Synchronous collaboration of virtual and remote laboratories

Virtual and remote laboratories(VRLs) are e-learning resources which enhance the accessibility of experimental setups providing a distance teaching framework which meets the student's hands-on learning needs. In addition, online collaborative communication represents a practical and a constructivist method to transmit the knowledge and experience from the teacher to students, overcoming physical distance and isolation. Thus, the integration of learning environments in the form of VRLs inside collaborative learning spaces is strongly desired. Considering these facts, the authors of this document present an original approach which enables user to share practical experiences while they work collaboratively through the Internet. This practical experimentation is based on VRLs, which have been integrated inside a synchronous collaborative e-learning framework. This article describes the main features of this system and its successful application for science and engineering subjects.

Accurate integration of forced and damped oscillators

The new methods accurately integrate forced and damped oscillators. A family of analytical functions is introduced known as T-functions which are dependent on three parameters. The solution is expressed as a series of T-functions calculating their coefficients by means of recurrences which involve the perturbation function. In the T-functions series method the perturbation parameter is the factor in the local truncation error. Furthermore, this method is zero-stable and convergent. An application of this method is exposed to resolve a physic IVP, modeled by means of forced and damped oscillators. The good behavior and precision of the methods, is evidenced by contrasting the results with other-reputed algorithms implemented in MAPLE.

Advances in camera trap data management tools: Towards collaborative development and integration with GIS

Camera traps have become a widely used technique for conducting biological inventories, generating a large number of database records of great interest. The main aim of this paper is to describe a new free and open source software (FOSS), developed to facilitate the management of camera-trapped data which originated from a protected Mediterranean area (SE Spain). In the last decade, some other useful alternatives have been proposed, but ours focuses especially on a collaborative undertaking and on the importance of spatial information underpinning common camera trap studies. This FOSS application, namely, “Camera Trap Manager” (CTM), has been designed to expedite the processing of pictures on the .NET platform. CTM has a very intuitive user interface, automatic extraction of some image metadata (date, time, moon phase, location, temperature, atmospheric pressure, among others), analytical (Geographical Information Systems, statistics, charts, among others), and reporting capabilities (ESRI Shapefiles, Microsoft Excel Spreadsheets, PDF reports, among others). Using this application, we have achieved a very simple management, fast analysis, and a significant reduction of costs. While we were able to classify an average of 55 pictures per hour manually, CTM has made it possible to process over 1000 photographs per hour, consequently retrieving a greater amount of data.

Simultaneous synthesis of heat exchanger networks with pressure recovery: optimal integration between heat and work

The optimal integration between heat and work may significantly reduce the energy demand and consequently the process cost. This paper introduces a new mathematical model for the simultaneous synthesis of heat exchanger networks (HENs) in which the pressure levels of the process streams can be adjusted to enhance the heat integration. A superstructure is proposed for the HEN design with pressure recovery, developed via generalized disjunctive programming (GDP) and mixed-integer nonlinear programming (MINLP) formulation. The process conditions (stream temperature and pressure) must be optimized. Furthermore, the approach allows for coupling of the turbines and compressors and selection of the turbines and valves to minimize the total annualized cost, which consists of the operational and capital expenses. The model is tested for its applicability in three case studies, including a cryogenic application. The results indicate that the energy integration reduces the quantity of utilities required, thus decreasing the overall cost.

Polarimetric Response of Rice Fields at C-Band: Analysis and Phenology Retrieval

A set of ten RADARSAT-2 images acquired in fully polarimetric mode over a test site with rice fields in Seville, Spain, has been analyzed to extract the main features of the C-band radar backscatter as a function of rice phenology. After observing the evolutions versus phenology of different polarimetric observables and explaining their behavior in terms of scattering mechanisms present in the scene, a simple retrieval approach has been proposed. This algorithm is based on three polarimetric observables and provides estimates from a set of four relevant intervals of phenological stages. The validation against ground data, carried out at parcel level for a set of six stands and up to nine dates per stand, provides a 96% rate of coincidence. Moreover, an equivalent compact-pol retrieval algorithm has been also proposed and validated, providing the same performance at parcel level. In all cases, the inversion is carried out by exploiting a single satellite acquisition, without any other auxiliary information.

Estimation of Key Dates and Stages in Rice Crops Using Dual-Polarization SAR Time Series and a Particle Filtering Approach

Information of crop phenology is essential for evaluating crop productivity. In a previous work, we determined phenological stages with remote sensing data using a dynamic system framework and an extended Kalman filter (EKF) approach. In this paper, we demonstrate that the particle filter is a more reliable method to infer any phenological stage compared to the EKF. The improvements achieved with this approach are discussed. In addition, this methodology enables the estimation of key cultivation dates, thus providing a practical product for many applications. The dates of some important stages, as the sowing date and the day when the crop reaches the panicle initiation stage, have been chosen to show the potential of this technique.

Subsidence damage assessment of a Gothic church using differential interferometry and field data

The Santas Justa and Rufina Gothic church (fourteenth century) has suffered several physical, mechanical, chemical, and biochemical types of pathologies along its history: rock alveolization, efflorescence, biological activity, and capillary ascent of groundwater. However, during the last two decades, a new phenomenon has seriously affected the church: ground subsidence caused by aquifer overexploitation. Subsidence is a process that affects the whole Vega Baja of the Segura River basin and consists of gradual sinking in the ground surface caused by soil consolidation due to a pore pressure decrease. This phenomenon has been studied by differential synthetic aperture radar interferometry techniques, which illustrate settlements up to 100 mm for the 1993–2009 period for the whole Orihuela city. Although no differential synthetic aperture radar interferometry information is available for the church due to the loss of interferometric coherence, the spatial analysis of nearby deformation combined with fieldwork has advanced the current understanding on the mechanisms that affect the Santas Justa and Rufina church. These results show the potential interest and the limitations of using this remote sensing technique as a complementary tool for the forensic analysis of building structures.

Contribution to Real-Time Estimation of Crop Phenological States in a Dynamical Framework Based on NDVI Time Series: Data Fusion With SAR and Temperature

In this study, a methodology based in a dynamical framework is proposed to incorporate additional sources of information to normalized difference vegetation index (NDVI) time series of agricultural observations for a phenological state estimation application. The proposed implementation is based on the particle filter (PF) scheme that is able to integrate multiple sources of data. Moreover, the dynamics-led design is able to conduct real-time (online) estimations, i.e., without requiring to wait until the end of the campaign. The evaluation of the algorithm is performed by estimating the phenological states over a set of rice fields in Seville (SW, Spain). A Landsat-5/7 NDVI series of images is complemented with two distinct sources of information: SAR images from the TerraSAR-X satellite and air temperature information from a ground-based station. An improvement in the overall estimation accuracy is obtained, especially when the time series of NDVI data is incomplete. Evaluations on the sensitivity to different development intervals and on the mitigation of discontinuities of the time series are also addressed in this work, demonstrating the benefits of this data fusion approach based on the dynamic systems.