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A detailed spatially explicit evapotranspiration (ET) mapping at daily basis is of substantial benefit for agricultural water management. An integrated multi-sensor approach that combines the benefits of the high spatial resolution of Landsat and the high temporal resolution of MODIS and geostationary satellites to provide daily field-scale ET estimates is evaluated over two different agricultural landscapes. The ET data fusion methodology described here can provide detailed information about daily and seasonal water use patterns. This information can be of utility for irrigation managers at the scale of individual fields as well as for regional monitoring of water use toward allocation and conservation efforts.

Global satellite sea-surface salinity (SSS) observations are now a reality; consequently, the influences of SSS on operational microwave radiometry need to be considered. At the same time, the in-progress transition of operational agencies from salinity-independent radiative transfer modeling (RTM) to a salinity-dependent RTM exposes non-negligible sources of error and uncertainty in past operational passive microwave retrievals; consequently, the impact of improved modeling of SSS influences on ocean surface permittivity, as a principal component of ocean surface emissivity, is examined. Both reductions and continuing elements of uncertainty due to SSS are explored. Ocean surface emissivity's interwoven dependencies on salinity, temperature, and frequency are highly nonlinear; consequently, impacts due to salinity will depend on the instrument, application, and situation.

This work deals with the study of human postural responses to external perturbations, performed using a novel mechatronic electro-pneumatic system. The device, which must be handled by a clinical operator, has been designed, developed and tested on human subjects. An Hardware-in-the-Loop equipment is designed and developed reproducing the behavior of the operator, the automatic perturbator and the subject. Results underline a good capability of the device to reproduce the reference of the impact force. https://youtu.be/ATUFuetf-cI

AbstractDiffusion of innovations has gained a lot of attention and concerns different scientific fields. Many studies, which examine the determining factors of technological innovations in the agricultural and agrifood sector, have been conducted using the widely used Technology Accepted Model, for a random sample of farmers or firms engaged in agricultural sector. In the present study, a holistic examination of the determining factors that affect the propensity of firms to innovate or imitate, is conducted. The diffusion of ICT tools of firms which are engaged in the NACE 02/03 as well as in the NACE 10/11 classifications for 49 heterogeneous national markets is examined, using the Bass model. The innovation parameter is positively associated with rural income, female employment, export activity and education of farmers, while the imitation parameter is increased in countries whose societies are characterized by uncertainty avoidance.

Fog-to-Cloud (F2C) is a novel paradigm aimed at increasing the benefits brought by the growing Internet-of-Things (IoT) devices population at the edge of the network. F2C is intended to manage the available resources from the core to the edge of the network, allowing services to choose and use either a specific cloud or fog offer or a combination of both. Recognized the key benefits brought by F2C systems, such as low-latency for real-time services, location awareness services, mobility support and the possibility to process data close to where they are generated, research efforts are being made towards the creation of a widely accepted F2C architecture. However, in order to achieve the desired F2C control framework, many open challenges must be solved. In this paper, we address the identity management challenges and propose an Identity Management System (IDMS) that is based on the fragmentation of the network resource IDs. In our approach, we divide the IDs into smaller fragments and then, when two nodes connect, they use a portion of their full ID (n fragments) for mutual identification. The conducted experiments have shown that an important reduction in both, the query execution times and the space required to store IDs, can be achieved when our IDMS is applied.

A combination of good spatial and spectral resolution make visible to shortwave infrared spectral imaging from aircraft or spacecraft a highly valuable technology for remote sensing of the Earth's surface. Many applications require the elimination of atmospheric effects caused by molecular and particulate scattering; a process known as atmospheric correction, compensation, or removal. The Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes (FLAASH) atmospheric correction code derives its physics-based algorithm from the MODTRAN4 radiative transfer code. A new spectra; recalibration algorithm, which has been incorporated into FLAASH, is described. Results from processing Hyperion data with FLAASH are discussed.

Robotics is a versatile tool for teaching STEM topics, as it supports various disciplines, skill sets and target audiences. However, controllers used in Educational Robotics are often limited in their use cases. In this regard, Hedgehog tries to be flexible by design. This paper introduces Hedgehog’s architecture, currently implemented and future use cases, and experiences from our first Hedgehog workshops.

The European funded research project CAPSELLA has developed a pilot application that uses open data-driven services to enhance transparency and inform decision making in food supply chain management, public procurement and consumption of meals served at public schools. The application acquires nutritional, health and social data by users and exploits other data available in open databases. Aggregated data form a geolocated interface informing parents, city officers, canteen operators and public food procurement officers about the nutritional background and habits of school children across the city. The pilot is implemented in the cities of Milan and Asti, Italy. The Public Food sector can drive urban sustainability strategies, having the potential to influence the traded volumes and overall quality in the food system and the food chain. Developing data driven ICT tools by integrating health, nutritional, environmental (i.e. food miles, carbon, water) and consumer data can support sustainability goals and the process of food production, delivery and consumption.

This poster about SolACE was presented at the Agri Innovation Summit in Lisbon on October 11 and 12, 2017. More information about the summit is available on http://www.aislisbon2017.com.

The aim of this paper is to trigger a conversation about the assessment, definition of metrics and testing procedures of software-defined GNSS receivers. While the evaluation of traditional (i.e., built on application–specific integrated circuit technology) GNSS receivers is now well–understood, and enjoys both a solid testing industry providing the required equipment and universally agreed figures of merit, the particularities of software–defined radio technologies claim for a more comprehensive approach. In order to account for such a multi–faceted nature, the authors identify sixteen design forces, or dimensions in which a software-defined GNSS can improve. Upon those definitions, a wide list of performance indicators, metrics and procedures are then proposed for each of the identified thrusts. The list can be used as a generative source of ideas when defining key performance indicators in projects, products or services involving a software–defined GNSS receiver.