Computing Minimum Area Homologies

Calculating and categorizing the similarity of curves is a fundamental problem which has generated much recent interest. However, to date there are no implementations of these algorithms for curves on surfaces with provable guarantees on the quality of the measure. In this paper, we present a similarity measure for any two cycles that are homologous, where we calculate the minimum area of any homology (or connected bounding chain) between the two cycles. The minimum area homology exists for broader classes of cycles than previous measures which are based on homotopy. It is also much easier to compute than previously defined measures, yielding an efficient implementation that is based on linear algebra tools. We demonstrate our algorithm on a range of inputs, showing examples which highlight the feasibility of this similarity measure.     

Application of particle swarm optimization in epileptic spike EEG source localization

Surgical therapy has become an important therapeutic alternative for patients with medically intractable epilepsy. Correct and anatomically precise localization of an epileptic focus is essential to decide if resection of brain tissue is possible. The inverse problem in EEG-based source localization is to determine the location of the brain sources that are responsible for the measured potentials at the scalp electrodes. We propose a new global optimization method based on particle swarm optimization (PSO) to solve the epileptic spike EEG source localization inverse problem. In a forward problem a modified subtraction method is proposed to reduce the computational time. The good accuracy and fast convergence are demonstrated for 2D and 3D cases with realistic head models. The results from the new method are promising for use in the pre-surgical clinic in the future.     

Degree-Optimal Routing for P2P Systems

We define a family of Distributed Hash Table systems whose aim is to combine the routing efficiency of randomized networks—e.g. optimal average path length O(log ² n/δlog δ) with δ degree—with the programmability and startup efficiency of a uniform overlay—that is, a deterministic system in which the overlay network is transitive and greedy routing is optimal. It is known that Ω(log n) is a lower bound on the average path length for uniform overlays with O(log n) degree (Xu et al., IEEE J. Sel. Areas Commun. 22(1), 151–163, 2004). Our work is inspired by neighbor-of-neighbor (NoN) routing, a recently introduced variation of greedy routing that allows us to achieve optimal average path length in randomized networks. The advantage of our proposal is that of allowing the NoN technique to be implemented without adding any overhead to the corresponding deterministic network. We propose a family of networks parameterized with a positive integer c which measures the amount of randomness that is used. By varying the value c, the system goes from the deterministic case (c=1) to an “almost uniform” system. Increasing c to relatively low values allows for routing with asymptotically optimal average path length while retaining most of the advantages of a uniform system, such as easy programmability and quick bootstrap of the nodes entering the system. We also provide a matching lower bound for the average path length of the routing schemes for any c. This work was partially supported by the Italian FIRB project “WEB-MINDS” (Wide-scalE, Broadband MIddleware for Network Distributed Services), .     

Infrastructure Federation Through Virtualized Delegation of Resources and Services

Infrastructure federation is becoming an increasingly important issue for modern Distributed Computing Infrastructures (DCIs): Dynamic elasticity of quasi-static Grid environments, incorporation of special-purpose resources into commoditized Cloud infrastructures, cross-community collaboration for increasingly diverging areas of modern e-Science, and Cloud Bursting pose major challenges on the technical level for many resource and middleware providers. Especially with respect to increasing costs of operating data centers, the intelligent yet automated and secure sharing of resources is a key factor for success. With the D-Grid Scheduler Interoperability (DGSI) project within the German D-Grid Initiative, we provide a strategic technology for the automatically negotiated, SLA-secured, dynamically provisioned federation of resources and services for Grid-and Cloud-type infrastructures. This goal is achieved by complementing current DCI schedulers with the ability to federate infrastructure for the temporary leasing of resources and rechanneling of workloads. In this work, we describe the overall architecture and SLA-secured negotiation protocols within DGSI and depict an advanced mechanism for resource delegation through means of dynamically provisioned, virtualized middleware. Through this methodology, we provide the technological foundation for intelligent capacity planning and workload management in a cross-infrastructure fashion.     

High power devices in wide bandgap semiconductors

Silicon carbide (SiC) semiconductor devices for high power applications are now commercially available as discrete devices. Recently Schottky diodes are offered by both USA and Europe based companies. Active switching devices such as bipolar junction transistors (BJTs), field effect transistors (JFETs and MOSFETs) are now reaching the market. The interest is rapidly growing for these devices in high power and high temperature applications. The main advantages of wide bandgap semiconductors are their very hi...     

Branching and circular features in high dimensional data

Large observations and simulations in scientific research give rise to high-dimensional data sets that present many challenges and opportunities in data analysis and visualization. Researchers in application domains such as engineering, computational biology, climate study, imaging and motion capture are faced with the problem of how to discover compact representations of high-dimensional data while preserving their intrinsic structure. In many applications, the original data is projected onto low-dimensional space via dimensionality reduction techniques prior to modeling. One problem with this approach is that the projection step in the process can fail to preserve structure in the data that is only apparent in high dimensions. Conversely, such techniques may create structural illusions in the projection, implying structure not present in the original high-dimensional data. Our solution is to utilize topological techniques to recover important structures in high-dimensional data that contains non-trivial topology. Specifically, we are interested in high-dimensional branching structures. We construct local circle-valued coordinate functions to represent such features. Subsequently, we perform dimensionality reduction on the data while ensuring such structures are visually preserved. Additionally, we study the effects of global circular structures on visualizations. Our results reveal never-before-seen structures on real-world data sets from a variety of applications.     

Next generation remote critical care through service-oriented architectures: challenges and opportunities

Health care providers and governments are under pressure to maintain and improve the quality of care to an increasing volume of critical care patients at either end of the life cycle, namely premature and ill term babies together with the elderly. The provision of a service of critical care utilizing real time service-oriented architectures has the potential to enable clinicians to be supported in the care of a greater number patients that are, perhaps more importantly, located elsewhere to their intensive care units. This paper presents a review of recent research in the application of computing and IT to support the service of critical care and determines the trends and challenges for the application of real time service-oriented architectures within the domain. It then presents some case study–based research on the design of a service-oriented architecture-based approach to support two aspects of critical care namely elderly care and neonatal intensive care to provide further context to trends and opportunities.     

Strategies for increasing evaporative cooling during simulated desert patrol mission

The study evaluated the efficiency of two heat dissipation strategies under simulated desert patrol missions. Ten men participated in four trials, during which they walked on a treadmill (45°C, 20% relative humidity), carrying a load of 35 kg; two 50-min walks were separated by a 20-min rest. Cooling strategies, provided by an ambient air-ventilated vest (active cooling condition, AC), or water spraying of the skin during the rest (passive cooling condition, PC), in addition to reduced clothing and open zippers, were compared to conditions with full protective (FP) clothing and naked condition (NC). Skin temperature was higher during NC (37.9 ± 0.4°C; p < 0.001), and rectal temperature and heart rate were higher during FP (38.6 ± 0.4°C, p < 0.001 and 145 ± 12, p < 0.001, respectively), compared to other conditions. Four subjects terminated the trial prematurely due to signs of heat exhaustion in FP. Both cooling strategies substantially improved evaporative cooling.