6x3 Microstrip Beam Forming Network for Multibeam Triangular Array

A six inputs and three outputs structure which can be used to obtain six simultaneous beams with a triangular array of 3 elements is presented. The beam forming network is obtained combining balanced and unbalanced hybrid couplers and allows to obtain six main beams with sixty degrees of separation in azimuth direction. Simulations and measurements showing the performance of the array and other detailed results are presented

On-chip Monitoring: A Light-Weight Interconnection Network Approach

Current nanometer technologies are subjected to several adverse effects that seriously impact the yield and performance of integrated circuits. Such is the case of within-die parameters uncertainties, varying workload conditions, aging, temperature, etc. Monitoring, calibration and dynamic adaptation have appeared as promising solutions to these issues and many kinds of monitors have been presented recently. In this scenario, where systems with hundreds of monitors of different types have been proposed, the need for light-weight monitoring networks has become essential. In this work we present a light-weight network architecture based on digitization resource sharing of nodes that require a time-to-digital conversion. Our proposal employs a single wire interface, shared among all the nodes in the network, and quantizes the time domain to perform the access multiplexing and transmit the information. It supposes a 16% improvement in area and power consumption compared to traditional approaches.

Performance of Scheduling Policies in Adversarial Networks with Non-synchronized Clocks

In this paper we generalize the Continuous Adversarial Queuing Theory (CAQT) model (Blesa et al. in MFCS, Lecture Notes in Computer Science, vol. 3618, pp. 144–155, 2005) by considering the possibility that the router clocks in the network are not synchronized. We name the new model Non Synchronized CAQT (NSCAQT). Clearly, this new extension to the model only affects those scheduling policies that use some form of timing. In a first approach we consider the case in which although not synchronized, all clocks run at the same speed, maintaining constant differences. In this case we show that all universally stable policies in CAQT that use the injection time and the remaining path to schedule packets remain universally stable. These policies include, for instance, Shortest in System (SIS) and Longest in System (LIS). Then, we study the case in which clock differences can vary over time, but the maximum difference is bounded. In this model we show the universal stability of two families of policies related to SIS and LIS respectively (the priority of a packet in these policies depends on the arrival time and a function of the path traversed). The bounds we obtain in this case depend on the maximum difference between clocks. This is a necessary requirement, since we also show that LIS is not universally stable in systems without bounded clock difference. We then present a new policy that we call Longest in Queues (LIQ), which gives priority to the packet that has been waiting the longest in edge queues. This policy is universally stable and, if clocks maintain constant differences, the bounds we prove do not depend on them. To finish, we provide with simulation results that compare the behavior of some of these policies in a network with stochastic injection of packets.

Performance of artificial neural networks and genetical evolved artificial neural networks unfolding techniques

With the Bonner spheres spectrometer neutron spectrum is obtained through an unfolding procedure. Monte Carlo methods, Regularization, Parametrization, Least-squares, and Maximum Entropy are some of the techniques utilized for unfolding. In the last decade methods based on Artificial Intelligence Technology have been used. Approaches based on Genetic Algorithms and Artificial Neural Networks have been developed in order to overcome the drawbacks of previous techniques. Nevertheless the advantages of Artificial Neural Networks still it has some drawbacks mainly in the design process of the network, vg the optimum selection of the architectural and learning ANN parameters. In recent years the use of hybrid technologies, combining Artificial Neural Networks and Genetic Algorithms, has been utilized to. In this work, several ANN topologies were trained and tested using Artificial Neural Networks and Genetically Evolved Artificial Neural Networks in the aim to unfold neutron spectra using the count rates of a Bonner sphere spectrometer. Here, a comparative study of both procedures has been carried out.

Improving Wishart Classification of Polarimetric SAR Data Using the Hopfield Neural Network Optimization Approach.

This paper proposes the optimization relaxation approach based on the analogue Hopfield Neural Network (HNN) for cluster refinement of pre-classified Polarimetric Synthetic Aperture Radar (PolSAR) image data. We consider the initial classification provided by the maximum-likelihood classifier based on the complex Wishart distribution, which is then supplied to the HNN optimization approach. The goal is to improve the classification results obtained by the Wishart approach. The classification improvement is verified by computing a cluster separability coefficient and a measure of homogeneity within the clusters. During the HNN optimization process, for each iteration and for each pixel, two consistency coefficients are computed, taking into account two types of relations between the pixel under consideration and its corresponding neighbors. Based on these coefficients and on the information coming from the pixel itself, the pixel under study is re-classified. Different experiments are carried out to verify that the proposed approach outperforms other strategies, achieving the best results in terms of separability and a trade-off with the homogeneity preserving relevant structures in the image. The performance is also measured in terms of computational central processing unit (CPU) times.

Neural network controller for active demand side management with PV energy in the residential sector

In this paper, we describe the development of a control system for Demand-Side Management in the residential sector with Distributed Generation. The electrical system under study incorporates local PV energy generation, an electricity storage system, connection to the grid and a home automation system. The distributed control system is composed of two modules: a scheduler and a coordinator, both implemented with neural networks. The control system enhances the local energy performance, scheduling the tasks demanded by the user and maximizing the use of local generation.

Citizens Interactive Behaviour in the Performance of the Urban Space of Cohabitacion. Interactive Atlas of Urban Habitability

The article shows a range of contemporary phenomena linked with urban space and the increasing citizens? interactivity in the network. The sources for theory and reflection are related to the ongoing research project ?Interactive Atlas of urban habitability" which is based on citizen participation in the sensitive description of the urban environment. It addresses a classification of variables related to the desires of urban habitability.

On the design and measurement of a novel non-orthogonal multi-beam network for triangular arrays of three radiating elements

An innovative dissipative multi-beam network for triangular arrays of three radiating elements is proposed. This novel network provides three orthogonal beams in θ0 elevation angle and a fourth one in the broadside steering direction. The network is composed of 90º hybrid couplers and fixed phase shifters. In this paper, a relation between network components, radiating element distance and beam steering directions will be shown. Application of the proposed dissipative network to the triangular cells of three radiating elements that integrate the intelligent antenna GEODA will be exhibited. This system works at 1.7 GHz, it has a 60º single radiating element beamwidth and a distance between array elements of 0.57 λ. Both beam patterns, theoretical and simulated, obtained with the network will be depicted. Moreover, the whole system, dissipative network built with GEODA cell array, has been measured in the anechoic chamber of the Radiation Group of Technical University of Madrid, demonstrating expected performance.

Study of a new 4×3 beam forming network for triangular arrays of three radiating elements

An innovative dissipative multi-beam network for triangular arrays of three radiating elements is proposed. This novel network provides three orthogonal beams in θ0 elevation angle and a fourth one in the broadside steering direction. The network is composed of 90º hybrid couplers and fixed phase shifters. In this paper, a relation between network components, radiating element distance and beam steering directions will be shown. Application of the proposed dissipative network to the triangular cells of three radiating elements that integrate the intelligent antenna GEODA will be exhibited. This system works at 1.7 GHz, it has a 60º single radiating element beamwidth and a distance between array elements of 0.57λ. Both beam patterns, theoretical and simulated, obtained with the network will be depicted. Moreover, the whole system, dissipative network built with GEODA cell array, has been measured in the anechoic chamber of the Radiation Group of Technical University of Madrid, demonstrating expected performance

Simulation Tool and Case Study for Planning Wireless Sensor Network

In this paper, a simulation tool for assisting the deployment of wireless sensor network is introduced and simulation results are verified under a specific indoor environment. The simulation tool supports two modes: deterministic mode and stochastic mode. The deterministic mode is environment dependent in which the information of environment should be provided beforehand. Ray tracing method and deterministic propagation model are employed in order to increase the accuracy of the estimated coverage, connectivity and routing; the stochastic mode is useful for large scale random deployment without previous knowledge on geographic information. Dynamic Source Routing protocol (DSR) and Ad hoc On-Demand Distance Vector Routing protocol (AODV) are implemented in order to calculate the topology of WSN. Hence this tool gives direct view on the performance of WSN and assists users in finding the potential problems of wireless sensor network before real deployment. At the end, a case study is realized in Centro de Electronica Industrial (CEI), the simulation results on coverage, connectivity and routing are verified by the measurement.

Assessment of troughput performance under NS2 in Mobile Ad Hoc Networks (MANETs)

Providing QoS in the context of Ad Hoc networks includes a very wide field of application from the perspective of every level of the architecture in the network.In order for simulation studies to be useful, it is very important that the simulation results match as closely as possible with the test bed results. In this Paper, we study the throughput performance (parameter QoS) in Mobile Ad Hoc Networks (MANETs) and compares emulated test bed results with simulation results from NS2 (Network Simulator). The performance of the Mobile Ad Hoc Networks is very sensitive to the number of users and the offered load. When the number of users/offered load is high then the collisions increase resulting in larger wastage of the medium and lowering overall throughput. The aim of this research is to compare the throughput of Mobile Ad Hoc Networks using three different scenarios: 97, 100 and 120 users (nodes) using simulator NS2. By analyzing the graphs in MANETs, it is concluded When the number of users o nodes is increased beyond the certain limit, throughput decreases.

Evaluating alternative industrial network organizations and information systems

Purpose – The purpose of this paper is to present a simulation‐based evaluation method for the comparison of different organizational forms and software support levels in the field of supply chain management (SCM). Design/methodology/approach – Apart from widely known logistic performance indicators, the discrete event simulation model considers explicitly coordination cost as stemming from iterative administration procedures. Findings - The method is applied to an exemplary supply chain configuration considering various parameter settings. Curiously, additional coordination cost does not always result in improved logistic performance. Influence factor variations lead to different organizational recommendations. The results confirm the high importance of (up to now) disregarded dimensions when evaluating SCM concepts and IT tools. Research limitations/implications – The model is based on simplified product and network structures. Future research shall include more complex, real world configurations. Practical implications – The developed method is designed for the identification of improvement potential when SCM software is employed. Coordination schemes based only on ERP systems are valid alternatives in industrial practice because significant investment IT can be avoided. Therefore, the evaluation of these coordination procedures, in particular the cost due to iterations, is of high managerial interest and the method provides a comprehensive tool for strategic IT decision making. Originality/value – Reviewed literature is mostly focused on the benefits of SCM software implementations. However, ERP system based supply chain coordination is still widespread industrial practice but associated coordination cost has not been addressed by researchers.

How network operators can enhance ambient assisted living applications through next generation networks

Within the technological framework of Information and Communication Technologies (ICT), consumers are currently requesting multimedia services with simplicity of use, reliability, security and service availability through mobile and fixed access. Network operators are proposing the Next Generation Networks (NGN) to address the challenges of providing both services and network convergence. Apart from these considerations, there is a need to provide social and healthcare assistance services in order to support the progressive aging in the elderly population. In order to achieve this objective, the Ambient Assisted Living (AAL) initiative proposes ICT systems and services to promote autonomy and an independent life among the elderly. This paper describes the design and implementation of a group of services, called “service enablers”, which helps AAL applications to be supported in NGN. The presented enablers are identified to support the teleconsulting applications requirements in an NGN environment, involving the implementation of a virtual waiting room, a virtual whiteboard, a multimedia multiconference and a vital-signs monitoring presence status. A use case is defined and implemented to evaluate the developed enablers' performance.

BatNet: an implementation of a 6LoWPAN sensor and actuator network

This demo presents BatNet, a 6LoWPAN Wireless Transducer Network, in a Home Automation context. Its suitability for such application is shown by means of several performance and usability tests.

Predicting EQ-5D from the Parkinson's disease questionnaire PDQ-8 using multi-dimensional Bayesian network classifiers

The impact of the Parkinson's disease and its treatment on the patients' health-related quality of life can be estimated either by means of generic measures such as the european quality of Life-5 Dimensions (EQ-5D) or specific measures such as the 8-item Parkinson's disease questionnaire (PDQ-8). In clinical studies, PDQ-8 could be used in detriment of EQ-5D due to the lack of resources, time or clinical interest in generic measures. Nevertheless, PDQ-8 cannot be applied in cost-effectiveness analyses which require generic measures and quantitative utility scores, such as EQ-5D. To deal with this problem, a commonly used solution is the prediction of EQ-5D from PDQ-8. In this paper, we propose a new probabilistic method to predict EQ-5D from PDQ-8 using multi-dimensional Bayesian network classifiers. Our approach is evaluated using five-fold cross-validation experiments carried out on a Parkinson's data set containing 488 patients, and is compared with two additional Bayesian network-based approaches, two commonly used mapping methods namely, ordinary least squares and censored least absolute deviations, and a deterministic model. Experimental results are promising in terms of predictive performance as well as the identification of dependence relationships among EQ-5D and PDQ-8 items that the mapping approaches are unable to detect