cortical activity. One of the main issues related to fNIRS applications is the motion artefact removal, since a corrupted physiological signal is not correctly indicative of the underlying biological process. A novel procedure for motion artifact correction for fNIRS signals based on wavelet transform and video tracking developed for infrared thermography (IRT) is presented. In detail, fNIRS and IRT were concurrently recorded and the optodes’ movement was estimated employing a video tracking procedure developed for IRT recordings. The wavelet transform of the fNIRS signal and of the optodes’ movement, together with their wavelet coherence, were computed. Then, the inverse wavelet transform was evaluated for the fNIRS signal excluding the frequency content corresponding to the optdes’ movement and to the coherence in the epochs where they were higher with respect to an established threshold. The method was tested using simulated functional hemodynamic responses added to real resting-state fNIRS recordings corrupted by movement artifacts. The results demonstrated the effectiveness of the procedure in eliminating noise, producing results with higher signal to noise ratio with respect to another validated method.

Trailer angle estimation using radar point clouds

Algorithms for trailer control and backup need to keep track of the trailer angle, therefore, the angle needs to be determined. This work shows that the angle can be estimated using 2D point clouds collected from two automotive radars installed in the taillight fixtures of a trailer-coupled truck. The detection threshold of each radar is reduced to allow more detections of the trailer. A tracking procedure is introduced to find the trailer detections as the trailer rotates; the tracked set of detections are then compared with one or more reference sets to estimate the angle. Estimated angles are further refined with a Kalman filter to obtain smooth estimates of the angle. The algorithm is tested on 15 datasets; each dataset is obtained in an experiment in which the trailer is rotated up to about 40∘ in both radar directions. The estimates from all the datasets result in a global root mean squared error of about 0.9∘ for up to 10∘ absolute trailer rotation; about 1.3∘ for up to 20∘ absolute rotation; about 1.5∘ for up to 30∘ absolute rotation; and about 1.9∘ for all trailer angles considered. The algorithm executes in about 3 ms on a typical personal computer.

Engaging Sexual and Gender Minority Youth in HIV Interventions Through Gay Dating Apps: Recruitment Protocol.

BackgroundHIV continues to disproportionately impact sexual and gender minority youth (SGMY) in the United States. Public health efforts have increasingly focused on developing efficacious interventions to curb the spread of HIV among SGMY and help those living with HIV achieve and sustain viral suppression. However, recruiting and engaging SGMY in prevention and care interventions is challenging.ObjectiveDuring the past decade, gay dating apps have quickly emerged as popular web-based spaces in which SGMY congregate. Although the recruitment of SGMY through these apps has been commonly reported, advertisement is the typical modality used, and direct recruitment approaches are not adequately described. This study aims to describe the process for developing a direct recruitment protocol for use in gay dating apps.MethodsThe Adolescent Medicine Trials Network Comprehensive Adolescent Research and Engagement Studies is a community-based research program consisting of 3 interrelated studies testing scalable behavioral interventions to improve HIV prevention and care engagement among youth aged 12-24 years in Los Angeles and New Orleans. To supplement our in-person recruitment approaches for Comprehensive Adolescent Research and Engagement Studies, the New Orleans site formed a gay dating app recruitment team. In April 2018, the team developed a loosely structured protocol that included study-specific profiles and sample language to guide initial recruitment efforts. Two self-identified Black, gay cisgender male field recruiters field-tested the protocol on the popular gay dating app Jack’d. During the field test, the recruitment team met weekly to discuss the recruiters’ experiences and user reactions. For example, we learned the importance of addressing concerns about study legitimacy and identifying appropriate ways to describe the study. We iteratively incorporated these lessons learned into the final protocol and developed a training program and tracking procedures before moving to full-scale implementation at both sites.ResultsAdhering to this protocol yielded 162 enrollments in New Orleans (332 total enrollments across the two sites) throughout the recruitment period (April 2018 to August 2019). Most of these participants were sexual minority cisgender males (91%), and the remainder were identified as members of gender minority groups. We outlined step-by-step instructions on training staff, engaging users, and scheduling and tracking recruitment activities.ConclusionsThis paper provides a practical guide for researchers and community-based providers to implement a gay dating app recruitment protocol. Our experience indicates that gay dating app recruitment is feasible and fruitful when the staff members are knowledgeable, flexible, honest, and respectful to the user. Perhaps the most salient lesson we learned in approaching gay dating app users is the importance of setting clear and transparent intentions without judgment. As gay dating apps continue to increase in popularity, researchers need to stay vigilant to changing formats and develop systematic approaches to harness their potential as invaluable recruitment strategies for SGMY.International Registered Report Identifier (IRRID)RR1-10.2196/28864

Electrical stimulation of the external ear acutely activates noradrenergic mechanisms in humans

BackgroundTranscutaneous stimulation of the external ear is thought to recruit afferents of the auricular vagus nerve, providing a means to activate noradrenergic pathways in the central nervous system. Findings from human studies examining the effects of auricular stimulation on noradrenergic biomarkers have been mixed, possibly relating to the limited and variable parameter space explored to date. ObjectiveWe tested the extent to which brief pulse trains applied to locations of auricular innervation (canal and concha) elicit acute pupillary responses (PRs) compared to a sham location (lobe). Pulse amplitude and frequency were varied systematically to examine effects on PR features. MethodsParticipants (n = 19) underwent testing in three separate experiments, each with stimulation applied to a different external ear location. Perceptual threshold (PT) was measured at the beginning of each experiment. Pulse trains (∼600 ms) consisting of different amplitude (0.0xPT, 0.8xPT, 1.0xPT, 1.5xPT, 2.0xPT) and frequency (25 Hz, 300 Hz) combinations were administered during eye tracking procedures. ResultsStimulation to all locations elicited PRs which began approximately halfway through the pulse train and peaked shortly after the final pulse (≤1 s). PR size and incidence increased with pulse amplitude and tended to be greatest with canal stimulation. Higher pulse frequency shortened the latency of PR onset and peak dilation. Changes in pupil diameter elicited by pulse trains were weakly associated with baseline pupil diameter. Conclusion(s): Auricular stimulation elicits acute PRs, providing a basis to synchronize neuromodulator release with task-related neural spiking which preclinical studies show is a critical determinant of therapeutic effects. Further work is needed to dissociate contributions from vagal and non-vagal afferents mediating activation of the biomarker.

AdaMM: Adaptive Object Movement and Motion Tracking in Hierarchical Edge Computing System.

This paper presents a novel adaptive object movement and motion tracking (AdaMM) framework in a hierarchical edge computing system for achieving GPU memory footprint reduction of deep learning (DL)-based video surveillance services. DL-based object movement and motion tracking requires a significant amount of resources, such as (1) GPU processing power for the inference phase and (2) GPU memory for model loading. Despite the absence of an object in the video, if the DL model is loaded, the GPU memory must be kept allocated for the loaded model. Moreover, in several cases, video surveillance tries to capture events that rarely occur (e.g., abnormal object behaviors); therefore, such standby GPU memory might be easily wasted. To alleviate this problem, the proposed AdaMM framework categorizes the tasks used for the object movement and motion tracking procedure in an increasing order of the required processing and memory resources as task (1) frame difference calculation, task (2) object detection, and task (3) object motion and movement tracking. The proposed framework aims to adaptively release the unnecessary standby object motion and movement tracking model to save GPU memory by utilizing light tasks, such as frame difference calculation and object detection in a hierarchical manner. Consequently, object movement and motion tracking are adaptively triggered if the object is detected within the specified threshold time; otherwise, the GPU memory for the model of task (3) can be released. Moreover, object detection is also adaptively performed if the frame difference over time is greater than the specified threshold. We implemented the proposed AdaMM framework using commercial edge devices by considering a three-tier system, such as the 1st edge node for both tasks (1) and (2), the 2nd edge node for task (3), and the cloud for sending a push alarm. A measurement-based experiment reveals that the proposed framework achieves a maximum GPU memory reduction of 76.8% compared to the baseline system, while requiring a 2680 ms delay for loading the model for object movement and motion tracking.

Securing Participant Engagement in Longitudinal Substance Use Disorder Recovery Research: A Qualitative Exploration of Key Retention Factors

The longitudinal cohort study is the gold standard in observational epidemiology. A central challenge with this design is the risk of attrition over time, especially in studies of inaccessible clinical populations, such as individuals with substance use disorder (SUD). Research on individuals who have achieved stable substance use abstinence and functional recovery is scarce. 30 participants from a longitudinal cohort study (the Stayer study), were interviewed concerning their experiences of participation over several years to explore retention factors. Interviewers with first-hand experience of recovery from SUD conducted the interviews. Data were analyzed using a thematic analytic approach within an interpretative–phenomenological framework. The analyses yielded the following themes: (1) Individuals’ substance use: adaptation to slips and relapses in treatment and research, (2) “Show that you care”: Developing working relationships in research with study participants by negotiating expectations flexibly, and (3) “You don’t just make dropouts”: A long-term focus on study participation and treatment can increase retention. Several factors were perceived as relevant to participation in a long-term follow-up study with diverse recovery routes, including working research relationships and explicit contracts allowing follow-up participation, even during periods of drug use. Longitudinal studies could benefit from including such factors in the tracking procedures in addition to more traditional tracking techniques. Clinical services could benefit from developing interventions that use knowledge of long-term recovery processes as non-linear, heterogeneous trajectories, and proactive approaches to motivate recovery.

Track-to-Learn: A general framework for tractography with deep reinforcement learning.

Diffusion MRI tractography is currently the only non-invasive tool able to assess the white-matter structural connectivity of a brain. Since its inception, it has been widely documented that tractography is prone to producing erroneous tracks while missing true positive connections. Recently, supervised learning algorithms have been proposed to learn the tracking procedure implicitly from data, without relying on anatomical priors. However, these methods rely on curated streamlines that are very hard to obtain. To remove the need for such data but still leverage the expressiveness of neural networks, we introduce Track-To-Learn: A general framework to pose tractography as a deep reinforcement learning problem. Deep reinforcement learning is a type of machine learning that does not depend on ground-truth data but rather on the concept of "reward". We implement and train algorithms to maximize returns from a reward function based on the alignment of streamlines with principal directions extracted from diffusion data. We show competitive results on known data and little loss of performance when generalizing to new, unseen data, compared to prior machine learning-based tractography algorithms. To the best of our knowledge, this is the first successful use of deep reinforcement learning for tractography.

Psychophysical Tracking Method to Assess Taste Detection Thresholds in Children, Adolescents, and Adults: The Taste Detection Threshold (TDT) Test

This paper describes a two-alternative, forced-choice, staircase, tracking procedure, called the Taste Detection Threshold (TDT) test, that provides a reliable measure of sweet, salty, and umami taste detection thresholds from childhood to adulthood. Advantages of the method include procedures that are identical for children and adults, thus allowing the determination of age-related and individual differences in taste perception, if any, and tasks that can be completed in a relatively short time frame, do not rely on continuous attention or require memorization, control for subjective response biases, and minimize the impact of language development. After a 1 hour fast, participants are presented with pairs of solutions; in each pair, one solution is water, and the other solution contains varying concentrations of the tastant. Using a whole-mouth tasting method, participants taste each solution (without swallowing and with rinsing between tastings) and then point to the solution with a taste or that tastes different from water. The concentration of the stimulus in the subsequent pair increases after a single incorrect response and decreases after two consecutive correct responses. A reversal occurs when the concentration sequence changes direction. The task is deemed completed after the occurrence of four reversals, provided there are a maximum of two dilution steps between two successive reversals, and the series of reversals do not form an ascending pattern. These additional criteria ensure greater reliability in outcomes. The TDT is then calculated as the geometric mean of the concentrations of the four reversals. This method has real-world relevance as it provides information on a dimension of taste perception that is independent of hedonics, and that can change with aging and certain disease states, making it a valuable psychophysical test.

Psychophysical Tracking Method to Assess Taste Detection Thresholds in Children, Adolescents, and Adults: The Taste Detection Threshold (TDT) Test

This paper describes a two-alternative, forced-choice, staircase, tracking procedure, called the Taste Detection Threshold (TDT) test, that provides a reliable measure of sweet, salty, and umami taste detection thresholds from childhood to adulthood. Advantages of the method include procedures that are identical for children and adults, thus allowing the determination of age-related and individual differences in taste perception, if any, and tasks that can be completed in a relatively short time frame, do not rely on continuous attention or require memorization, control for subjective response biases, and minimize the impact of language development. After a 1 hour fast, participants are presented with pairs of solutions; in each pair, one solution is water, and the other solution contains varying concentrations of the tastant. Using a whole-mouth tasting method, participants taste each solution (without swallowing and with rinsing between tastings) and then point to the solution with a taste or that tastes different from water. The concentration of the stimulus in the subsequent pair increases after a single incorrect response and decreases after two consecutive correct responses. A reversal occurs when the concentration sequence changes direction. The task is deemed completed after the occurrence of four reversals, provided there are a maximum of two dilution steps between two successive reversals, and the series of reversals do not form an ascending pattern. These additional criteria ensure greater reliability in outcomes. The TDT is then calculated as the geometric mean of the concentrations of the four reversals. This method has real-world relevance as it provides information on a dimension of taste perception that is independent of hedonics, and that can change with aging and certain disease states, making it a valuable psychophysical test.

Preventing illegal logging

This paper presents ideas and strategies to prevent illegal logging of timber. Globally, illegal logging is a substantial problem. While the exact amount of timber harvested illegally is unknown, the problem is estimated to cost USD$30–100 billion annually. Criminological theories suggest intervention mechanisms that could either prevent or severely limit illegal logging in the forests. Utilizing situational crime prevention techniques, certain strategies for prevention on the ground include signage indicating boundaries, gates lining access roads, and checkpoint locations. Transparency strategies include remote sensing, wood tracking operation standards and procedures, and independent certification. Additionally, forestry law enforcement, forestry management, and local communities must be encouraged to actively combat the problem of illegal logging.

Does Sentence-Level Coarticulation Affect Speech Recognition in Noise or a Speech Masker?

Purpose Three experiments were conducted to better understand the role of between-word coarticulation in masked speech recognition. Specifically, we explored whether naturally coarticulated sentences supported better masked speech recognition as compared to sentences derived from individually spoken concatenated words. We hypothesized that sentence recognition thresholds (SRTs) would be similar for coarticulated and concatenated sentences in a noise masker but would be better for coarticulated sentences in a speech masker. Method Sixty young adults participated (n = 20 per experiment). An adaptive tracking procedure was used to estimate SRTs in the presence of noise or two-talker speech maskers. Targets in Experiments 1 and 2 were matrix-style sentences, while targets in Experiment 3 were semantically meaningful sentences. All experiments included coarticulated and concatenated targets; Experiments 2 and 3 included a third target type, concatenated keyword-intensity-matched (KIM) sentences, in which the words were concatenated but individually scaled to replicate the intensity contours of the coarticulated sentences. Results Regression analyses evaluated the main effects of target type, masker type, and their interaction. Across all three experiments, effects of target type were small (< 2 dB). In Experiment 1, SRTs were slightly poorer for coarticulated than concatenated sentences. In Experiment 2, coarticulation facilitated speech recognition compared to the concatenated KIM condition. When listeners had access to semantic context (Experiment 3), a coarticulation benefit was observed in noise but not in the speech masker. Conclusions Overall, differences between SRTs for sentences with and without between-word coarticulation were small. Beneficial effects of coarticulation were only observed relative to the concatenated KIM targets; for unscaled concatenated targets, it appeared that consistent audibility across the sentence offsets any benefit of coarticulation. Contrary to our hypothesis, effects of coarticulation generally were not more pronounced in speech maskers than in noise maskers.

Comparing accuracy of fish sperm motility measurements obtained from two computational extremes in tracking approaches: Nearest neighbor and multiple hypothesis tracking.

We conducted a study to assess the accuracy of nearest neighbour (NN) and multiple hypothesis tracking (MHT) methods-which are opposite extremes in computational complexity-in determining the percentage of motile sperms and the number of sperms tracked in simulated data of fish sperm movements, and to evaluate the resulting number of tracking errors and analysis duration. Sperm tracking and swimming path assembly were assessed in 36 video clips (1s length at 100 fps) of emulated Rhamdia quelen sperm kinetics at different densities (50, 100, 200 or 300 spermatozoa in the field of view) and motility rates (30, 60 or 90%). The MHT method accurately estimated the percentage of motile sperms, whereas NN underestimated it by up to 6.59%. Increase in sperm density reduced the number of sperms tracked from both trackers. With more than 50 sperms in the field of view, NN and MHT tracked 73% and 92% of the ground-truth sperm count, respectively. Both trackers showed a quadratic increase in tracking errors with increasing sperm density. The maximum percentage of errors at 90% motility was 12% for NN and 4.7% for MHT. The MHT tracker required up to 150s to track 300 sperms, whereas NN completed the tracking procedure in less than 0.5s. On maintaining a density of up to 100 sperms in the field of view, it was possible to obtain high accuracy, low number of tracking errors and an acceptable analysis duration with both tracking methods.

Performance Analysis of a Full Order Sensorless Control Adaptive Observer for Doubly-Fed Induction Generator in Grid Connected Operation

This paper focuses on the performance analysis of a sensorless control for a Doubly Fed Induction Generator (DFIG) in grid-connected operation for turbine-based wind generation systems. With reference to a conventional stator flux based Field Oriented Control (FOC), a full-order adaptive observer is implemented and a criterion to calculate the observer gain matrix is provided. The observer provides the estimated stator flux and an estimation of the rotor position is also obtained through the measurements of stator and rotor phase currents. Due to parameter inaccuracy, the rotor position estimation is affected by an error. As a novelty of the discussed approach, the rotor position estimation error is considered as an additional machine parameter, and an error tracking procedure is envisioned in order to track the DFIG rotor position with better accuracy. In particular, an adaptive law based on the Lyapunov theory is implemented for the tracking of the rotor position estimation error, and a current injection strategy is developed in order to ensure the necessary tracking sensitivity around zero rotor voltages. The roughly evaluated rotor position can be corrected by means of the tracked rotor position estimation error, so that the corrected rotor position is sent to the FOC for the necessary rotating coordinate transformation. An extensive experimental analysis is carried out on an 11 kW, 4 poles, 400 V/50 Hz induction machine testifying the quality of the sensorless control.

Co-culture of Glioblastoma Stem-like Cells on Patterned Neurons to Study Migration and Cellular Interactions.

Glioblastomas (GBMs), grade IV malignant gliomas, are one of the deadliest types of human cancer because of their aggressive characteristics. Despite significant advances in the genetics of these tumors, how GBM cells invade the healthy brain parenchyma is not well understood. Notably, it has been shown that GBM cells invade the peritumoral space via different routes; the main interest of this paper is the route along white matter tracts (WMTs). The interactions of tumor cells with the peritumoral nervous cell components are not well characterized. Herein, a method has been described that evaluates the impact of neurons on GBM cell invasion. This paper presents an advanced co-culture in vitro assay that mimics WMT invasion by analyzing the migration of GBM stem-like cells on neurons. The behavior of GBM cells in the presence of neurons is monitored by using an automated tracking procedure with open-source and free-access software. This method is useful for many applications, in particular, for functional and mechanistic studies as well as for analyzing the effects of pharmacological agents that can block GBM cell migration on neurons.

Joint tracking and classification of multiple extended targets via the PHD filter and star-convex RHM

For joint tracking and classification (JTC) of multiple extended targets in the presence of clutter and detection uncertainty, this paper proposes a recursive algorithm based on the probability hypothesis density (PHD) filter and star-convex random hypersurface model (RHM), resulting in the JTC-RHM-PHD filter. By modeling the extent state via the star-convex RHM, the JTC-RHM-PHD filter can classify the extended targets using the feature information of size and shape, instead of the size information only in the random matrix model (RMM)-based JTC method. To integrate the prior class-dependent information into the tracking procedure and obtain the recursive expressions of the JTC-RHM-PHD filter, the relationship between the instantaneous extent state and prior class-dependent information is first constructed. Then, the target state is remodeled by two vectors: one for the kinematic state and another for the extent state. The kinematic state is estimated via a Kalman-like filter. For the extent state, the measurement-based extent state and class-based extent state are obtained via the sensor measurements and prior class-dependent information, respectively. The two kinds of extent states are used to determine the target class. At last, a Gamma-Gaussian-Gaussian mixture implementation of the JTC-RHM-PHD filter is presented. Simulation results indicate that: (1) Compared with the RMM-based JTC method, the proposed JTC-RHM-PHD filter can correctly classify multiple extended targets with similar sizes. (2) Compared with the RHM-PHD filter, the proposed JTC-RHM-PHD filter has superior tracking performance with a similar algorithm complexity.

Spatial ecology of Norway lobster Nephrops norvegicus in Mediterranean deep-water environments: implications for designing no-take marine reserves

The Norway lobsterNephrops norvegicusis one of the most important marine resources for European fisheries. However, overfishing has caused the stocks to decline over the last decades, particularly in the Mediterranean Sea. The implementation of no-take marine reserves could change these current trends, thus achieving a more sustainable fishery. The effectiveness of no-take reserves depends on optimal size design, and because of this, new behavioural data on the spatial ecology of the species are of pivotal importance. Here, for the first time, we investigated the spatial movements and daily activity patterns of Norway lobster in a deep-water (315-475 m depth) no-take marine reserve of 10 km2in the continental slope of the northwestern Mediterranean Sea, by combining acoustic tracking and tagging-recapture procedures. The results revealed the territorial behaviour of Norway lobster, centred in small exclusive individual areas where most displacements took place at midday. We found that once settled in a place, their home ranges reached approximate sizes of 17.75 to 736.25 m2, suggesting that no-take marine areas focussed on recovering Norway lobster populations do not require large extents to be effective. Tag-recapture data indicated minimal spillover of biomass, implying that Norway lobsters are site settled and do not perform large movements. Future studies on larval spread and recruitment would be necessary to focus on the possible spillover benefit for fisheries. The acoustic telemetry system used in the present experiment effectively revealed the range of movement of individuals, and thus represents a promising monitoring tool to assess no-take marine reserve sizes and reciprocal spacing for deep-water demersal resources.

Decoupled Kalman Filter Based Identification of Time-Varying FIR Systems

When system parameters vary at a fast rate, identification schemes based on model-free local estimation approaches do not yield satisfactory results. In cases like this, more sophisticated parameter tracking procedures must be used, based on explicit models of parameter variation (often referred to as hypermodels), either deterministic or stochastic. Kalman filter trackers, which belong to the second category, are seldom used in practice due to difficulties in adjusting their internal parameters such as the smoothness coefficient and the order of the hypermodel. The paper presents a new solution to this problem, based on the concept of preestimation of system parameters. The resulting identification algorithms, which can be characterized as decoupled Kalman trackers, are computationally attractive, easy to tune and can be optimized in an adaptive fashion using the parallel estimation approach. The decoupled KF algorithms can be regarded as an attractive alternative to the state-of-the-art algorithms which are much more computationally demanding.