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.     

Data‐based design of robust fault detection and isolation residuals via LASSO optimization and Bayesian filtering

In this paper, a data‐based approach for the design of structured residual subsets for the robust isolation of sensor faults is proposed. Linear regression models are employed to estimate faulty signals and to build a set of primary residuals. L₁‐regularized least squares estimation is used to identify model parameters and to enforce sparsity of the solutions by increasing the regularization weight. In this way, it is possible to generate a set of residuals generators with different fault sensitivity. Then, a residual selection procedure based on fault sensitivity maximization is proposed to extract a minimum size subset of structured residuals that allows for isolation of the faulty sensor. To overcome modelling uncertainty, a robust recursive Bayesian Filter has been employed to process, online, the distance of the residuals from nominal fault directions, providing a fault probability for each sensor. The proposed method has been validated by designing and testing a fault isolation scheme for six aircraft sensors using multi‐flight experimental data of a P92 Tecnam aircraft.     

中等传输距离下的无线功率传输链路第1部分:实现工作状态最优化

中程无线功率传输(WPT)可以采用几种不同的方式实现,如通过电感或电容耦合、谐振或非谐振网络实现.本文主要研究了通过感应耦合谐振器实现的WPT链路,而且只着重研究了利用2个谐振器的链路(直接链路)并工作在主谐振频率下的情况.研究结果表明,当工作在主谐振频率下,可以根据网络参数来对传输效率或负载功率进行优化.     

TGI-Simulator: a visual tool to support the preclinical phase of the drug discovery process by assessing in silico the effect of an anticancer drug

This paper presents TGI-Simulator, a software tool designed to show, through a 2-D graphical animation, the simulated time effect of an anticancer drug on a tumor mass by exploiting the well-known Tumor Growth Inhibition (TGI) model published by Simeoni et al. [1]. Simeoni TGI model is a mathematical model routinely used by pharma companies and researchers during the drug development process. The application is based on a Java graphical user interface (GUI) including a self installing differential equation solver implemented in Matlab together with an optimization algorithm that performs model identification via Weighted Least Squares (WLS). However, it can graphically show also the simulation results obtained within other scientific software tools, if they are preventively stored into a suitable ASCII file. The tool would be a valid support also for researchers with no specific skills in scientific calculations and in pharmacokinetic and pharmacodynamic modeling but daily involved in pharma companies drug development processes at different levels. The availability of a movie with a temporal varying 2-D iconographic representation is an original instrument to communicate results and learn Simeoni TGI model and its potential application in preclinical studies.     

Temporal aggregation on user-defined granularities

Time-varying data play a major role in many applications, and, starting from the 80’s, they have been widely studied in temporal databases. In the last two decades, several researchers have shown that, to deal with many application domains, user-defined temporal granularities must be coped with. When data are stored at multiple user-defined temporal granularities, the task of defining proper conversion functions to aggregate data from an origin granularity (e.g., business days) to a task granularity (e.g., months) is of primary importance. However, current temporal database approaches mostly demand such a task to system administrators, or to specific applications, providing no methodology or general guideline to accomplish it. In this paper, we propose a general and application-independent methodology which, on the basis of the temporal relationship between two user-defined granularities, provides users with a set of conversion/aggregation functions between them, consistent with the telic vs. atelic character of the data to be aggregated. The correctness of the approach is also proved.