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Specific Sample (specific + sample)
Selected AbstractsDecision-making method using a visual approach for cluster analysis problems; indicative classification algorithms and grouping scopeEXPERT SYSTEMS, Issue 3 2007Ran M. Bittmann Abstract: Currently, classifying samples into a fixed number of clusters (i.e. supervised cluster analysis) as well as unsupervised cluster analysis are limited in their ability to support ,cross-algorithms' analysis. It is well known that each cluster analysis algorithm yields different results (i.e. a different classification); even running the same algorithm with two different similarity measures commonly yields different results. Researchers usually choose the preferred algorithm and similarity measure according to analysis objectives and data set features, but they have neither a formal method nor tool that supports comparisons and evaluations of the different classifications that result from the diverse algorithms. Current research development and prototype decisions support a methodology based upon formal quantitative measures and a visual approach, enabling presentation, comparison and evaluation of multiple classification suggestions resulting from diverse algorithms. This methodology and tool were used in two basic scenarios: (I) a classification problem in which a ,true result' is known, using the Fisher iris data set; (II) a classification problem in which there is no ,true result' to compare with. In this case, we used a small data set from a user profile study (a study that tries to relate users to a set of stereotypes based on sociological aspects and interests). In each scenario, ten diverse algorithms were executed. The suggested methodology and decision support system produced a cross-algorithms presentation; all ten resultant classifications are presented together in a ,Tetris-like' format. Each column represents a specific classification algorithm, each line represents a specific sample, and formal quantitative measures analyse the ,Tetris blocks', arranging them according to their best structures, i.e. best classification. [source] Reversible transition between active and dormant microbial states in soilFEMS MICROBIOLOGY ECOLOGY, Issue 2-3 2001John Stenström Abstract The rate of respiration obtained in the substrate-induced respiration (SIR) method can be divided into the respiration rate of growing (r) and non-growing (K) microorganisms. The fraction of r is generally small (5,20%) in soils with no recent addition of substrates, but can be 100% in soils with high substrate availability. This suggests that substrate availability determines the proportion of biomass between these groups, and implies that transitions between them can take place reversibly. These hypotheses were tested by adding three different amounts of glucose which induced first-order, zero-order, and growth-associated respiration kinetics to three soils at four pre-incubation times (4, 12, 27, and 46 days) before the SIR measurement. An abiotic flush of CO2 in the SIR measurement was detected and corrected for before data analysis. Accumulated CO2 -C over 4 days after glucose addition, corrected for the respiration in unamended controls, corresponded to 41,50% mineralization of the glucose-C, and the relative amount mineralized by each soil was independent of the glucose amount added. The high glucose concentration gave an increased SIR, which reverted to the initial value within 27,46 days. In a specific sample, the maximum respiration rate induced during the pre-incubation, and the amount of organisms transformed from the K to the r state, as quantified in respiration rate units in the SIR measurement, were identical to each other, and these parameters were also highly correlated to the initial glucose concentration. The K,r transition was very fast, probably concurrent with the instantaneous increase in the respiration rate obtained by the glucose amendment. Thereafter, a slow first-order back-transition from the r to the K state ensued, with half-lives of 12, 23, and 70 days for the three soils. The results suggest the existence of community-level controls by which growth within or of the whole biomass is inhibited until it has been completely transformed into the r state. The data also suggest that the microbial specific activity is not related to the availability of exogenous substrate in a continuous fashion, rather it responds as a sharp transition between dormant and fully active. Furthermore, the inherent physiological state of the microbial biomass is strongly related to its history. It is proposed that the normal dynamics of the soil microbial biomass is an oscillation between active and dormant physiological states, while significant growth occurs only at substantial substrate amendment. [source] Designing Accurate Control Charts Based on the Geometric and Negative Binomial DistributionsQUALITY AND RELIABILITY ENGINEERING INTERNATIONAL, Issue 8 2005Neil C. Schwertman Abstract Attribute control charts are used effectively to monitor for process change. Their accuracy can be improved by judiciously selecting the sample size. The required sample sizes to achieve accuracy can be quite restrictive, especially when the nominal proportions of non-conforming units are quite small. The usual attribute control chart has a set sample size and the number of non-conforming units in the sample is plotted. If, instead of setting a specific sample size the number of non-conforming units is set, an alternative monitoring process is possible. Specifically, the cumulative count of conforming (CCC- r) control chart is a plot of the number of units that must be tested to find the rth non-conforming unit. These charts, based on the geometric and negative binomial distributions, are often suggested for monitoring very high quality processes. However, they can also be used very efficiently to monitor processes of lesser quality. This procedure has the potential to find process deterioration more quickly and efficiently. Xie et al. (Journal of Quality and Reliability Management 1999; 16(2):148,157) provided tables of control limits for CCC- r charts for but focused mainly on high-quality processes and the tables do not include any assessments of the risk of a false alarm or the reliability of detecting process change. In this paper, these tables are expanded for processes of lesser quality and include such assessments using the number of expected monitoring periods (average run lengths (ARLs)) to detect process change. Also included is an assessment of the risk of a false alarm, that is, a false indication of process deterioration. Such assessments were not included by Xie et al. but are essential for the quality engineer to make sound decisions. Furthermore, a hybrid of the control charts based on the binomial, geometric and negative binomial distributions is proposed to monitor for process change. Copyright © 2005 John Wiley & Sons, Ltd. [source] Eclogites from the south Tianshan, NW China: petrological characteristic and calculated mineral equilibria in the Na2O,CaO,FeO,MgO,Al2O3,SiO2,H2O systemJOURNAL OF METAMORPHIC GEOLOGY, Issue 2 2003C. J. Wei Abstract Eclogites from the south Tianshan, NW China are grouped into two types: glaucophane and hornblende eclogites, composed, respectively, of garnet + omphacite + glaucophane + paragonite + epidote + quartz and garnet + omphacite + hornblende (sensu lato) + paragonite + epidote + quartz, plus accessory rutile and ilmenite. These eclogites are diverse both in mineral composition and texture not only between the two types but also among the different selected samples within the glaucophane eclogite. Using thermocalc 3.1 and recent models of activity,composition relation for minerals, a P,T projection and a series of P,T pseudosections for specific samples of eclogite have been calculated in the system Na2O,CaO,FeO,MgO,Al2O3,SiO2,H2O (NCFMASH) with quartz and water taken to be in excess. On the basis of these phase diagrams, the phase relations and P,T conditions are well delineated. The three selected samples of glaucophane eclogite AK05, AK11 and AK17 are estimated to have peak P,T conditions, respectively, of 540,550 °C at c. 16 kbar, c. 560 °C at 15,17 kbar and c. 580 °C at 15,19 kbar, and two samples of hornblende eclogite AK10 and AK30 of 610,630 °C and 17,18 kbar. Together with H2O-content contours in the related P,T pseudosections and textural relations, both types of eclogite are inferred to show clockwise P,T paths, with the hornblende eclogite being transformed from the glaucophane eclogite assemblage dominantly through increasing temperature. [source] Relative clinical utility of three child symptom inventory-4 scoring algorithms for differentiating children with autism spectrum disorder vs. attention-deficit hyperactivity disorderAUTISM RESEARCH, Issue 6 2009Carla J. DeVincent Abstract Objective: The present study compared three separate Child Symptom Inventory-4 (CSI-4) scoring algorithms for differentiating children with autism spectrum disorder (ASD) from youngsters with attention-deficit/hyperactivity disorder (ADHD). Method: Parents/teachers completed the CSI-4, a DSM-IV-referenced rating scale, for 6 to 12-year-old clinical referrals with ASD (N=186) and ADHD (N=251). Algorithms were based on either all CSI-4 items (forward logistic regressions) or the 12 DSM-IV symptoms of pervasive developmental disorder (PDD) included in the CSI-4. Results: ROC analyses indicated generally good to excellent values for area under the curve, sensitivity, specificity, and positive predictive power. Algorithms for parent ratings were superior to teacher ratings. The algorithm based solely on PDD symptoms evidenced the greatest generalizability. Conclusion: Although algorithms generated from regression analyses produced greater clinical utility for specific samples, the PDD-based algorithm resulted in greater stability across samples. [source] | ||||||||||