High-efficiency and wide-bandwidth performance obtainable from atwo-input buck converter

A study of the two-input post-regulators is carried out in this paper. In these post-regulators, only a part of the total power undergoes a switching conversion process, whereas the remainder of the power comes up to the load directly, with no power conversion process. Due to this fact, very high efficiency is achieved. Moreover, the stress in the semiconductors and the filter size are both much lower than in standard post-regulators. Two-input post-regulators require two-output main converters. However, many converter topologies can be easily adapted to supply two-output voltages with no efficiency penalty. Two-input postregulators can be used in many power converters. Multiple-output DC-to-DC converters and AC-to-DC power factor correctors are two good examples     

New recovery error indicator for adaptive finite-element analysis on waveguiding structures

The adaptive finite-element method (FEM) is an iterative variant of the FEM where, in a first step, an initial mesh with few and low-order elements is generated, the corresponding algebraic problem is solved and the error in the solution is estimated in order to add degrees of freedom in those regions of the domain with the biggest error estimation. This process is repeated until an ending condition is reached. The two basic stages in this method are the error indication and the mesh enrichment. In this paper, within the analysis of waveguiding structures, a new error indicator based on the curl recovery is described. In addition, an overview on refinement techniques is presented, and the h-refinement employed in this study is briefly described. Results obtained with the curl-recovery indicator are discussed and compared with the classical nonadaptive FEM and two previously developed error indicators: the residual and flux continuity indicators.     

Assessment of a Web-Based Water Information System Performance in the Context of Groundwater Governance

Water Resources Management - Portugal recently faced a severe financial crisis that led to the suspension of funding for water monitoring programmes of the Portuguese National Water Resources...     

Cache-conscious run-time decomposition of data parallel computations

Multi-core architectures feature an intricate hierarchy of cache memories, with multiple levels and sizes. To adequately decompose an application according to the traits of a particular memory hierarchy is a cumbersome task that may be rewarded with significant performance gains. The current state-of-the-art in memory hierarchy-aware parallel computing delegates this endeavour on the programmer, demanding from him deep knowledge of both parallel programming and computer architecture. In this paper, we propose the shifting of these memory hierarchy-related concerns to the run-time system, which then takes on the responsibility of distributing the computation’s data across the target memory hierarchy. We evaluate our approach from a performance perspective, comparing it against the common cache-neglectful data decomposition strategy.     

Contextual Policy Search for Linear and Nonlinear Generalization of a Humanoid Walking Controller

We investigate learning of flexible robot locomotion controllers, i.e., the controllers should be applicable for multiple contexts, for example different walking speeds, various slopes of the terrain or other physical properties of the robot. In our experiments, contexts are desired walking linear speed of the gait. Current approaches for learning control parameters of biped locomotion controllers are typically only applicable for a single context. They can be used for a particular context, for example to learn a gait with highest speed, lowest energy consumption or a combination of both. The question of our research is, how can we obtain a flexible walking controller that controls the robot (near) optimally for many different contexts? We achieve the desired flexibility of the controller by applying the recently developed contextual relative entropy policy search(REPS) method which generalizes the robot walking controller for different contexts, where a context is described by a real valued vector. In this paper we also extend the contextual REPS algorithm to learn a non-linear policy instead of a linear policy over the contexts which call it RBF-REPS as it uses Radial Basis Functions. In order to validate our method, we perform three simulation experiments including a walking experiment using a simulated NAO humanoid robot. The robot learns a policy to choose the controller parameters for a continuous set of forward walking speeds.     

Animal‐borne wireless network: Remote imaging of community ecology

This article describes the design, construction, and field‐testing of a standalone networked animal‐borne monitoring system conceived to study community ecology remotely. The system consists of an assemblage of identical battery‐powered sensing devices with wireless communication capabilities that are each collar‐mounted on a study animal and together form a mobile ad hoc network. The sensing modalities of each device include high‐definition video, inertial accelerometry, and location resolved via a global positioning system module. Our system is conceived to use information exchange across the network to enable the devices to jointly decide without supervision when and how to use each sensing modality. The ultimate goal is to extend battery life while making sure that important events are appropriately documented. This requires judicious use of highly informative but power‐hungry sensing modalities, such as video, because battery capacity is constrained by stringent weight and dimension restrictions. We have proposed algorithms to regulate sensing rates, data transmission among devices, and triggering for video recording based on location and animal group movements and configuration. We have also developed the hardware and firmware of our devices to reliably execute these algorithms in the exacting conditions of real‐life deployments. We describe validation of the performance and reliability of our system using deployment results for a mission in Gorongosa National Park (Mozambique) to monitor two species in their natural habitat: the waterbuck and the African buffalo. We present movement data and snapshots of animal point‐of‐view videos collected by 14 fully operational devices collared on 10 waterbucks and 4 buffaloes.     

Hydroxyapatite Reinforced Chitosan and Polyester Blends for Biomedical Applications

Summary: Hydroxyapatite, chitosan, and aliphatic polyester were compounded using a twin‐screw extruder. The polyesters include poly(ε‐caprolactone) (PCL), poly(lactic acid) , poly(butylene succinate) (PBS), and poly(butylene terephthalate adipate). The mass fraction of chitosan ranged from 17.5 to 45%, while that of HA ranged from 10 to 30%. These blends were injection molded and evaluated for thermal, morphological, and mechanical properties. The addition of hydroxyapatite decreased the crystallinity in chitosan/PBS blends, while in blends containing chitosan/PCL, the crystallinity increased. Addition of hydroxyapatite significantly decreased the tensile strength and elongation of polyester/hydroxyapatite composites as well as chitosan/polyester/hydroxyapatite composites with elongations undergoing decreases over an order of magnitude. The tensile strength of the composite was dictated by the adhesion of HA to the chitosan/polyester matrix. The tensile strength of composites containing hydroxyapatite could be predicted using the Nicolai and Narkis equation for weak filler adhesion (K ≈ 1.21). Tensile‐fractured and cryogenically‐fractured surface indicates extensive debonding of hydroxyapatite crystals from the matrix, indicating weak adhesion. The adhesion of hydroxyapatite was higher for pure polyester than those containing chitosan and polyester. The modulus of the composites registered modest increase. The two main diffraction peaks observed using WAXS are unaffected by the amount of chitosan or hydroxyapatite.

     

Mechanism and Convergence Analysis of a Multi-Robot Swarm Approach Based on Natural Selection

The Darwinian Particle Swarm Optimization (DPSO) is an evolutionary algorithm that extends the Particle Swarm Optimization (PSO) using natural selection, or survival-of-the-fittest, to enhance the ability to escape from local optima. An extension of the DPSO to multi-robot applications has been recently proposed and denoted as Robotic Darwinian PSO (RDPSO), benefiting from the dynamical partitioning of the whole population of robots. Therefore, the RDPSO decreases the amount of required information exchange among robots, and is scalable to large populations of robots. This paper presents a stability analysis of the RDPSO to better understand the relationship between the algorithm parameters and the robot’s convergence. Moreover, the analysis of the RDPSO is further extended for real robot constraints (e.g., robot dynamics, obstacles and communication constraints) and experimental assessment with physical robots. The optimal parameters are evaluated in groups of physical robots and a larger population of simulated mobile robots for different target distributions within larger scenarios. Experimental results show that robots are able to converge regardless of the RDPSO parameters within the defined attraction domain. However, a more conservative parametrization presents a significant influence on the convergence time. To further evaluate the herein proposed approach, the RDPSO is further compared with four state-of-the-art swarm robotic alternatives under simulation. It is observed that the RDPSO algorithm provably converges to the optimal solution faster and more accurately than the other approaches.     

Analysis of operating system diversity for intrusion tolerance

One of the key benefits of using intrusion‐tolerant systems is the possibility of ensuring correct behavior in the presence of attacks and intrusions. These security gains are directly dependent on the components exhibiting failure diversity. To what extent failure diversity is observed in practical deployment depends on how diverse are the components that constitute the system. In this paper, we present a study with operating system's (OS's) vulnerability data from the NIST National Vulnerability Database (NVD). We have analyzed the vulnerabilities of 11 different OSs over a period of 18 years, to check how many of these vulnerabilities occur in more than one OS. We found this number to be low for several combinations of OSs. Hence, although there are a few caveats on the use of NVD data to support definitive conclusions, our analysis shows that by selecting appropriate OSs, one can preclude (or reduce substantially) common vulnerabilities from occurring in the replicas of the intrusion‐tolerant system. Copyright © 2013 John Wiley & Sons, Ltd.