The Combination of Multiple Classifiers Using an Evidential Reasoning Approach

In many domains when we have several competing classifiers available we want to synthesize them or some of them to get a more accurate classifier by a combination function. In this paper we propose a ‘class-indifferent’ method for combining classifier decisions represented by evidential structures called triplet and quartet, using Dempster's rule of combination. This method is unique in that it distinguishes important elements from the trivial ones in representing classifier decisions, makes use of more information than others in calculating the support for class labels and provides a practical way to apply the theoretically appealing Dempster–Shafer theory of evidence to the problem of ensemble learning. We present a formalism for modelling classifier decisions as triplet mass functions and we establish a range of formulae for combining these mass functions in order to arrive at a consensus decision. In addition we carry out a comparative study with the alternatives of simplet and dichotomous structure and also compare two combination methods, Dempster's rule and majority voting, over the UCI benchmark data, to demonstrate the advantage our approach offers. (A continuation of the work in this area that was published in IEEE Trans on KDE, and conferences)

Survival of Swiss-Webster mouse cerebellar granule neurons is promoted by a combination of potassium channel blockers

Cultured cerebellar granule neurons (CGN) are commonly used to assess neurotoxicity, but are routinely maintained in supraphysiological (25 mM) extracellular K⁺ concentrations [K⁺]_o. We investigated the effect of potassium channel blockade on survival of CGN derived from Swiss-Webster mice in supraphysiological (25 mM) and physiological (5.6 mM) [K⁺]_o. CGN were cultured for 5 days in 25 mM K⁺, then in 5.6 mM K⁺ or 25 mM K⁺ (control). Viability, assayed 24 h later by 3-(4,5-dimethylthiazolyl-2)-2,5-diphenyltetrazolium bromide (MTT) reduction and by lactate dehydrogenase (LDH) release, was ∼50% in 5.6 mM K⁺ versus 25 mM K⁺ (p < .001). Potassium channel blockers, 2 mM 4-aminopyridine (4-AP), 2 mM tetraethylammonium (TEA) or 1 mM Ba²⁺, individually afforded limited protection in 5.6 mM K⁺. However, survival in 5.6 mM K⁺ with a combination of 4-AP, TEA and Ba²⁺ was similar to survival in 25 mM K⁺ without blockers (p < .001 versus 5.6 mM K⁺ alone). CGN survival in 25 mM K⁺ was attenuated 25% by 2 μM nifedipine (p > .001), but nifedipine did not attenuate neuroprotection by K⁺ channel blockers. Together, these results suggest that the survival of CGN depends on the K⁺ permeability of the membrane rather than the activity of a particular type of K⁺ channel, and that the mechanism of neuroprotection by K⁺ channel blockers is different from that of elevated [K⁺]_o.

A new lead for nonpeptidic active-site-directed inhibitors of the severe acute respiratory syndrome coronavirus main protease discovered by a combination of screening and docking methods.

The coronavirus main protease, Mpro, is considered to be a major target for drugs suitable for combating coronavirus infections including severe acute respiratory syndrome (SARS). An HPLC-based screening of electrophilic compounds that was performed to identify potential Mpro inhibitors revealed etacrynic acid tert-butylamide (6a) as an effective nonpeptidic inhibitor. Docking studies suggested a binding mode in which the phenyl ring acts as a spacer bridging the inhibitor's activated double bond and its hydrophobic tert-butyl moiety. The latter is supposed to fit into the S4 pocket of the target protease. Furthermore, these studies revealed etacrynic acid amide (6b) as a promising lead for nonpeptidic active-site-directed Mpro inhibitors. In a fluorimetric enzyme assay using a novel fluorescence resonance energy transfer (FRET) pair labeled substrate, compound 6b showed a Ki value of 35.3 M. Since the novel lead compound does not target the S1', S1, and S2 subsites of the enzyme's substrate-binding pockets, there is room for improvement that underlines the lead character of compound 6b.

Rotational Molding Cycle Time Reduction Using a Combination of Physical Techniques

Rotational molding is a process used to manufacture hollow plastic products, and has been heralded as a molding method with great potential. Reduction of cycle times is an important issue for the rotational molding industry, addressing a significant disadvantage of the process. Previous attempts to reduce cycle times have addressed surface enhanced molds, internal pressure, internal cooling, water spray cooling, and higher oven air flow rates within the existing process. This article explores the potential benefits of these cycle time reduction techniques, and combinations of them. Recommendations on a best practice combination are made, based on experimental observations and resulting product quality. Applying the proposed molding conditions (i.e., a combination of surface-enhanced molds, higher oven flow rates, internal mold pressure, and water spray cooling), cycle time reductions of up to 70% were achieved. Such savings are very significant, inviting the rotomolding community to incorporate these techniques efficiently in an industrial setting. POLYM. ENG. SCI., 49:1846-1854, 2009. (C) 2009 Society of Plastics Engineers

Combination of CFD and DOE to analyze and improve the mass flow rate in urinary catheters

The urinary catheter is a thin plastic tube that has been designed to empty the bladder artificially, effortlessly, and with minimum discomfort. The current CH14 male catheter design was examined with a view to optimizing the mass flow rate. The literature imposed constraints to the analysis of the urinary catheter to ensure that a compromise between optimal flow, patient comfort, and everyday practicality from manufacture to use was achieved in the new design. As a result a total of six design characteristics were examined. The input variables in question were the length and width of eyelets 1 and 2 (four variables), the distance between the eyelets, and the angle of rotation between the eyelets. Due to the high number of possible input combinations a structured approach to the analysis of data was necessary. A combination of computational fluid dynamics (CFD) and design of experiments (DOE) has been used to evaluate the "optimal configuration." The use of CFD couple with DOE is a novel concept, which harnesses the computational power of CFD in the most efficient manner for prediction of the mass flow rate in the catheter. Copyright © 2009 by ASME.

Combination of CFD and DOE to analyse solid particle erosion in elbows

Solid particle erosion is a major concern in the engineering industry, particularly where transport of slurry flow is involved. Such flow regimes are characteristic of those in alumina refinement plants. The entrainment of particulate matter, for example sand, in the Bayer liquor can cause severe erosion in pipe fittings, especially in those which redirect the flow. The considerable costs involved in the maintenance and replacement of these eroded components led to an interest in research into erosion prediction by numerical methods at Rusal Aughinish alumina refinery, Limerick, Ireland, and the University of Limerick. The first stage of this study focused on the use of computational fluid dynamics (CFD) to simulate solid particle erosion in elbows. Subsequently an analysis of the factors that affect erosion of elbows was performed using design of experiments (DOE) techniques. Combining CFD with DOE harnesses the computational power of CFD in the most efficient manner for prediction of elbow erosion. An analysis of the factors that affect the erosion of elbows was undertaken with the intention of producing an erosion prediction model. © 2009 Taylor & Francis.

Adaptive linear combination of heuristic orderings in constructing examination timetables

In this paper, we investigate adaptive linear combinations of graph coloring heuristics with a heuristic modifier to address the examination timetabling problem. We invoke a normalisation strategy for each parameter in order to generalise the specific problem data. Two graph coloring heuristics were used in this study (largest degree and saturation degree). A score for the difficulty of assigning each examination was obtained from an adaptive linear combination of these two heuristics and examinations in the list were ordered based on this value. The examinations with the score value representing the higher difficulty were chosen for scheduling based on two strategies. We tested for single and multiple heuristics with and without a heuristic modifier with different combinations of weight values for each parameter on the Toronto and ITC2007 benchmark data sets. We observed that the combination of multiple heuristics with a heuristic modifier offers an effective way to obtain good solution quality. Experimental results demonstrate that our approach delivers promising results. We conclude that this adaptive linear combination of heuristics is a highly effective method and simple to implement.