A fast and simple algorithm for computing the longest common subsequence of run-length encoded strings

Let X and Y be two strings of lengths n and m, respectively, and k and l, respectively, be the numbers of runs in their corresponding run-length encoded forms. We propose a simple algorithm for computing the longest common subsequence of two given strings X and Y in O(kl+min{p₁,p₂}) time, where p₁ and p₂ denote the numbers of elements in the bottom and right boundaries of the matched blocks, respectively. It improves the previously known time bound O(min{nl,km}) and outperforms the time bounds O(kllogkl) or O((k+l+q)log(k+l+q)) for some cases, where q denotes the number of matched blocks.     

Building Knowledge for Substation-Based Decision Support Using Rough Sets

This paper describes a new technique based on rough sets to extract decision rules from large volumes of data captured by protection, control, and monitoring intelligent electronic devices. The methodology correctly identifies faults from large datasets and could be used to assist operators in their decision-making processes. Building knowledge for a fault diagnostic system is a time-consuming and costly process. The quality of a knowledge base can sometimes be hampered by a large number of superfluous decision-making rules that can lead to an unnecessarily large knowledge base system and inefficient or even detrimental rule maintenance. The methodology proposed cannot only induce decision rules efficiently but can also reduce the size of the knowledge base without causing loss of useful information. Results can be used by an expert system to generate supervisory automation and to support operators, for example, during an emergency situation. This methodology involves the generation of human-machine interface alarms. These can then be used for diagnosis of the type and cause of a fault event to give suggestions for network restoration and post-emergency repair. A power systems computer aided design/electromagnetic transients including dc simulator has been used to investigate the effect of faults and switching actions on the protection and control equipment associated with a typical distribution network. The fundamental ideas of rough set theory are discussed, followed by a rule assessment method that is outlined using an illustrative example.     

Influence of nitrogen content on the pit formation and pit propagation in the welded joints of X5CrNi18-10 stainless steel

The influence of welding current and nitrogen content in argon shielding gas on the resistance of the welded joint (weld metal and heat-affected zone [HAZ]) of the stainless steel X5CrNi18-10 to the formation and growth of pits was investigated. Also, the susceptibility of the welded joint to intergranular corrosion was examined. Pitting corrosion resistance indicators were determined based on anodic potentiodynamic polarization measurements in NaCl + Na₂SO₄ solution, while susceptibility to intergranular corrosion was determined by the potentiokinetic method with a double loop (DL EPR). SEM/EDS was used to analyze the microstructure. It has been shown that higher nitrogen content in shielding gas leads to an increase in the resistance of welded joints (weld metal and HAZ) to the pit formation. However, an improvement in the resistance to the pit formation leads to a decline in the resistance of the welded joint to pit growth. An explanation of this phenomenon is proposed. Also, it was shown that the increase of the welding current increases the susceptibility of the welded joint to intergranular corrosion, while the higher nitrogen content has no effect.     

Glomerular haemodynamics during renal artery clamping and haemorrhage in the dog

The influence of gradual decline in renal perfusion pressure (RPP) due either to renal artery clamping (C) or to haemorrhagic hypotension (HH) was studied using micropuncture techniques in anaesthetized dogs. The decrease in renal blood flow (RBF) was more profound and set in earlier during HH than during C, where perfect autoregulation was observed down to a mean arterial blood pressure of 85 mmHg. Glomerular filtration rate (GFR) was also only slightly decreased during C, with no change in filtration fraction (FF); again, a much greater decrease in GFR with an increase in FF was seen in HH. The excretion of water, electrolytes and urea were also more decreased during HH than during C. Similar changes were seen at the single nephron (SN) level. Opposite changes were observed in arteriolar resistances: during C a decrease in total arteriolar resistance (RT) amounting to -22% at a RPP of 84 mmHg and -13% at 60 mmHg was seen, due exclusively to a drop in afferent resistance (RA), but during HH there was a significant increase in RT by +36% at RPP of 110 mmHg, +39% at 85 mmHg and +68% at 60 mmHg. This increase was mainly due to an increase in efferent resistance (RE) rather than in RA: +42 vs. +31%, respectively, at 110 mmHg and +67 vs +19% respectively, at 85 mmHg. It was not until a RPP of 60 mmHg was reached that this difference between RE and RA disappeared, being +67% for RE and +69% for RA. The ultrafiltration coefficient, Kf, did not change during C and only decreased slightly with the biggest drop in RPP during HH (2.84 microliters mmHg-1 min-1 during HH vs. 4.19 microliters mmHg-1 min-1 before HH). The SNGFR/GFR ratio remained unchanged during C but declined with decreasing RPP during HH, which probably indicates a 'redistribution' of RBF to the deeper regions of the renal cortex. In conclusion, major differences in renal function were observed between C and HH whose cause is unknown.     

A Comparison of Digital Algorithms Used in Computing the Derivative of Left Ventricular Pressure

Five commonly used algorithms for digital differentiation are evaluated to determine how they perform in the presence of 8, 12, and 16 bit quantization noise. The algorithms are compared on the basis of rms error between a model derivative of the left ventricular pressure waveform and the approximate results of each algorithm. Algorithms based on interpolating techniques introduced the least amount of error when 16 bit data were used while algorithms based on least-squares data fit methods performed best on the less accurate 8 bit data. Some of the band-limiting characteristics of the algorithms are also discussed.     

Analytic solution of the anisotropic bidomain equations for myocardial tissue: the effect of adjoining conductive regions

The anisotropic bidomain model for the propagation of electrical activation in the human myocardium H consists of coupled elliptic-parabolic partial differential equations for the transmembrane potential Vm, intracellular potential phi(i), and extracellular potential phi(e) in H, together with quasi-static equations for the potential distribution phiB in the surrounding (passive) isotropic extracardiac regions B. Four local parameters sigma((i,e) (l,t)) specify the conductivities in the longitudinal (l) and transverse (t) directions with respect to cardiac muscle fibers. Continuous current flow is required at the interface S(H) between H and B. We derive analytic formulas for Vm, phi(e), phi(i), and phiB for plane wave propagation in a uniformly anisotropic slab surmounted by a homogeneous region of conductivity sigmaB. No assumptions are required regarding the anisotropy ratios of the conductivity coefficients. The properties of these solutions are examined with a view to providing insight into the effect of the passive region B on the propagation of Vm and phi(e) in H. We show that for a suitably chosen boundary condition, the problem can be reduced to solving the bidomain equations in H alone.