Research on multi-degree-of-freedom neurons with weighted graphs

In this paper, we redefine the sample points set in the feature space from the point of view of weighted graph and propose a new covering model - Multi-Degree-of-Freedorn Neurons (MDFN). Base on this model, we describe a geometric learning algorithm with 3-degree-of-freedom neurons. It identifies the sample points secs topological character in the feature space, which is different from the traditional "separation" method. Experiment results demonstrates the general superiority of this algorithm over the traditional PCA+NN algorithm in terms of efficiency and accuracy.

Modeling the effect of ozone loss on photobleaching of chromophoric dissolved organic matter in the St. Lawrence estuary

Temporal trends in total ozone for the St. Lawrence estuary were estimated from ground-based measurements at the NOAA/CMDL station in Caribou, Maine. Linear regression analysis showed that from 1979 to 1999 total ozone has decreased by about 3.3% per decade on an annual basis and ≤6.2% per decade on a monthly basis relative to unperturbed (pre-CFC) levels. The influence of increased ultraviolet-B (280–320 nm) radiation associated with ozone depletion on water column photochemical processes was evaluated by modeling the photobleaching of chromophoric dissolved organic material (CDOM). Linear regression analysis showed small (<0.5% per decade), but statistically significant upward trends in maximum noontime photobleaching rates. Most notably, positive trends in relative rates for May, June, and July, when maximum absolute rates are expected, were predicted. A global model based on TOMS ozone data revealed increases in photobleaching of ≤3% per decade at high latitudes in the Southern Hemisphere. Radiation amplification factors for increases in photochemically weighted UV (280–400 nm) in response to ozone depletion were estimated at 0.1 and 0.08 for photobleaching of CDOM absorbance at 300 and 350 nm, respectively. Application of the laboratory-based model to conditions that more closely resembled those in situ were variable with both overestimation and underestimation of measured rates. The differences between modeled rates and observed rates under quasi-natural conditions were as large or larger than the predicted increases due to ozone depletion. These comparisons suggest that biological activity and mixing play an important, but as yet ill-defined, role in modifying photochemical processes.

SEARCH FOR THE BASIC REGULARITIES OF THE TRANSITION EMISSION OF EUROPIUM(II) ION IN COMPLEX FLUORIDES USING PATTERN-RECOGNITION

The relationship between structures of complex fluorides and spectral structure of Eu(II) ion in complex fluorides (AB(m)F(n)) is investigated by means of pattern recognition methods, such as KNN, ALKNN, BAYES, LLM, SIMCA and PCA. A learning set consisting of 32 f-f transition emission host compounds and 31 d-f transition emission host compounds and a test set consisting of 27 host compounds were characterized by 12 crystal structural parameters. These parameters, i.e. features, were reduced from 12 to 6 by multiple criteria for the classification of these host compounds as f-f transition emission or d-f transition emission. A recognition rate from 79.4 to 96.8% and prediction capabilities from 85.2 to 92.6% were obtained. According to the above results, the spectral structures of Eu(II) ion in seven unknown host lattices were predicted.

Asymptotic weighted-periodicity of the impulsive parabolic equation with time delay

The main aim of this paper is to investigate the effects of the impulse and time delay on a type of parabolic equations. In view of the characteristics of the equation, a particular iteration scheme is adopted. The results show that Under certain conditions on the coefficients of the equation and the impulse, the solution oscillates in a particular manner-called "asymptotic weighted-periodicity".

Modifying weighted fuzzy subsethood-based rule models with fuzzy quantifiers

K. Rasmani and Q. Shen. Modifying weighted fuzzy subsethood-based rule models with fuzzy quantifiers. Proceedings of the 13th International Conference on Fuzzy Systems, pages 1679-1684, 2004

Weighted and two-stage least squares estimation of semiparametric truncated regression models

This paper provides a root-n consistent, asymptotically normal weighted least squares estimator of the coefficients in a truncated regression model. The distribution of the errors is unknown and permits general forms of unknown heteroskedasticity. Also provided is an instrumental variables based two-stage least squares estimator for this model, which can be used when some regressors are endogenous, mismeasured, or otherwise correlated with the errors. A simulation study indicates that the new estimators perform well in finite samples. Our limiting distribution theory includes a new asymptotic trimming result addressing the boundary bias in first-stage density estimation without knowledge of the support boundary. © 2007 Cambridge University Press.

Iterative inversion of experimental data in weighted spaces

We present iterative algorithms for solving linear inverse problems with discrete data and compare their performances with the method of singular function expansion, in view of applications in optical imaging and particle sizing.

The Use of Singular Systems and other Inversion Methods in Weighted L2- spaces

info:eu-repo/semantics/published

Minimizing total weighted completion time in a proportionate flow shop

We study the special case of the m machine flow shop problem in which the processing time of each operation of job j is equal to pj; this variant of the flow shop problem is known as the proportionate flow shop problem. We show that for any number of machines and for any regular performance criterion we can restrict our search for an optimal schedule to permutation schedules. Moreover, we show that the problem of minimizing total weighted completion time is solvable in O(n2) time. © 1998 John Wiley & Sons, Ltd.

A fully polynomial approximation scheme for the single machine weighted total tardiness problem with a common due date

We develop a fully polynomial-time approximation scheme (FPTAS) for minimizing the weighted total tardiness on a single machine, provided that all due dates are equal. The FPTAS is obtained by converting an especially designed pseudopolynomial dynamic programming algorithm.

Probabilistic approach in weighted Markov branching processes

This note provides a new probabilistic approach in discussing the weighted Markov branching process (WMBP) which is a natural generalisation of the ordinary Markov branching process. Using this approach, some important characteristics regarding the hitting times of such processes can be easily obtained. In particular, the closed forms for the mean extinction time and conditional mean extinction time are presented. The explosion behaviour of the process is investigated and the mean explosion time is derived. The mean global holding time and the mean total survival time are also obtained. The close link between these newly developed processes and the well-known compound Poisson processes is investigated. It is revealed that any weighted Markov branching process (WMBP) is a random time change of a compound Poisson process.

Two simple constant ratio approximation algorithms for minimizing the total weighted completion time on a single machine with a fixed non-availability interval

In this note, we consider the scheduling problem of minimizing the sum of the weighted completion times on a single machine with one non-availability interval on the machine under the non-resumable scenario. Together with a recent 2-approximation algorithm designed by Kacem [I. Kacem, Approximation algorithm for the weighted flow-time minimization on a single machine with a fixed non-availability interval, Computers & Industrial Engineering 54 (2008) 401–410], this paper is the first successful attempt to develop a constant ratio approximation algorithm for this problem. We present two approaches to designing such an algorithm. Our best algorithm guarantees a worst-case performance ratio of 2+ε. © 2008 Elsevier B.V. All rights reserved.

The effects of blood pressure lowering on development of cognitive impairment and dementia in patients without apparent prior cerebrovascular disease

BACKGROUND: Hypertension and cognitive impairment are prevalent in older people. It is known that hypertension is a direct risk factor for vascular dementia and recent studies have suggested hypertension also impacts upon prevalence of Alzheimer's disease. The question is therefore whether treatment of hypertension lowers the rate of cognitive decline. OBJECTIVES: To assess the effects of blood pressure lowering treatments for the prevention of dementia and cognitive decline in patients with hypertension but no history of cerebrovascular disease. SEARCH STRATEGY: The trials were identified through a search of CDCIG's Specialised Register, CENTRAL, MEDLINE, EMBASE, PsycINFO and CINAHL on 27 April 2005. SELECTION CRITERIA: Randomized, double-blind, placebo controlled trials in which pharmacological or non-pharmacological interventions to lower blood pressure were given for at least six months. DATA COLLECTION AND ANALYSIS: Two independent reviewers assessed trial quality and extracted data. The following outcomes were assessed: incidence of dementia, cognitive change from baseline, blood pressure level, incidence and severity of side effects and quality of life. MAIN RESULTS: Three trials including 12,091 hypertensive subjects were identified. Average age was 72.8 years. Participants were recruited from industrialised countries. Mean blood pressure at entry across the studies was 170/84 mmHg. All trials instituted a stepped care approach to hypertension treatment, starting with a calcium-channel blocker, a diuretic or an angiotensin receptor blocker. The combined result of the three trials reporting incidence of dementia indicated no significant difference between treatment and placebo (Odds Ratio (OR) = 0.89, 95% CI 0.69, 1.16). Blood pressure reduction resulted in a 11% relative risk reduction of dementia in patients with no prior cerebrovascular disease but this effect was not statistically significant (p = 0.38) and there was considerable heterogeneity between the trials. The combined results from the two trials reporting change in Mini Mental State Examination (MMSE) did not indicate a benefit from treatment (Weighted Mean Difference (WMD) = 0.10, 95% CI -0.03, 0.23). Both systolic and diastolic blood pressure levels were reduced significantly in the two trials assessing this outcome (WMD = -7.53, 95% CI -8.28, -6.77 for systolic blood pressure, WMD = -3.87, 95% CI -4.25, -3.50 for diastolic blood pressure).Two trials reported adverse effects requiring discontinuation of treatment and the combined results indicated a significant benefit from placebo (OR = 1.18, 95% CI 1.06, 1.30). When analysed separately, however, more patients on placebo in SCOPE were likely to discontinue treatment due to side effects; the converse was true in SHEP 1991. Quality of life data could not be analysed in the three studies. There was difficulty with the control group in this review as many of the control subjects received antihypertensive treatment because their blood pressures exceeded pre-set values. In most cases the study became a comparison between the study drug against a usual antihypertensive regimen. AUTHORS' CONCLUSIONS: There was no convincing evidence from the trials identified that blood pressure lowering prevents the development of dementia or cognitive impairment in hypertensive patients with no apparent prior cerebrovascular disease. There were significant problems identified with analysing the data, however, due to the number of patients lost to follow-up and the number of placebo patients given active treatment. This introduced bias. More robust results may be obtained by analysing one year data to reduce differential drop-out or by conducting a meta-analysis using individual patient data.