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This paper focuses on the design of a robust Real Time Locating Systems (RTLS) based on the Ultra-Wide Band (UWB) technology for Augmented Reality (AR) applications in TV studios that require artists and/or a presenter to be accurately localized. According to a UWB-based measurement campaign, carried out in a TV studio environment, ranging measurements are heavily affected by the human body interference. Indeed, lots of outliers are present as the UWB receiver may synchronize to reflected paths, which result to be much stronger than the direct one. As a consequence, range errors are very large. In this context, to improve the localization performance, we increased the redundancy of the RTLS by employing more than one tag to localize the artists on the TV scene. In particular, we have applied the Extended Kalman Filter (EKF) algorithm to work with two and three tags. Moreover, an outlier detection and correction procedure have been defined and adopted for the ranging phase. The resulting localization performance, based on real range measurements, shows that the EKF with two tags outperforms by 83.5 % the one with single tag.

Previous research has suggested that activities such as community gardens could offer a wide range of health benefits. The aim of the article is to systematically review the available literature to analyse the magnitude of the phenomenon, the geographical distribution, and the main characteristics in terms of health outcomes and target populations. The search addresses the question whether the activity in community gardens improves health and well-being outcomes of individuals. From the total amount of 7226, 84 selected articles showed that:(1) up to 50% are published by U.S. universities or institutions; (2) up to 44% of the studies considered “community gardens” as the main activity of the research focus; (3) one-third of the studies included adults; (4) almost 25% of the studies used “general health” as the main outcome when investigating the benefits of community gardens; (5) the percentage of studies that achieved their outcomes was heterogeneous among the different health dimensions. In conclusion, while a certain degree of heterogeneity in the used definition and outcome still exist, community gardens may be a viable strategy for well-being promotion in terms of psychological, social, and physical health and may be considered as an innovative urban strategy to promote urban public health.

A growing awareness that highly intensified agricultural systems have made a substantial worldwide contribution to the worsening of the resilience capacity of natural ecosystems has, over the last twenty years, brought general attention to agroecological management models. This aspect is even more evident in industrial agriculture, which is based on the use of multiple chemical products derived from non-natural synthesis. In more developed countries, a new idea of ecology linked to agricultural production has been increasingly developed and, for this reason, there has been a greater diffusion of differentiated agricultural models taking into consideration the environmental impact of production choices and policies addressed to the conservation of natural resources. In urban agricultural production, it is even more important to adopt resilient production models that, in addition to developing responsible production paths and allowing a positive connection with the needs of consumers, guarantees reasonable and positive behaviors respecting the environment in which most of the urban population lives; in other words, the implementation of goal 12 of the sustainable development goals (SDG #12 Responsible Production and Consumption) of the United Nations. In this work, we report some case studies inspired by the activities carried out by the Slow Food Association in Africa and demonstrate the importance of agroecological models in small-scale agricultural systems, related to the development of school and community gardens in small urban areas of different African countries, as a tool for integrating agricultural activities aimed at social resilience and the conservation of ecosystems.

This research explored the preferences and buying habits of a sample of 620 consumers of fresh-cut, ready-to-eat salads. A best&ndash, worst scaling approach was used to measure the level of preference stated by individuals regarding 12 attributes for quality (intrinsic, extrinsic and credence) of fresh-cut salads. The experiment was carried out through direct interviews at several large-scale retail outlets in the Turin metropolitan area (north-west of Italy). Out of the total number of questioned consumers, 35% said they did not consume fresh-cut salads. On the contrary, the rest of the involved sample expressed the highest degree of preference towards the freshness/appearance attribute, followed by the expiration date and the brand. On the contrary, attributes such as price, organic certification and food safety did not emerge as discriminating factors in consumer choices. Additionally, five clusters of consumers were identified, whose preferences are related both to purchasing styles and socio-demographic variables. In conclusion, this research has highlighted the positive attitude of consumers towards quality products backed by a brand, providing ideas for companies to improve within this sector and implement strategies to answer the needs of a new segment of consumers, by determining market opportunities that aim to strengthen local brands.

Advances in cultivation of almonds: effects of genotypes, environment and cultural techniques

Millions of people worldwide suffer from visual disabilities as a result of retinal degeneration. Due to the poor regenerative capability of the central nervous system, retinal cell loss is essentially irreversible. Currently available therapies can only decelerate the degenerative process at late stages and are largely ineffective. However, the possibility of using stem cell-based therapy as cell rescue or cell replacement therapy is broadly being explored. While cell rescue is based on the secretion of biologically active molecules by the transplanted cells, cell replacement refers to the possibility of injected stem cells replacing the defective ones either via direct differentiation, transdifferentiation of the transplanted cells, or via cell fusion-mediated reprogramming of retinal cells.

A sustainable future for the community is one of the objectives established by the European Union Agenda 2030. Furthermore, sustainable consumption has been identified as one of the possible trajectories for sustainable development. It is for this reason that food production, distribution and consumption ways cannot be overlooked for sustainability achievement, as well as the consumer&rsquo, s related perception. In this research the Best&ndash, Worst scaling methodology was adopted to explore the priorities declared by a sample of 801 consumers among 12 different sustainability definitions selected from the scientific literature. The choice experiment was carried out through face-to-face interviews during two food and wine events closely related to the sustainability theme in the food sector. The respondents considered as sustainability priority definition the &ldquo, preservation of natural resources&rdquo, followed by &ldquo, decent working conditions&rdquo, and &ldquo, accessibility for everyone to healthy and safe food&rdquo, Moreover, 5 consumer&rsquo, s clusters were identified according to the priorities assigned to the different sustainability definitions, as well as to individuals socio-demographic characteristics. The description of the priorities assigned by the clusters to the different sustainability definitions have also been described as guidelines for consumer attitudes towards the different sustainability dimensions (environmental, social, economic and governance).

L'agroecologia viene spesso presentata come un'alternativa agli attuali sistemi di produzione diffusi, sebbene ci siano molte domande sulla reale possibilità di una produzione alimentare sufficiente- mente elevata per una popolazione in crescita. L' analisi sviluppata in questo paper è basata sulla ricer- ca scientifica degli ultimi vent'anni e sulle l'attività delle ONG, dei movimenti degli agricoltori e delle organizzazioni governative di diversi contesti. L'obiettivo è quello di fornire un panorama dei princi- pali argomenti in discussione per una transizione agroecologica dei sistemi alimentari mondiali, individ- uando alcune sfide prioritarie e immaginando chi saranno i partecipanti questo cambiamento. Data la complessità del tema, alcuni temi specifici non sono stati presi in considerazione (ad esempio valore nutrizionale degli alimenti, salute), invece ci siamo concentrati su quelle questioni trasversali che stanno infiammando il dibattito in contesti istituzionali e non istituzionali .

This study assesses consumer preferences during fruit and vegetable (FV) sales, considering the sociodemographic variables of individuals together with their choice of point of purchase. A choice experiment was conducted in two metropolitan areas in Northwest Italy. A total of 1170 consumers were interviewed at different FV purchase points (mass retail chains and open-air markets) using a paper questionnaire. The relative importance assigned by consumers to 12 fruit and vegetable product attributes, including both intrinsic and extrinsic quality cues, was assessed by using the best&ndash, worst scaling (BWS) methodology. The BWS results showed that &ldquo, origin&rdquo, &ldquo, seasonality&rdquo, and &ldquo, freshness&rdquo, were the most preferred attributes that Italian consumers took into account for purchases, while no importance was given to &ldquo, organic certification&rdquo, variety&rdquo, or &ldquo, brand&rdquo, Additionally, a latent class analysis was employed to divide the total sample into five different clusters of consumers, characterized by the same preferences related to FV attributes. Each group of individuals is described on the basis of sociodemographic variables and by the declared fruit and vegetable point of purchase. This research demonstrates that age, average annual income, and families with children are all discriminating factors that influence consumer preference and behavior, in addition to affecting which point of purchase the consumer prefers to acquire FV products from.

Today, a large number of cost saving and energy efficient applications are enabled by Wireless Sensor and Actuator Networks (WSANs). Usually, these solutions have serious connectivity problems in scenarios where other wireless technologies are co-located sharing the frequency spectrum (e.g. industrial shop-floors). To cope with this issue, the concept of Multi-Radio (MR) has been introduced, which promotes the simultaneous use of multiple radio communication interfaces, leveraging their different characteristics, to improve the overall system performance and reliability. The proposed approach based on cognitive algorithm, considers two wireless technologies operating at the 2.4 GHz frequency band, namely Wi-Fi and 6LoWPAN, and provides a concrete implementation of the system using a real test-bed industry scenario. The solution provides a reliable communication infrastructure for manufacturing processes, firstly combining the properties of several physical layer standards and secondly, providing the ability to recover from temporary network failures by switching from a communication channel to another one.

Occupational safety and health (OSH) in industrial environments is gathering increasing attention in the era of Industry 4.0. In this context, location based services (LBS) can be adopted to support workers' safety in hazardous industrial environments. However, the provision of accurate location service in these harsh environments still faces big challenges. To address these challenges, this paper presents a robust hybrid localization algorithm that combines ultra-wideband (UWB) based ranging measurements and inertial measurement unit (IMU) data. The algorithm has been implemented on a proprietary wearable platform and its performance has been evaluated in an indoor environment. The experimental results show that the proposed hybrid algorithm outperforms a non-hybrid, UWB-based, Position --- Velocity (PV) extended Kalman filter (EKF), which has been chosen as benchmark, in terms of both location accuracy and availability. Thanks to a modular approach, the proposed solution also leads to a lower computation processing compared to other hybrid solutions.

The authors propose a simulation tool (ST) able to test real-time hybrid GNSS/terrestrial and cooperative positioning algorithms that fuse both pseudorange measurements from satellites and terrestrial range measurements based on radio frequency communication performed between nodes of a wireless network. In particular, the ST simulates devices belonging to a peer-to-peer (P2P) wireless network where peers, equipped also with a GNSS receiver, cooperate among them by exchanging aiding data in order to improve both positioning accuracy and availability. Furthermore, the authors propose a method to increase the robustness of cooperative algorithms based on the estimated position covariance matrix. In particular, the proposed approach assures a faster estimation convergence and improved accuracy while lowering computational complexity and network traffic. Finally, the authors tested the sensitivity of the implemented positioning algorithms through the ST in two different scenarios, first in presence of high level of pseudorange noise and then in presence of a malicious peer in the P2P network.

An increase of plum industry has been evident in Italy since the 1990s. This growth was in both area planted and production and it has been especially evident in the South of Italy, where the environmental conditions favor the development of plum orchards, particularly those adopting Japanese cultivars. The Myrobalan seedling was the main rootstock historically used in the south of the country for plum orchards, on account of its strong vigor, hardiness, longevity and adaptability to a wide range of soil types. The introduction of new scion cultivars and new rootstocks has stimulated new studies on the main technical aspects related to plum cultivation, to evaluate the wide number of rootstock genotypes which are today available for the plum species. The Italian Ministry of Agriculture has sponsored a National project which aims to evaluate the most recent rootstocks licensed and available for European and Japanese plum cultivars. A series of experimental orchards have been established in different regions representative of the main Italian plum growing areas. This paper reports on the vegetative and qualitative traits observed both for European and Japanese plum cultivars, respectively, 'Stanley' and 'Shiro', grafted onto five rootstocks.

The Sicilian territory contains a wide reserve of biodiversity of fruit tree species that, over a period of several centuries, have found there propitious pedoclimatic conditions for their establishment, and genetic diversification. The indigenous germplasm characterized Sicilian agriculture until less than one century ago but, after the diffusion of new cultivars originating from genetic improvement programs, a great part of this germplasm was replaced and now these important resources are at high risk of genetic erosion. Recently, public interest in the safeguarding of biodiversity and the development of a new interest in genetic resources and their scientific, economic and cultural importance, inspired several political actions aimed at the valorisation and conservation of this material. The present study, funded by the Sicilian government, aims to improve knowledge concerning Sicilian plum germplasm, which accounts for a great number of the accessions on the Island, through an action of characterization that includes various steps: biometric, qualitative and nutraceutical. The study was preliminarily carried out on 26 accessions as a preliminary study to facilitate the development of an efficient methodology prior to extending it to other accessions localized in the Sicilian territory.

School gardens are, increasingly, an integral part of projects aiming to promote nutritional education and environmental sustainability in many countries throughout the world. In the late 1950s, FAO (Food and Agriculture Organization) and UNICEF (United Nations Children's Fund) had already developed projects to improve the dietary intake and behavior through school and community gardens. However, notwithstanding decades of experience, real proof of how these programs contribute to improving sustainability has not been well-documented, and reported findings have mostly been anecdotal. Therefore, it is important to begin a process of collecting and monitoring data to quantify the results and possibly improve their efficiency. This study’s primary goal is to propose an interpretive structure—the “Sustainable Agri-Food Evaluation Methodology-Garden” (SAEMETH-G), that is able to quantifiably guide the sustainability evaluation of various school garden organizational forms. As a case study, the methodology was applied to 15 school gardens located in three regions of Kenya, Africa. This application of SAEMETH-G as an assessment tool based on user-friendly indicators demonstrates that it is possible to carry out sustainability evaluations of school gardens through a participatory and interdisciplinary approach. Thus, the hypothesis that the original SAEMETH operative framework could be tested in gardens has also been confirmed. SAEMETH-G is a promising tool that has the potential to help us understand school gardens’ sustainability better and to use that knowledge in their further development all over the world.

We present a screened exact-exchange (SXX) method for the efficient and accurate calculation of the optical properties of solids, where the screening is achieved through the zero-wave-vector limit of the inverse dielectric function. The SXX approach can be viewed as a simplification of the Bethe-Salpeter equation (BSE) or, in the context of time-dependent density-functional theory, as a first step towards a new class of hybrid functionals for the optical properties of solids. SXX performs well for bound excitons and continuum spectra in both small-gap semiconductors and large-gap insulators, with a computational cost much lower than that of the BSE.

Wireless sensor networks (WSNs) are a key part of the Internet of Things vision which aims at bridging together the physical and the digital worlds in several application domains. In the building automation field, WSNs are widely adopted for energy optimization, safety and security purposes, and could greatly benefit from existing information already available in preexisting building information models (BIMs). Such BIMs are normally developed during the building design phase and reused continuously during the construction and operation phases of the building life-cycle. In current deployments, however, due to lack of interoperability such information (e.g., walls geometry, materials, and so on) must often be recollected and reinputed by WSN commissioning specialists. Open development and planning tools and methodologies can play a key role in fostering interoperability and convergence of BIM and WSN systems. This paper aims at demonstrating how increased interoperability between WSN development-support tools and BIM systems could provide advantages to developers, integrators, domain specialist, and BIM users. The methodology is validated by applying a newly proposed tool exploiting BIM interoperability to support the planning of the topology of a WSN based on ultrawideband technologies. The proposed approach is evaluated through a small-scale experimentation held in a historical building in Torino (Italy).

We survey the state-of-the-art on the Internet-of-Things (IoT) from a wireless communications point of view, as a result of the European FP7 project BUTLER which has its focus on pervasiveness, context-awareness and security for IoT. In particular, we describe the efforts to develop so-called (wireless) enabling technologies, aimed at circumventing the many challenges involved in extending the current set of domains (“verticals”) of IoT applications towards a “horizontal” (i.e. integrated) vision of the IoT. We start by illustrating current research effort in machine-to-machine (M2M), which is mainly focused on vertical domains, and we discuss some of them in details, depicting then the necessary horizontal vision for the future intelligent daily routine (“Smart Life”). We then describe the technical features of the most relevant heterogeneous communications technologies on which the IoT relies, under the light of the on-going M2M service layer standardization. Finally we identify and present the key aspects, within three major cross-vertical categories, under which M2M technologies can function as enablers for the horizontal vision of the IoT.

New and alternative models for agri-food production and consumption have brought up questions regarding the effects they have on local development processes in terms of the economic exploitation of rural areas as well as environmental, cultural, and social factors. The agri-food system proposed by the Slow Food (SF) Presidia Project, which focuses on farm-to-market systems for local, high-quality, sustainable products, can respond to the new and emerging needs of both rural and urban populaces via several approaches in addition to food production itself. However, evaluating these parameters is challenging. The aim of this study was to develop an indicator-based tool to monitor the sustainability in agri-food systems that considers quality as well as economic, ecological, social, and cultural aspects. We: (i) translated the major SF principles of "good," "clean," and "fair" into five major criteria to evaluate sustainability; (ii) designed multiple indicators to monitor progress toward sustainability for each of those criteria; and (iii) applied the monitoring tools to three case studies as a first attempt at end-use validation. Indicators and criteria were weighted either equally or based on their importance to surveyed stakeholders, i.e., consumers, producers, and scientists/experts. The proposed approach performed well as a tool for a broad sustainability evaluation by effectively combining the indicators with the same feedback. With this approach, we demonstrated that the SF Presidia project increases all dimensions of sustainability and in particular socioeconomic and cultural capital by preserving the environmental and quality aspects of the food products.

Dense urban areas are particularly challenging environments for global navigation satellite systems (GNSS) because the satellite visibility is heavily reduced due to the presence of the so called urban canyons, composed of a series of tall buildings and narrow streets. In order to improve GNSS performance in these environments, hybrid (GNSS/terrestrial) and cooperative positioning algorithms that combine pseudorange measurements from visible satellites and terrestrial range measurements from neighboring terrestrial receivers have been recently proposed in the literature. Mainly, these algorithms have been tested in static or pedestrian mobility scenarios. This paper, first introduces a robust procedure that selects the most reliable neighbors for cooperation and then analyzes the performance of the optimized hybrid and cooperative positioning algorithms in a typical urban canyon scenario for vehicular navigations. Simulation results demonstrate that the positioning algorithms can accurately track the movement of vehicles in urban canyons even without fixed terrestrial infrastructure. Moreover, an accurate complexity analysis of the different hybrid algorithms is presented to understand their suitability for a real implementation.

Wireless sensor networks (WSNs), consisting of a large number of nodes to detect ambient environment, are widely deployed in a predefined area to provide more sophisticated sensing, communication, and processing capabilities, especially concerning the maintenance when hundreds or thousands of nodes are required to be deployed over wide areas at the same time. Radio frequency identification (RFID) technology, by reading the low-cost passive tags installed on objects or people, has been widely adopted in the tracing and tracking industry and can support an accurate positioning within a limited distance. Joint utilization of WSN and RFID technologies is attracting increasing attention within the Internet of Things (IoT) community, due to the potential of providing pervasive context-aware applications with advantages from both fields. WSN-RFID convergence is considered especially promising in context-aware systems with indoor positioning capabilities, where data from deployed WSN and RFID systems can be opportunistically exploited to refine and enhance the collected data with position information. In this papera, we design and evaluate a hybrid system which combines WSN and RFID technologies to provide an indoor positioning service with the capability of feeding position information into a general-purpose IoT environment. Performance of the proposed system is evaluated by means of simulations and a small-scale experimental set-up. The performed analysis demonstrates that the joint use of heterogeneous technologies can increase the robustness and the accuracy of the indoor positioning systems.

In wireless sensor networks (WSNs), hybrid algorithms are widely used in order to improve the final positioning accuracy. This paper presents a hybrid positioning algorithm which combines time of arrival (TOA) and received signal strength (RSS) measurements using two different radio technologies, ultra wide band (UWB) and ZigBee, respectively. The TOA measurements are used to estimate the distances between a mobile node and a set of anchor nodes. Both UWB- based distance estimates and RSS measurements based on ZigBee are simultaneously processed by an Extended Kalman Filter (EKF). Moreover, a low cost inertial device is also used to acquire acceleration measurements which proved to be useful in order to detect the motion of the mobile node. This information has also been integrated in the EKF algorithm accordingly. The performance of the final hybrid positioning algorithm is compared with the conventional EKF which uses a single type of range measurements, TOA or RSS. Simulation results based on a real measurements campaign, show that the hybrid algorithm significantly improves positioning accuracy. In addition, a further improvement has been achieved by applying the motion detection approach based on inertial measurements performed by the low cost acceleration sensor.

EFFECT OF ORCHARD SYSTEM ON FRUIT QUALITY OF FOUR EARLY RIPENING PEACH CULTIVARS: PRELIMINARY RESULTS E. Barone, T. Caruso, L. Di Marco F. Sottile Ist. Colture Legnose Agr. e For. Ist. Colt. Arboree University of Reggio Calabria University of Palermo 89061 Gallina (RC) 90128 Palermo Italy Italy Abstract The preliminary results of a study on the effect of orchard system on fruit quality of 'Flordaprince', 'Flordastar', 'Flordacrest' and 'Maravilha' low-chill and early ripening peach cultivars on micropropagated GF677 rootstock is reported in this paper. With the aim of evaluating the different factors that could affect fruit quality under different planting systems, two experimental orchards were established in 1990 in Sicily. Two orchard systems, 'Y' and free spindle, with planting densities respectively of 1850-2000 and 670-930 trees/ha, were compared. Data regarding yield, crop efficiency and fruit qualitative characteristics are discussed.

We present experimental data and theoretical results for valence-band satellites in semiconductors, using the prototypical example of bulk silicon. In a previous publication we introduced a new approach that allows us to describe satellites in valence photoemission spectroscopy, in good agreement with experiment. Here we give more details; we show how the the spectra change with photon energy, and how the theory explains this behaviour. We also describe how we include several effects which are important to obtain a correct comparison between theory and experiment, such as secondary electrons and photon cross sections. In particular the inclusion of extrinsic losses and their dependence on the photon energy are key to the description of the energy dependence of spectra.

This work analyzes the impact of medium access control (MAC) layer on the performance of real-time cooperative positioning in ad-hoc mobile wireless networks. The probability mass function (pmf) of the latency introduced by the MAC layer is here derived to assess the influence of MAC parameters on the latency and then operate on those to improve the positioning performance while reducing the number of position estimation iterations.

Publisher Summary This chapter presents fundamental positioning techniques typically adopted in most terrestrial networks. A straightforward method of estimating that difference in time is to cross-correlate the signals arriving at a pair of BSs. In order to estimate the angle of arrival (AOA) of incident signals, a directional antenna, such as an adaptive phased array of two or more antenna elements, is required. The straightforward method is to measure the phase difference between the signals, when impinging on different antenna elements, and convert this to an AOA estimate. Conventional methods are based on classical beamforming techniques and do not exploit any assumption on the model of the received signal nor noise. Conventional AOA-estimation techniques electronically steer beams in all possible directions and look for peaks in the output power. Low-cost solutions use lateration, estimating distances from the measured RSS between the MS and the BSs, based on some propagation channel model, usually the log-normal shadow path loss.

We propose a novel hybrid GNSS-terrestrial localization algorithm based on particle filter that fuses ranging data from both satellites and terrestrial receivers. The proposed positioning approach, named hybrid-cooperative particle filter (HCPF), is fully distributed and allows both increased positioning availability and accuracy compared to GNSS-only localization in challenged scenarios. Moreover, simulation results based on a realistic indoor scenario show that the proposed solution outperforms several state of the art algorithms such as unscented Kalman filter and an approach based on belief propagation.

In this paper we propose a novel hybrid and cooperative positioning approach based on extended Kalman filter (EKF) to localize mobile targets in indoors. The algorithm fuses both received signal strength (RSS) measurements performed by nodes of a wireless sensor network (WSN) and proximity information from radio frequency identification (RFID) devices. Simulation results prove that the proposed cooperative approach outperforms the non-cooperative version of the algorithm.

We propose a simulation tool able to test hybrid GNSS-terrestrial and cooperative positioning algorithms that fuse both pseudorange measurements from satellites and range estimates between terrestrial receivers. In particular, the tool simulates devices belonging to a peer-to-peer (P2P) network where peers cooperate by exchanging data in order to improve both positioning accuracy and availability. More specifically, the simulation tool generates range and pseudorange measurements by employing realistic propagation models and GPS orbits. Furthermore, the simulation tool allows the user to test different algorithms based on Bayesian and least squares methods in two realistic GNSS challenged scenarios namely indoor and urban canyon. Finally, the simulator take into account communication and mobility aspects allowing the user to evaluate their impact on the final positioning accuracy.

Nowadays indoor positioning applications have received great attentions among short range wireless communication systems. In particular, Wireless Sensor Network (WSN) is the most widely used technology for indoor localization as it is cheap and easy to deploy. However, location accuracy is limited by the harsh propagation of the Radio Frequency (RF) signals in indoor environments, for instance, caused by the presence of obstacles between wireless nodes, multi-paths, interference, etc. To overcome these effects and improve positioning accuracy, Radio Frequency Identification (RFID) technology is employed to assist the WSN based positioning. This paper proposes two hybrid positioning approaches based both on WSN and RFID. One solution uses an Extended Kalman Filter (EKF) algorithm while the other one uses a Particle Filter (PF) approach. Both methods are compared through Matlab simulations which demonstrate that in general the WSN/RFID hybrid approach is feasible and provides good positioning estimation capabilities even under harsh indoor conditions.

Cooperative localization algorithms have been recently introduced to overcome the limitations of systems relying on GPS or other terrestrial infrastructure. The novel hybrid cooperative unscented Kalman filter (hcUKF) approach, which fuses ranging data from both satellites and terrestrial receivers, allows increased availability, robustness and accuracy compared to GNSS-only localization in challenged scenarios. Simulation results show that the proposed solution outperforms traditional algorithms such as extended Kalman filter.

This paper presents a hybrid localization algorithm for a Peer-to-Peer (P2P)-Positioning scenario, where “peers” are devices equipped with both a GNSS (Global Navigation Satellite System) receiver and a wireless communications interface. Through their GNSS receiver, peers obtain pseudorange estimates from satellites while they use their wireless interface both to communicate with each other and to obtain terrestrial range estimates. The proposed algorithm is an extended version of the distributed-weighted multidimensional scaling (dwMDS) [1] algorithm to be compatible with the hybrid P2P scenario where unknown peers infer their own positions by fusing both GNSS pseudorange and terrestrial range estimates. Simulation results show that the proposed hybrid dwMDS (hdwMDS) algorithm out-performs the cooperative version of the least squares algorithm. Moreover, they show the related benefits in term of positioning performance in a cooperative scenario in comparison to a non cooperative one based on GNSS-only positioning.

This paper presents a wireless local area network (WLAN)-based real time system for indoors and outdoors ve- hicle localization. The proposed solution uses a neural network trained with a map of received power fingerprints from WLAN Access Points (APs) surrounding the vehicle. The practical implementation of the system is described and results from an outdoor experimental testbed are analyzed to address system performance in terms of calibration, estimation complexity, and location accuracy. Pre- and post-processing approaches aimed at improving system accuracy are also discussed. Index Terms—positioning, neural network, fingerprint, real time locating system, wireless local area network ∗

The increasing availability of ubiquitous, small, low-cost devices using wireless communications to build wireless sensor networks calls for autonomous solutions and algorithms capable of calculating the location where the information is gathered, processed, used. The requirements are particularly strict when sensor nodes are mobile; in fact, mobile applications demand more accurate locating and real time tracking, with limited impact on hardware complexity, network load and latency. Despite of remarkable research efforts put into this field by the scientific community, a common unique solution has not been adopted yet, due to the great variety of scenarios and application requirements. This paper focuses on the design and performance evaluation of Kalman filters for tracking a mobile target moving at low dynamics and for smoothing range estimations from noisy measurements. Some adaptive techniques to self-tune the filter and estimate the propagation model parameters are presented. One among the most promising adaptive algorithm presented is implemented in a real-life wireless sensor network test-bed including a mobile node. The resulting experimental results illustrate the benefits of this approach with respect to traditional multilateration based on least mean squares estimators.

[EN]: The suitability of the time-dependent density-functional theory (TDDFT) approach for the theoretical study of the optical properties of biomolecules is demonstrated by several examples. We critically discuss the limitations of available TDDFT implementations to address some of the present open questions in the description of the excited-state dynamics of biological complexes. The key objective of the present work is to address the performance of TDDFT in the linear response regime of the bio-molecular systems to the visible or near UV radiation - measured by, e.g. optical absorption or optical dichroism spectra. Although these spectra are essentially determined by the electronic degrees of freedom of small, optically active regions within the usually large biological systems, they can also be strongly influenced by environment effects (solvent, hosting protein, temperature, etc.). Moreover, many key biological processes consist of photo-induced dynamics (photoisomerisation, etc.), and their description requires a coupled treatment of electronic and nuclear degrees of freedom. We illustrate these aspects with a selection of paradigmatic biomolecular systems: chromophores in fluorescent proteins, porphyrins, DNA basis, the azobenzene dye, etc. To cite this article: A. Castro et al., C. R. Physique 10 (2009). © 2008., We acknowledge funding by the Deutsche Forschungsgemeinschaft through SPP 1093 and SFB 658, Spanish MEC (FIS2007-65702-C02-01) and Grupos Consolidados UPV/EHU of the Basque Country Government (2007), by the European Community through NoE Nanoquanta (NMP4-CT-2004-500198), SANES (NMP4-CT-2006-017310), ANR (Project NT0S-3_43900), DNA-NANODEVICES (IST-2006-029192) and NANO-ERA Chemistry projects, UPV/EHU (SGIker Arina) and the European Community through e-I3 ETSF project (Contract Number 211956). M.A.L.M. acknowledges partial support by the Portuguese FCT through the project PTDC/FIS/73578/2006.

This paper proposes a complete system for nodes localization in a Wireless Sensor Network (WSN) based on the ZigBee standard. The system includes a real-time location engine, which adopts a Received Signal Strength Indicator (RSSI)-based localization algorithm, and three tools, namely an Environment Description Tool (EDT), a Channel Modeling Tool (CMT) and a Network Planning Tool (NPT), which enable efficient deployment and accurate operation. Experimental evaluations show how the system performs in a real environment and how the proposed approach improves localization accuracy.

In the description of the interaction between electrons beyond the classical Hartree picture, bare exchange often yields a leading contribution. Here we discuss its effect on optical spectra of solids, comparing three different frameworks: time-dependent Hartree-Fock, a recently introduced combined density-functional and Green's functions approach applied to the bare exchange self-energy, and time-dependent exact-exchange within time-dependent density-functional theory (TD-EXX). We show that these three approximations give rise to identical excitonic effects in solids; these effects are drastically overestimated for semiconductors. They are partially compensated by the usual overestimation of the quasiparticle band gap within Hartree-Fock. The physics that lacks in these approaches can be formulated as screening. We show that the introduction of screening in TD-EXX indeed leads to a formulation that is equivalent to previously proposed functionals derived from Many-Body Perturbation Theory. It can be simulated by reducing the long-range part of the Coulomb interaction: this produces absorption spectra of semiconductors in good agreement with experiment., Comment: 12 pages, 3 figures, 1 table

This chapter presents several signal processing strategies to combine together, in a seamless estimation process, position-related measurements coming from different technologies and/or systems (e.g., TOA and TDOA measurements in terrestrial networks, TOA and RSS measurements, or even satellite and terrestrial systems, or satellite and inertial navigation systems). This approach, generally indicated as “hybridization”, promises to provide better accuracy with respect to its stand-alone counterparts, or better availability thanks to the diversity of the employed technologies. For example, hybridization between satellite and inertial systems is expected to compensate for the respective fragilities of the two systems, namely the relatively high error variance of the former and the drift of the latter. The mathematical framework where hybridization is developed is Bayesian filtering: the generic structure is reviewed and the well-known Kalman filter and its variants are inserted in the framework, with examples of applications to positioning problems. Then the particle filter approach is explained, with its most used variants. Examples of hybrid localization algorithms are then shown, starting from a hybrid terrestrial architecture, then passing to the architectures that blend GNSS and inertial measurements, using either the Kalman filter approach or the direct position estimation approach. Finally, an example of hybrid localization based on GNSS and peer-to-peer terrestrial signaling is presented.