Temperature and emissivity separation from ASTER data for low spectral contrast surfaces

The performance of Advanced Spaceborne Thermal Emission Reflection Radiometer (ASTER) thermal infrared (TIR) data product algorithms was evaluated for low spectral contrast surfaces (such as vegetation and water) in a test site close to Valencia, Spain. Concurrent ground measurements of surface temperature, emissivity, and atmospheric radiosonde profiles were collected at the test site, which is a thermally homogeneous area of rice crops with nearly full vegetation cover in summer. Using the ground data and the local radiosonde profiles, at-sensor radiances were simulated for the ASTER TIR channels and compared with L1B data (calibrated at-sensor radiances) showing discrepancies up to 3% in radiance for channel 10 at 8.3 μm (equivalently, 2.5 °C in temperature or 7% in emissivity), whereas channel 13 (10.7 μm) yielded a closer agreement (maximum difference of 0.5% in radiance or 0.4 °C in temperature). We also tested the ASTER standard products of land surface temperature (LST) and spectral emissivity generated with the Temperature-Emissivity Separation (TES) algorithm with standard atmospheric correction from both global data assimilation system profiles and climatology profiles. These products showed anomalous emissivity spectra with lower emissivity values and larger spectral contrast (or maximum-minimum emissivity difference, MMD) than expected, and as a result, overestimated LSTs. In this work, a scene-based procedure is proposed to obtain more accurate MMD estimates for low spectral contrast materials (vegetation and water) and therefore a better retrieval of LST and emissivity with the TES algorithm. The method uses various gray-bodies or near gray-bodies with known emissivities and assumes that the calibration and atmospheric correction performed with local radiosonde data are accurate for channel 13. Taking the channel 13 temperature (atmospherically and emissivity corrected) as the true LST, the radiances for the other channels were simulated and used to derive linear relationships between ASTER digital numbers and at-ground radiances for each channel. The TES algorithm was applied to the adjusted radiances and the resulting products showed a closer agreement with the ground measurements (differences lower than 1% in channel 13 emissivities and within ± 0.3 °C in temperature for rice and sea pixels).     

Intelligent planning and the design of a new risk-based,intelligent flight plan

A safe flight starts with effective performance of the pre-flight flight planning and briefing task. However, several problems related to the execution of this task can be identified. Potentially, the introduction of an improved flight plan provides an opportunity to improve the quality and availability of information provided to Flight Crew, thereby enhancing the quality of crew briefings. The proposed risk-based, intelligent flight plan is designed from the perspective of the current operational concept (e.g. fixed routes and ATC managerial role for separation), and associated airline Flight Planning and Dispatch functions. In this case, the focus is sharing information across specific airline stakeholders (e.g. Flight Operations Management and Safety functions) and Maintenance, to support a safe and efficient flight operation. Overall, the introduction of this new flight plan will result in the definition of new operational and organisational processes, along with a new way of performing the pre-flight, planning and briefing task. It is anticipated that this will impact positively on the operational and safety outcome of the flight.     

Updated Taxonomy for the Network and Service Management Research Field

Network and service management is an established research field within the general area of computer networks. A few years ago, an initial taxonomy, organizing a comprehensive list of terms and topics, was established through interviews with experts from both industry and academia. This taxonomy has since been used to better partition standardization efforts, identify classes of managed objects and improve the assignment of reviewers to papers submitted in the field. Because the field of network and service management is rapidly evolving, a biyearly update of the taxonomy was proposed. In this paper, a large-scale questionnaire is presented which was answered by experts in the field, evaluating the relevance of each individual topic for the next five years. Missing topics, which are likely to become relevant over the next few years, are identified as well. Furthermore, an analysis is performed of the records of papers submitted to major conferences in the area. Based on the obtained results, an updated version of the taxonomy is proposed.     

Long-term availability prediction for groups of volunteer resources

Volunteer computing uses the free resources in Internet and Intranet environments for large-scale computation and storage. Currently, 70 applications use over 12 PetaFLOPS of computing power from such platforms. However, these platforms are currently limited to embarrassingly parallel applications. In an effort to broaden the set of applications that can leverage volunteer computing, we focus on the problem of predicting if a group of resources will be continuously available for a relatively long time period. Ensuring the collective availability of volunteer resources is challenging due to their inherent volatility and autonomy. Collective availability is important for enabling parallel applications and workflows on volunteer computing platforms. We evaluate our predictive methods using real availability traces gathered from hundreds of thousands of hosts from the SETI@home volunteer computing project. We show our prediction methods can guarantee reliably the availability of collections of volunteer resources. We show that this is particularly useful for service deployments over volunteer computing environments.     

The personal lift-assist device and lifting technique: a principal component analysis

The personal lift-assist device (PLAD) is a non-motorised, on-body device that acts as an external force generator using the concept of stored elastic energy. In this study, the effect of the PLAD on the lifting kinematics of male and female lifters was investigated using principal component analysis. Joint kinematic data of 15 males and 15 females were collected using an opto-electronic system during a freestyle, symmetrical-lifting protocol with and without wearing the PLAD. Of the 31 Principal Components (PCs) retained in the models, eight scores were significantly different between the PLAD and no-PLAD conditions. There were no main effects for gender and no significant interactions. Results indicated that the PLAD similarly affected the lifting kinematics of males and females; demonstrating significantly less lumbar and thoracic flexion and significantly greater hip and ankle flexion when wearing the PLAD. These findings add to the body of work that suggest the PLAD may be a safe and effective ergonomic aid. STATEMENT OF RELEVANCE: The PLAD is an ergonomic aid that has been shown to be effective at reducing low back demands during manual materials handling tasks. This body of work establishes that the PLAD encourages safe lifting practices without adversely affecting lifting technique.     

Angle-of-arrival localization based on antenna arrays for wireless sensor networks

Among the large number of contributions concerning the localization techniques for wireless sensor networks (WSNs), there is still no simple, energy and cost efficient solution suitable in outdoor scenarios. In this paper, a technique based on antenna arrays and angle-of-arrival (AoA) measurements is carefully discussed. While the AoA algorithms are rarely considered for WSNs due to the large dimensions of directional antennas, some system configurations are investigated that can be easily incorporated in pocket-size wireless devices.A heuristic weighting function that enables decreasing the location errors is introduced. Also, the detailed performance analysis of the presented system is provided. The localization accuracy is validated through realistic Monte-Carlo simulations that take into account the specificity of propagation conditions in WSNs as well as the radio noise effects. Finally, trade-offs between the accuracy, localization time and the number of anchors in a network are addressed.     

A Unified Framework for Compositional Fitting of Active Appearance Models

Active appearance models (AAMs) are one of the most popular and well-established techniques for modeling deformable objects in computer vision. In this paper, we study the problem of fitting AAMs using compositional gradient descent (CGD) algorithms. We present a unified and complete view of these algorithms and classify them with respect to three main characteristics: (i) cost function; (ii) type of composition; and (iii) optimization method. Furthermore, we extend the previous view by: (a) proposing a novel Bayesian cost function that can be interpreted as a general probabilistic formulation of the well-known project-out loss; (b) introducing two new types of composition, asymmetric and bidirectional, that combine the gradients of both image and appearance model to derive better convergent and more robust CGD algorithms; and (c) providing new valuable insights into existent CGD algorithms by reinterpreting them as direct applications of the Schur complement and the Wiberg method. Finally, in order to encourage open research and facilitate future comparisons with our work, we make the implementation of the algorithms studied in this paper publicly available as part of the Menpo Project (http://www.menpo.org).     

Segmentation of multiple sclerosis lesions in brain MRI: A review of automated approaches

Automatic segmentation of multiple sclerosis (MS) lesions in brain MRI has been widely investigated in recent years with the goal of helping MS diagnosis and patient follow-up. However, the performance of most of the algorithms still falls far below expert expectations. In this paper, we review the main approaches to automated MS lesion segmentation. The main features of the segmentation algorithms are analysed and the most recent important techniques are classified into different strategies according to their main principle, pointing out their strengths and weaknesses and suggesting new research directions. A qualitative and quantitative comparison of the results of the approaches analysed is also presented. Finally, possible future approaches to MS lesion segmentation are discussed.     

Proteomic analysis in cerebrospinal fluid of patients with atypical nonketotic hyperglycinemia and pulmonary hypertension - A pilot study

A variant phenotype of nonketotic hyperglycinemia has been described by our group associated with pulmonary hypertension. The aim of this study is to investigate the cerebrospinal fluid proteomes to get an insight into this neurodegenerative process producing leukoencephalopathy with white matter spongiform degeneration. DIGE and MALDI-TOF-TOF analyses were performed to carry out the proteomic study of four patients against three normal controls and one additional control of a classical nonketotic hyperglycinemia. The differential proteomic analysis showed a displacement of some series of spots toward the acidic side. The shifted proteins showed a high degree of carbonylation and increased methionine sulfoxidation was found in cystatin C and in vitamin-D-binding protein. These findings in addition to the increase of serum malondialdehyde concentration provide evidence of an oxidative stress in the patients under study, which is probably systemic rather than mainly confined to the CNS. The similarities of our findings with those found in other neurodegenerative diseases suggest that oxidative damage is commonly involved in these pathologies. DIGE technology improves the 2-D PAGE differential analysis and it is suitable in proteomic studies with a small number of cases.