Multifunctional Metamaterial Microwave Blackbody with High-Frequency Compatibility,Temperature Insensitivity,and Structural Scalability

Compared with optical black, few attempts have focused on achieving broadband microwave blackbodies. In this study, all-ceramic metamaterial microwave blackbodies are created by integrating a graded Gyroid shellular (GGS) metastructure design with additive manufacturing of polymer-derived SiOC (PDCs-SiOC) ceramics encapsulated by Si₃N₄ (SiOC@Si₃N₄). Hardly influenced by the destructive interference effect, as-fabricated GGS-structured SiOC@Si₃N₄ microwave blackbodies demonstrate a broadband microwave absorption (MA) above 83.6% (91.3% on average) across the entire X-Ku band and encompassing higher frequencies above 18 GHz as well, together with the temperature insensitivity from room temperature to 500 °C. Based on the flexible electromagnetic tunability of PDCs-SiOC, exceptional structural scalability is experimentally validated for metal-doped modified CuSiOC and CoSiOC substrates with the same GGS metastructures, retaining high-efficiency MA capability. Furthermore, attachment of perfectly reflecting metal backplanes further enhances the MA performance, with an ultrawide MA exceeding 67.9% (89.1% on average) achievable at 2.95–18 GHz for CoSiOC substrate. Meanwhile, the GGS-structured SiOC@Si₃N₄ metamaterials possess additional multifunctional properties, such as good noise reduction performance as well as ultrahigh wear resistance. As a proof of concept, this study provides important guidance on achieving multifunctional coupling broadband MA characteristics by fully tapping the application potential of existing materials.     

Simulation of Entanglement Dynamics for Scattering Between a Free and a Bound Carrier in a Quantum Wire

The decoherence of a quantum system is ascribed to its enetanglement with another system considered as the environment, thus the quantitative evaluation of entanglement formation dynamics can shed light on the transition between quantum and classical behavior of a carrier that undergoes to a scattering event. We present here a numerical solution of the time-dependent 1D Schroedinger equation of a two-particle system consisting of a free carrier scattered by a bound one. The real-space entanglement between them is computed, at different times, for various initial conditions. The maximum entanglement corresponds to equal probability of transmission and reflection of the free particle.     

Virtual inspector: a flexible visualizer for dense 3D scanned models.

Virtual inspector lets novice users inspect dense 3D models at interactive frame rates on commodity PCs. The system obtains visualization efficiency without sacrificing quality by adopting a continuous level-of-detail representation. Visual inspector's use of XML to encode the GUI's structure and behavior makes it flexible and configurable. We can improve the virtual inspector system by adding new functionality and increasing its efficiency. Few restorers would consider the simple visualization of a digital 3D replica as the ultimate goal for the use of 3D scanning technologies in cultural heritage contexts. Once we can visualize an artifact with great accuracy, the need to map other data on the 3D model will rise. We're working on a slightly extended version of the tool to support mapping and selective visualization of different sources of surface data. We're also developing tools to compute measures. Finally, we're working to more dynamically enrich the data linked to the mesh by letting users add annotations or link multimedia material to selected points of the artifact surface. Our goal is to transform virtual inspector into a more dynamic instrument for cultural heritage research and restoration.     

Service-oriented middleware for distributed data mining on the grid

Distribution of data and computation allows for solving larger problems and executing applications that are distributed in nature. The grid is a distributed computing infrastructure that enables coordinated resource sharing within dynamic organizations consisting of individuals, institutions, and resources. The grid extends the distributed and parallel computing paradigms allowing for resource negotiation and dynamical allocation, heterogeneity, open protocols, and services. Grid environments can be used both for compute-intensive tasks and data intensive applications by exploiting their resources, services, and data access mechanisms. Data mining algorithms and knowledge discovery processes are both compute and data intensive, therefore the grid can offer a computing and data management infrastructure for supporting decentralized and parallel data analysis. This paper discusses how grid computing can be used to support distributed data mining. Research activities in grid-based data mining and some challenges in this area are presented along with some promising future directions for developing grid-based distributed data mining.     

Dynamic and context-aware streaming adaptation to smooth quality degradation due to IEEE 802.11 performance anomaly

The need for application-level context visibility to properly perform streaming service management in wired-wireless integrated networks is widely recognized. In particular, the paper claims the need for full application-level awareness of context data about the IEEE 802.11 performance anomaly, i.e., when even a single node located at the borders of the coverage area of a Wi-Fi access point produces a relevant degradation in the connectivity quality of all other nodes in the area. We propose a middleware that on the one hand portably predicts and detects anomaly situations via decentralized and lightweight client-side mechanisms and, on the other hand, exploits anomaly awareness to promptly react with application-level management operations (streaming quality downscaling and traffic shaping). In particular, the paper focuses on how our middleware performs anomaly-driven quality downscaling both to preserve the goodput at nodes in well-covered areas and to minimize quality degradations at the clients generating the anomaly. The reported experimental results point out how anomaly prediction/detection can relevantly improve the effectiveness of streaming downscaling, thus allowing to maintain acceptable service quality notwithstanding Wi-Fi anomaly occurrences.

Optimal input design for set-membership identification of Hammerstein models

In this paper the problem of optimal input design for the identification of Hammerstein models is considered under the assumption that the linear dynamic part of the model is a FIR and that lower and upper bounds are available for the additive measurement errors. The parameters of the Hammerstein model can then be estimated via the identification of a linearized augmented Hammerstein model . External approximations of the feasible intervals for the parameters of the original Hammerstein models are then derived (which may correspond to the actual feasible intervals). This paper deals with the design of input sequences minimizing parameter uncertainty for the linearized augmented Hammerstein model . Some new results are also reported about optimal input design for polynomial non-linear blocks, that may be part of Hammerstein models.     

Altimeter observations of the MJO/ENSO connection through Kelvin waves

Altimeter‐derived Pacific Ocean sea surface height anomaly (SSHA) data are used to confirm the relationship between the Madden Julian Oscillation (MJO) and El Niño Southern Oscillation (ENSO), through Kelvin waves, previously identified in sea surface temperature (SST) data. The altimeter data, filtered for Kelvin waves, have been cross‐correlated with MJO indices, as an alternative way of exploring and quantifying the possible connection between the MJO and ENSO. The results of the cross‐correlations of the SSHA filtered data and the MJO indices generally show higher values in the periods preceding the three ENSO warm events and lower values during, and for a short time after, these events. The significance of this correlation pattern appears to link the MJO to the ENSO warm events, through Kelvin waves. Whether this can be used for predictive purposes needs to be confirmed by further studies.     

TMS for multimodal information processing

Many working processes are complex and composed by heterogeneous atomic tasks, e.g. editing, assembling data from different sources (as databases or laboratory's devices) with texts, images or learning objects, or submitting them to software components to retrieve information, to render them, re-format, submit to computations, and other types of information processing. All these processes heavily require procedural knowledge which is tacit as owned by experts of the working activity; they are complex and are extremely difficult to be modeled and automatized without having a flexible, multimodular evolutionary system in place. Support to information from different modalities increases the performance of a computer system originally designed for a task with a unimodular nature. In this paper, we discuss the idea of task management system (TMS) as a component-based system which offers a virtual workbench to search, acquire, describe and assemble computational agents performing single autonomous tasks into working processes. We sustain that TMS is a cutting edge platform to develop software solutions for problems related to workflow automatization and design. The architecture we propose follows the conceptual track of the TMS to allow composition and arrangement of atomic modules into a complex system. A configuration of the workflow can be implemented and extended with a set of task/components, chunks of activities which are considered basic elements of the workflow. By interacting with the TMS in editing mode, the workflow designer selects the relevant chunks from system repositories, drags them into a working system area and assembles them into a working process. As the main actor of the system, the workflow designer is provided with an environment resembling an artisan’s workshop, to let her/him select the relevant chunks from system repositories, drags them into a working area and assembles them into a working TMS instance, which represents the working process. Global interaction modality of the TMS instance is moulded and specialized on the base of the specific modalities of the task/components which have been retrieved from the system repositories and each time negotiated. Complex activities could be formally described, implemented and applied with a consequent advantage for personnel re-organization toward more conceptual activities.     

Augmented reality technologies,systems and applications

This paper surveys the current state-of-the-art of technology, systems and applications in Augmented Reality. It describes work performed by many different research groups, the purpose behind each new Augmented Reality system, and the difficulties and problems encountered when building some Augmented Reality applications. It surveys mobile augmented reality systems challenges and requirements for successful mobile systems. This paper summarizes the current applications of Augmented Reality and speculates on future applications and where current research will lead Augmented Reality’s development. Challenges augmented reality is facing in each of these applications to go from the laboratories to the industry, as well as the future challenges we can forecast are also discussed in this paper. Section 1 gives an introduction to what Augmented Reality is and the motivations for developing this technology. Section 2 discusses Augmented Reality Technologies with computer vision methods, AR devices, interfaces and systems, and visualization tools. The mobile and wireless systems for Augmented Reality are discussed in Section 3. Four classes of current applications that have been explored are described in Section 4. These applications were chosen as they are the most famous type of applications encountered when researching AR apps. The future of augmented reality and the challenges they will be facing are discussed in Section 5.