MELOC-X: extended memory and location optimized caching for large mobile ad hoc networks of UAVs

Effective caching in mobile ad hoc network increases data availability. However, caching at strategic locations with reduced (controlled) number of copies is needed for many military applications involving UAVs to address security concerns, less maintenance overhead and maintaining availability. In general, existing cooperative caching approaches are deficient in finding the reduced number of strategic cache locations. One such technique to reduce the number of strategic cache locations without affecting the efficacy of data access for a small network topology of UAVs is called “memory and location optimized caching scheme (MELOC)”. However, having a single broker and metadata broadcast across the whole network in MELOC lead to severe performance hindrance in case of a large network topology of UAVs. Moreover, frequent cache replacements due to a change in network topology do not favor cache hit and bandwidth conservation in case of large mobile networks consisting of UAVs. In this paper, we design and evaluate an extended version of “MELOC called MELOC-X”, which suits large network topologies of UAVs by overcoming the above challenges. Our comparison with one such recent scheme with similar objectives showcased a significant improvement in performance. We also evaluate the impact of this scheme with respect to different metrics including the average number of hops, the average roundtrip time (i.e., average query latency), cache hits and mobility to access cached data through extensive simulations.     

Bridging the gap: effect of text query reformulation in multimodal retrieval

Multimedia Tools and Applications - Multimodal Retrieval provides new paradigms and methods aimed at effectively searching through the enormous volume of data. Multimodal retrieval is a well...     

Automatic identification of cattle using muzzle point pattern: a hybrid feature extraction and classification paradigm

Multimedia Tools and Applications - Animal biometrics is an emerging research field that develops quantified methodologies for representing and detecting the visual appearances of animal based on...     

Derivative free algorithm for solving nonlinear equations

In this work, we develop a simple yet practical algorithm for constructing derivative free iterative methods of higher convergence orders. The algorithm can be easily implemented in software packages for achieving desired convergence orders. Convergence analysis shows that the algorithm can develop methods of various convergence orders which is also supported through the numerical work. Computational results ascertain that the developed algorithm is efficient and demonstrate equal or better performance as compared with other well known methods.     

Uncountable automatic classes and learning

In this paper we consider uncountable classes recognizable by ω-automata and investigate suitable learning paradigms for them. In particular, the counterparts of explanatory, vacillatory and behaviourally correct learning are introduced for this setting. Here the learner reads in parallel the data of a text for a language L from the class plus an ω-index α and outputs a sequence of ω-automata such that all but finitely many of these ω-automata accept the index α if and only if α is an index for L.It is shown that any class is behaviourally correct learnable if and only if it satisfies Angluin’s tell-tale condition. For explanatory learning, such a result needs that a suitable indexing of the class is chosen. On the one hand, every class satisfying Angluin’s tell-tale condition is vacillatorily learnable in every indexing; on the other hand, there is a fixed class such that the level of the class in the hierarchy of vacillatory learning depends on the indexing of the class chosen.We also consider a notion of blind learning. On the one hand, a class is blind explanatorily (vacillatorily) learnable if and only if it satisfies Angluin’s tell-tale condition and is countable; on the other hand, for behaviourally correct learning, there is no difference between the blind and non-blind version.This work establishes a bridge between the theory of ω-automata and inductive inference (learning theory).     

Generation of Efficient Nested Loops from Polyhedra

Automatic parallelization in the polyhedral model is based on affine transformations from an original computation domain (iteration space) to a target space-time domain, often with a different transformation for each variable. Code generation is an often ignored step in this process that has a significant impact on the quality of the final code. It involves making a trade-off between code size and control code simplification/optimization. Previous methods of doing code generation are based on loop splitting, however they have nonoptimal behavior when working on parameterized programs. We present a general parameterized method for code generation based on dual representation of polyhedra. Our algorithm uses a simple recursion on the dimensions of the domains, and enables fine control over the tradeoff between code size and control overhead.     

Is team training in briefings for surgical teams feasible in simulation?

We developed a module for surgical team training using briefings in simulated crisis scenarios and here we report preliminary findings. Nine surgical teams (34 trainees) participated in a pre-training simulation, followed by an interactive workshop on briefing and checklists, and then a post-training simulation. Both technical and non-technical skills were assessed via observation during simulations by expert trainers who provided feedback on performances at the end of simulation. Trainees also reported their attitudes to briefings and evaluated the training. Pre-training attitudes to briefing were positive, some of which improved post-training and trainees’ evaluation of the training was positive. Surgeons’ technical skill improved significantly post-training, but their decision-making skill was rated lower than other non-technical skills, compared to other trainees. The training did not appear to greatly improve non-technical skill performance. Training surgical teams in simulation is feasible but much more work is needed on measurement development and training strategy to confirm its efficacy and utility.     

Advanced networking services for distributed multimedia streaming applications

Increased network speeds coupled with new services delivered via the Internet have increased the demand for intelligence and flexibility in network systems. This paper argues that both can be provided by new hardware platforms comprised of heterogeneous multi-core systems with specialized communication support. We present and evaluate an experimental network service platform that uses an emergent class of devices—network processors—as its communication support, coupled via a dedicated interconnect to a host processor acting as a computational core. A software infrastructure spanning both enables the dynamic creation of application-specific services on the network processor, mediated by middleware and controlled by kernel-level communication support. Experimental evaluations use a Pentium IV-based computational core coupled with an IXP 2400 network processor. The sample application services run on both include an image manipulation application and application-level multicasting.

Identification of Pd3+ ions in zeolite L by temperature programmed reduction and electron paramagnetic resonance spectroscopy

Pd supported on KL zeolite has been studied by temperature programmed reduction (TPR) and electron paramagnetic resonance (EPR) spectroscopy. It has been found that upon calcination in pure oxygen Pd³⁺ and Pd²⁺ ions are formed; the Pd³⁺ ions are identified by their EPR signal. As Pd³⁺ ions in the cancrinite cages are difficult to reduce, the H₂ consumption in conventional TPR is below the stoichiometric amount.