Medical challenges of internal conflicts

The most prevalent menace since the end of the cold war is the occurrence of civil wars and local and regional conflicts. The term "low intensity conflict" describes the new threat environment and covers a multitude of phenomena, such as civil wars, guerrilla warfare, terrorism and counterinsurgency operations occurring between routine, peaceful inter- or intrastate competition, and a sustained conventional conflict. There is a great challenge to alert the physicians in general, and the surgical community of the world in particular, to the new threat environment and the medical challenges involved in treating casualties of low intensity conflicts. Specifically, a new international body of surgeons might be required to coordinate the recruitment, training, and creditation for surgeons with special expertise in the management of victims of such conflicts and to facilitate research and general knowledge of the medical challenges of modern conflicts.     

Spatiotemporal imaging of human brain activity using functional MRI constrained magnetoencephalography data: Monte Carlo simulations

The goal of our research is to develop an experimental and analytical framework for spatiotemporal imaging of human brain function. Preliminary studies suggest that noninvasive spatiotemporal maps of cerebral activity can be produced by combining the high spatial resolution (millimeters) of functional MRI (fMRI) with the high temporal resolution (milliseconds) of electroencephalography (EEG) and magnetoencephalography (MEG). Although MEG and EEG are sensitive to millisecond changes in mental activity, the ability to resolve source localization and timing is limited by the ill-posed "inverse" problem. We conducted Monte Carlo simulations to evaluate the use of MRI constraints in a linear estimation inverse procedure, where fMRI weighting, cortical location and orientation, and sensor noise statistics were realistically incorporated. An error metric was computed to quantify the effects of fMRI invisible ("missing") sources, "extra" fMRI sources, and cortical orientation errors. Our simulation results demonstrate that prior anatomical and functional information from MRI can be used to regularize the EEG/MEG inverse problem, giving an improved solution with high spatial and temporal resolution. An fMRI weighting of approximately 90% was determined to provide the best compromise between separation of activity from correctly localized sources and minimization of error caused by missing sources. The accuracy of the estimate was relatively independent of the number and extent of the sources, allowing for incorporation of physiologically realistic multiple distributed sources. This linear estimation method provides an operator-independent approach for combining information from fMRI, MEG, and EEG and represents a significant advance over traditional dipole modeling.     

Ultrarapid metabolizers of debrisoquine: characterization and PCR-based detection of alleles with duplication of the CYP2D6 gene

During a six-month period 2,221 haemocultures obtained from patients hospitalized in the Faculty Hospital Olomouc were examined. In all 304 isolated bacteria the sensitivity was assessed by the standard dilution micromethod and moreover all positive haemocultures were examined the "direct" disc method. Agreement between the results of the two methods was proved in 84% of pairs of tests and within a range from 67 to 100%, depending on the type of antimicrobial preparation. Based on these findings it may be stated that assessment of the sensitivity by the "direct" method agrees significantly with assessment of the sensitivity according to minimal inhibitory concentrations (MIC). In patients with septicaemia this procedure makes it possible to change empirical antibiotherapy by 24 hours sooner to aimed therapy.     

Selection of industrial robots using compromise ranking and outranking methods

Selection of a robot for a specific industrial application is one of the most challenging problems in real time manufacturing environment. It has become more and more complicated due to increase in complexity, advanced features and facilities that are continuously being incorporated into the robots by different manufacturers. At present, different types of industrial robots with diverse capabilities, features, facilities and specifications are available in the market. Manufacturing environment, product design, production system and cost involved are some of the most influencing factors that directly affect the robot selection decision. The decision maker needs to identify and select the best suited robot in order to achieve the desired output with minimum cost and specific application ability. This paper attempts to solve the robot selection problem using two most appropriate multi-criteria decision-making (MCDM) methods and compares their relative performance for a given industrial application. The first MCDM approach is ‘VIsekriterijumsko KOmpromisno Rangiranje’ (VIKOR), a compromise ranking method and the other one is ‘ELimination and Et Choice Translating REality’ (ELECTRE), an outranking method. Two real time examples are cited in order to demonstrate and validate the applicability and potentiality of both these MCDM methods. It is observed that the relative rankings of the alternative robots as obtained using these two MCDM methods match quite well with those as derived by the past researchers.     

A new social and momentum component adaptive PSO algorithm for image segmentation

In this paper, we present a new variant of Particle Swarm Optimization (PSO) for image segmentation using optimal multi-level thresholding. Some objective functions which are very efficient for bi-level thresholding purpose are not suitable for multi-level thresholding due to the exponential growth of computational complexity. The present paper also proposes an iterative scheme that is practically more suitable for obtaining initial values of candidate multilevel thresholds. This self iterative scheme is proposed to find the suitable number of thresholds that should be used to segment an image. This iterative scheme is based on the well known Otsu’s method, which shows a linear growth of computational complexity. The thresholds resulting from the iterative scheme are taken as initial thresholds and the particles are created randomly around these thresholds, for the proposed PSO variant. The proposed PSO algorithm makes a new contribution in adapting ‘social’ and ‘momentum’ components of the velocity equation for particle move updates. The proposed segmentation method is employed for four benchmark images and the performances obtained outperform results obtained with well known methods, like Gaussian-smoothing method (Lim, Y. K., & Lee, S. U. (1990). On the color image segmentation algorithm based on the thresholding and the fuzzy c-means techniques. Pattern Recognition, 23, 935–952; Tsai, D. M. (1995). A fast thresholding selection procedure for multimodal and unimodal histograms. Pattern Recognition Letters, 16, 653–666), Symmetry-duality method (Yin, P. Y., & Chen, L. H. (1993). New method for multilevel thresholding using the symmetry and duality of the histogram. Journal of Electronics and Imaging, 2, 337–344), GA-based algorithm (Yin, P. -Y. (1999). A fast scheme for optimal thresholding using genetic algorithms. Signal Processing, 72, 85–95) and the basic PSO variant employing linearly decreasing inertia weight factor.     

User-input driven QoS management in ad hoc networks

Though the network quality-of-service (QoS) metrics are defined in terms of technical parameters (e.g., delay, jitter, bandwidth), they are rather subjective when it comes to the end user. Oftentimes, the end user finds it difficult to express his desired QoS in such technical parameters, though he has a fair idea of what QoS he desires. In this paper, we show how translation functions can be devised and used to translate the user inputs to networking parameters that are used by various layers of the protocol stack. In particular, we consider an ad hoc network and show an interface design that uses translation functions to map user supplied inputs to parameters at the medium access control (MAC) and routing layers. These parameters, in turn, choose the right strategies that particular layer functionality can adopt, such that the QoS desired by the user is achieved. We also compute the associated costs due to the different strategies adopted. We implement the interface on ns-2 and conduct simulation experiments with randomly scattered IEEE 802.11 enabled nodes. Results show the functionality of the interface and demonstrate how delay, throughput, and network lifetime are affected when the end user seeks different levels of QoS.     

Experimental characterization of piezoelectrically actuated micromachined silicon valveless micropump

In this paper, performance of piezoelectrically actuated pyramidal valveless micropumps is studied experimentally in detail. Valveless micropumps based on silicon and glass substrate are fabricated using MEMS technology. Two different sizes of micropumps having overall dimensions of 5 mm × 5 mm × 1 mm and 10 mm × 10 mm × 1 mm are fabricated and characterized. In the fabricated micropumps, the thickness of silicon diaphragm is <20 µm which gives the advantage of operating pump at low voltage with excellent stability and consistency. The performance of micropumps in terms of flowrate and backpressure is evaluated for a wide range of driving frequency and actuating voltages. The maximum flowrate of water in the 10-mm micropump is 355 µl/min and backpressure of 3.1 kPa at zero flowrate for an applied voltage of 80 V at frequency 1.05 kHz. The reported micropumps have low footprint, high flowrate and backpressure. Thus, these micropumps are especially suited for biological applications as these can withstand adequate amount of backpressure. Comparative study of the performance of these micropumps with those available in the literature brings out the efficacy of these micropumps.     

Complexity of points-to analysis of Java in the presence ofexceptions

At each program point, points-to analysis for statically typed object oriented programming languages (e.g., Java, C++) determines those objects to which a reference may refer (or a pointer may point) during execution. Points-to analysis is necessary for any semantics based software tools for object oriented systems. Our new complexity results for points-to analysis distinguish the difficulty of intraprocedural and interprocedural points-to analyses for languages with combinations of single-level types (i.e., types with data members only of primitive type), exceptions with or without subtyping, and dynamic dispatch. Our results include: 1) the first polynomial-time algorithm for points-to analysis in the presence of exceptions that handles a robust subset of Java without threads and can be applied to C++; 2) proof that the above algorithm is safe, in general, and provably precise on programs with single-level types and exceptions without subtyping, but not dynamic dispatch, thus, this case is in P; 3) proof that an interprocedural points-to analysis problem with single-level types and exceptions with subtyping, but without dynamic dispatch, is PSPACE-hard, while the intraprocedural problem is PSPACE-complete. Other complexity characterizations of points-to analysis in programs without exceptions are presented, including an algorithm with worst-case bound of O(n⁵ ), which improves over the O(n⁷) worst-case bound achievable from previous approaches of T. Reps et al. (1995) and W.A. Landi and B.G. Ryder (1991)