Planetary exploration by robotic aerovehicles

Planetary aerobots are a new type of telerobotic science platform that can fly and navigate in a dynamic 3-dimensional atmospheric environment, thus enabling the global in situ exploration of planetary atmospheres and surfaces. Aerobots are enabled by a new concept in planetary balloon altitude control, developed at JPL, which employs reversible-fluid changes to permit repeated excursions in altitude. The essential physics and thermodynamics ofreversible-fluid altitude control have been demonstrated in a series of altitude-control experiments conducted in the Earth's atmosphere, which are described. Aerobot altitude-control technology will be important in the exploration of seven planets and satellites in our solar system. Three of these objects—Venus, Mars, and the Saturnian satellite Titan—have accessible solid surfaces and atmospheres dominated by the dense gases nitrogen or carbon dioxide. They will be explored with aerobots using helium or hydrogen as their primary means of buoyancy. The other four planets—Jupiter, Saturn, Uranus, and Neptune—have deep atmospheres that are predominantly hydrogen. It may be possible to explore these atmospheres with aerobots inflated with atmospheric gas that is then radiatively heated from the hotter gaseous depths below. To fulfill their potential, aerobots to explore the planets will need autonomous state estimators to guide their observations and provide information to the altitude-control systems. The techniques of acquiring these data remotely are outlined. Aerobots will also use on board altitude control and navigation systems to execute complex flight paths including descent to the surface and exploiting differential wind velocities to access different latitude belts. Approaches to control of these systems are examined. The application of aerobots to Venus exploration is explored in some detail: The most ambitious mission described, the Venus Flyer Robot (VFR), would have the capability to make repeated short excursions to the high-temperature surface environment of Venus to acquire data and then return to the Earth-like upper atmosphere to communicate and recool its electronic systems. Finally a Planetary Aerobot Testbed is discussed which will conduct Earth atmospheric flights to validate autonomous-state-estimator techniques and flight-path-control techniques needed for future planetary missions.     

First experiences of teaching quantum computing

The Journal of Supercomputing - Quantum computing is a reality that presents challenges to computer engineering students and practitioners. It has been claimed that it is possible to effectively...     

An algebraic approach to decoupling in linear multivariable systems

This paper examines the problem of decoupling designs for linear multivariable systems. Both partial and diagonal decoupling designs are considered. The development is based on an algebraic approach and the use of coprime factorizations, which provide a mechanism to account for key system properties including internal stability and decoupling invariants. The results obtained include necessary and sufficient conditions for decoupling and a parametrization of all decoupling controllers.     

New Results for Prediction of Chaotic Systems Using Deep Recurrent Neural Networks

Neural Processing Letters - Prediction of nonlinear and dynamic systems is a challenging task, however with the aid of machine learning techniques, particularly neural networks, is now possible to...     

Frequency domain design trade-offs for linear periodic feedback systems*

The purpose of this paper is to analyse inherent design limitations associated with systems that are linear and periodically time-varying. The contributions of the paper are (i) to relate frequency domain raising methods from signal processing literature to time-domain lifting used in control literature, and (ii) to develop extensions of the Poisson sensitivity and complementary sensitivity integral constraints. In particular, it is shown that there is generally an additional cost associated with having a time invariant target closed loop for a periodic open loop plant. It is also shown that design limitations due to unstable poles and/or non-minimum phase zeros of a discrete linear time-invariant plant remain even if a periodic time-varying controller is used. As a consequence, the utility of periodic control in circumventing design limitations is questioned.     

An Empirical Study on the Performance of Java/.Net Cryptographic APIs

ABSTRACT

The unprecedented growing demands on security and privacy protection ushered the proliferation of cryptographic tools. This article presents a study on the performance comparison of cryptographic Application Program Interfaces (APIs) that are implemented for the Java and the .Net frameworks. The results of the study clearly indicate the superiority of a set of commercial cryptographic APIs over its open-source counterpart.     

Collective intelligence as mechanism of medical diagnosis: The iPixel approach

Collective intelligence (CI) is an active field of research, which capitalizes the knowledge of human collectives in order to create, to innovate and to invent. There are two important mechanisms to implement CI: recommender and reputation systems. Recommender systems are used to provide filtered information from a large amount of elements. The recommendations are intended to provide interesting elements to users. Recommendation systems can be developed using different techniques and algorithms where the selection of these techniques depends on the area in which they will be applied. This work presents iPixel Recommender Engine, which is focused on the medical field. iPixel Recommendation Engine supports the process of differential diagnosis by recommending mammographic evaluations. Each mammogram is collectively tagged by the users’ community with a semantic sense; this feature allows iPixel acquires collective knowledge. iPixel can associate more than one feature with each mammogram. This work also presents a qualitative evaluation, where the basic features that a recommendation system should have in the medical field were obtained. Finally, a comparison was carried out with other similar recommender systems in order to know the Pixel advantages.     

F-MPJ: scalable Java message-passing communications on parallel systems

This paper presents F-MPJ (Fast MPJ), a scalable and efficient Message-Passing in Java (MPJ) communication middleware for parallel computing. The increasing interest in Java as the programming language of the multi-core era demands scalable performance on hybrid architectures (with both shared and distributed memory spaces). However, current Java communication middleware lacks efficient communication support. F-MPJ boosts this situation by: (1) providing efficient non-blocking communication, which allows communication overlapping and thus scalable performance; (2) taking advantage of shared memory systems and high-performance networks through the use of our high-performance Java sockets implementation (named JFS, Java Fast Sockets); (3) avoiding the use of communication buffers; and (4) optimizing MPJ collective primitives. Thus, F-MPJ significantly improves the scalability of current MPJ implementations. A performance evaluation on an InfiniBand multi-core cluster has shown that F-MPJ communication primitives outperform representative MPJ libraries up to 60 times. Furthermore, the use of F-MPJ in communication-intensive MPJ codes has increased their performance up to seven times.