A radiomics pipeline dedicated to Breast MRI: validation on a multi-scanner phantom study

Magnetic Resonance Materials in Physics, Biology and Medicine - Quantitative analysis in MRI is challenging due to variabilities in intensity distributions across patients, acquisitions and...     

Characterization of stabilized porous magnetite core–shell nanogel composites based on crosslinked acrylamide/sodium acrylate copolymers

Stabilized and dispersed superparamagnetic porous nanogels based on sodium acrylate (AA‐Na) and acrylamide (AM) in a surfactant‐free aqueous system were synthesized via solution polymerization at room temperature. The formation of magnetite nanoparticles was confirmed and their properties characterized using Fourier transform infrared spectroscopy. Extensive characterization of the magnetic polymer particles using transmission electron microscopy (TEM), dynamic light scattering and zeta potential measurements revealed that Fe₃O₄ nanoparticles were incorporated into the shells of poly(AM/AA‐Na). The average particle size was 5–8 nm as determined from TEM. AM/AA‐Na nanoparticles with a diameter of about 11 nm were effectively assembled onto the negatively charged surface of the as‐synthesized Fe₃O₄ nanoparticles via electrostatic interaction. Crosslinked magnetite nanocomposites were prepared by in situ development of surface‐modified magnetite nanoparticles in an AM/AA‐Na hydrogel. Scanning electron microscopy was used to study the surface morphology of the prepared composites. The morphology, phase composition and crystallinity of the prepared nanocomposites were characterized. Atomic force microscopy and argon adsorption–desorption measurements of Fe₃O₄.AM/AA indicated that the architecture of the polymer network can be a hollow porous sphere or a solid phase, depending on the AA‐Na content. © 2013 Society of Chemical Industry     

What is computation?

Three conditions are usually given that must be satisfied by a process in order for it to be called a computation, namely, there must exist a finite length algorithm for the process, the algorithm must terminate in finite time for valid inputs and return a valid output and, finally, the algorithm must never return an output for invalid inputs. These three conditions are advanced as being necessary and sufficient for the process to be computable by a universal model of computation. In fact, these conditions are neither necessary nor sufficient. On the one hand, recently defined paradigms show how certain processes that do not satisfy one or more of the aforementioned properties can indeed be carried out in principle on new, more powerful, types of computers, and hence can be considered as computations. Thus, the conditions are not necessary. On the other hand, contemporary work in unconventional computation has demonstrated the existence of processes that satisfy the three stated conditions, yet contradict the Church–Turing thesis and, more generally, the principle of universality in computer science. Thus, the conditions are not sufficient.     

Cellular automaton-based algorithms for the dispersion of mobile wireless sensor networks

Due to the advent of sensor technology and its applications, mobile wireless sensor networks (MWSNs) have gained a significant amount of research interest. In a typical MWSN, sensors can move within the network. We develop a set of probabilistic and deterministic cellular automaton (CA)-based algorithms for motion planning problems in MWSNs. First, we consider a scenario where a group of sensors are deployed and they need to disperse in order to maximise the area covered by the network. In this variant of the problem we do not explicitly consider that the sensors should maintain the connectivity of the network while they move. Second, we consider a scenario where the sensors are initially randomly distributed and they need to disperse autonomously to both maximise the coverage of the network and maintain its connectivity. We carry out extensive simulations of both deterministic and randomised variants of the algorithms. For the first variant of the problem we compare our algorithms with one previous algorithm and find that our algorithm yields better network coverage than the earlier algorithm. We also find that probabilistic algorithms have better overall performance for the second variant. CA algorithms rely only on local information about the network and, hence, they can be used in practice for MWSN problems. On the other hand, locality of the algorithm implies that maintaining connectivity becomes a non-trivial problem.     

Feature selection by interactive clustering

The results of experiments with a novel criterion for absolute non-parametric feature selection are reported. The basic idea of the new technique involves the use of computer graphics and the human pattern recognition ability to interactively choose a number of features, this number not being necessarily determined in advance, from a larger set of measurements. The triangulation method, recently proposed in the cluster analysis literature for mapping points from l-space to 2-space, is used to yield a simple and efficient algorithm for feature selection by interactive clustering. It is shown that a subset of features can thus be chosen which allows a significant reduction in storage and time while still keeping the probability of error in classification within reasonable bounds.     

Efficient virtual reality design of quiet underwater shells

Abstract Efficient computational tools are developed to model, visualize, and feel the structural-acoustics of shells in a virtual reality environment. These tools aim at building the structural-acoustic models of shells from an array of basic building blocks including: beams, shells, and stiffeners. The concepts of finite element analysis, sub-structuring, model reduction, meta-modeling, and parallel computations form the main steps to be followed for building simplified computational models of complex shell systems. The resulting models are particularly suitable for the efficient application of multi-criteria optimization techniques in order to select the optimal design parameters of these complex shell systems. The developed integrated analysis tools enable the engineers to design complex systems in a cost effective and a timely manner. Furthermore, engineers will be immersed in an audio-visually coupled tele-operated environment whereby direct interaction and control of the design process can be achieved. In this manner, the behavior of synthetic models of shells can be monitored by literally walking through the shell and adjusting its design parameters as needed to ensure optimal performance while satisfying design and operational requirements. For example, engineers can move electronic wands to vary the number, size, type, and location of stiffeners in the shell, monitor the resulting structural-acoustic visually or by haptic feedback and simultaneously listen to the radiated sound pressure field. Such manipulations of the virtual shells in the scene are carried out while the engineer is navigating through and around the shell to ensure that the vibration and sound levels, at any critical locations, are within the acceptable limits. The developed integrated approach also serves as a means for virtual training of students and engineers on designing and operating complex smart structures on the site as well as through collaborative efforts with other virtual reality sites. Such unique capability will enable engineers to design prototypes of expensive vehicles without building them. Examples of these vehicles include aircraft, submersibles, torpedoes, and others that can share this virtual experience and can be profoundly impacted upon by the proposed approach. The presented optimal design approach is implemented in the Virtual Reality CAVE Laboratory at the University of Maryland that is controlled by an eight parallel processor Silicon Graphics Infinite Reality (ONYX2) computer.