Cognitive-Mathematical Approaches for Evaluating Architectural Contextual Fit

The rank ordering of samples is widely used in robust nonlinear signal processing. Recent advances in nonlinear filtering algorithms have focused on combining spatial and rank (SR) order information into the filtering process to allow spatial correlations to be exploited while retaining the robust characteristics of strict rank order methods. Further generalization can be achieved by replacing the crisp, or binary, SR information utilized by most methods with more general fuzzy SR information. Indeed, by exploiting fuzzy methodologies real-valued SR orderings can be defined that not only relate the spatial and rank orderings of samples, but also includes information on sample spread. This paper utilizes this approach to define fuzzy ranking and fuzzy order statistics. Properties of these concepts are discussed and several previously defined filters are generalized by including fuzzy concepts. Specifically, the fuzzy median, fuzzy rank conditioned rank selection, and fuzzy weighted median filters are defined. Optimization of the parameters for these filters are discussed. Simulation results are presented to show the advantages of these fuzzy filters over their crisp counterparts.

Effects of RAS inhibitors on diabetic retinopathy: a systematic review and meta-analysis

Learning the true rank ordering among objects by aggregating a set of expert opinion rank order lists is an important and ubiquitous problem in many applications ranging from social choice theory to recommendation systems and search aggregation. We study the problem of unsupervised rank aggregation where no ground truth ordering information in available, neither about the true preference ordering among any set of objects nor about the quality of individual rank lists. Aggregating the often inconsistent and poor quality rank lists in such an unsupervised manner is a highly challenging problem, and standard consensus-based methods fall short in terms of both quality and scalability. In this manuscript we propose a novel framework to bypass these issues by using object attributes to augment the standard rank aggregation framework. We design algorithms that learn joint models on both rank lists and object features to obtain an aggregated rank ordering that is more accurate and robust, and also helps weed out rank lists of dubious validity. We validate our techniques on synthetic datasets where our algorithm is able to estimate the true rank ordering even when the rank lists are corrupted. Experiments on three real datasets, MQ2008, MQ2007 and OHSUMED, show that using object features can result in significant improvement in performance over existing rank aggregation methods that do not use object information. Furthermore, when at least some of the rank lists are of high quality, our methods are able to effectively exploit such information to output an aggregated rank ordering of high accuracy.

Chapter 1 - Communication and emotion: Basic concepts and approaches

The purpose of this study was to conduct an interlaboratory ring-study, with six partners (academic and industrial), investigating the measurement of intrinsic dissolution rate (IDR) using surface dissolution imaging (SDI) equipment. Measurement of IDR is important in pharmaceutical research as it provides characterising information on drugs and their formulations. This work allowed us to assess the SDI’s interlaboratory performance for measuring IDR using a defined standard operating procedure (see supporting information) and six drugs assigned as low (tadalafil, bromocriptine mesylate), medium (carvedilol, indomethacin) and high (ibuprofen, valsartan) solubility compounds. Fasted State Simulated Intestinal Fluid (FaSSIF) and blank FaSSIF (without sodium taurocholate and lecithin) (pH 6.5) were used as media. Using the standardised protocol an IDR value was obtained for all compounds and the results show that the overall IDR rank order matched the solubility rank order. Interlaboratory variability was also examined and it was observed that the variability for lower solubility compounds was higher, coefficient of variation >50%, than for intermediate and high solubility compounds, with the exception of indomethacin in FaSSIF medium. Inter laboratory variability is a useful descriptor for understanding the robustness of the protocol and the system variability. On comparison to another published small-scale IDR study the rank ordering with respect to dissolution rate is identical except for the high solubility compounds. This results indicates that the SDI robustly measures IDR however, no recommendation on the use of one small scale method over the other is made.

Predictive torque control (PTC) is an emerging and promising technology in electric drives. The effective performance of the PTC drive lies in its simple control law wherein different constraints can be easily added with weighting factors. However only empirical approximation methods are used for the determination of weighting factor. This paper presents a ranking weight method to find the weighting factor in predictive torque control of five-phase induction motor (IM). The weighting factor value is based on the rank ordering of the criteria (such as torque, flux, xy-plane current harmonics, CMV etc.) considered in the cost function. Assigning weights based on the rank of the criteria is more reliable than randomly assigning weights to the criteria because the decision makers are more confident on the ranks of the criteria than weights. Rank order centroid (ROC) weight technique is presented and compared with conventional weighting technique. The viability of the concept is verified by numerical simulations and the results are validated through experimentation.

malformations were excluded. The accuracy of each model for prediction of macrosomia was calculated using several thresholds: 4000 g (or 360 mm for AC), the threshold obtained from the inflexion point in the ROC curve, and the threshold associated with the highest overall accuracy. The models were rank ordered from 1 (most accurate) to 22 (least accurate) using a composite score. Results: 1) There was a considerable variation in the accuracy of the different models (in Table 1 values are presented as mean (range) of all models), 2) The use of different types of threshold resulted in significant differences in the performance of the different models (table). 3) Models based on three or four biometric indices were significantly more accurate than those based on two indices. 4) AC as a single measure was of relatively low accuracy in predicting macrosomia (rank order = 15). Conclusions: When macrosomia is suspected, models based on three or four biometric indices appear to be superior over those based on two indices or AC as a single measure. Model-specific threshold may provide better accuracy than the uniform use of the 4000 g threshold.

The occurrence and topographic analysis of granulovacuolar degeneration (GVD) in the hippocampal cortex of mentally normal controls (75 cases) and patients with Alzheimer's dementia (AD; 17 cases which included Alzheimer's disease and senile dementia of Alzheimer type), multi-infarct dementia (MID; 16 cases), Pick's disease (PD; 5 cases) and atypical dementia [5 cases; non-Alzheimer, non-Pick dementia with Fahr's syndrome (NANPDF)] were investigated. GVD was rarely found in control cases below the age of 60 years. In elderly normal brains, the statistically most representative ranking order of predilection for GVD (in decreasing severity) was: in the 60 s, CA1 > prosubiculum > CA2 (no GVD was found in the CA3 and CA4); in the 70 s, CA1 > prosubiculum > CA2 > CA3 > CA4; in the 80 s, CA1 > prosubiculum > CA2 > CA3 > CA4; in the 90 s, CA1 > prosubiculum > CA2 > CA3 > CA4. In the brains of demented patients, the rank order for GVD was: for AD, CA1 > CA2 > CA3 > prosubiculum > CA4; for MID, CA1 > prosubiculum > CA2 > CA3 > CA4; for PD, CA1 > CA2 > CA3 > prosubiculum > CA4; and for atypical dementia (NANPDF), CA1 > CA2 > prosubiculum > CA3 > CA4. The similarity of the predilection to ranking order was noted both in normal aged subjects and in MID as well as both in AD and in PD.(ABSTRACT TRUNCATED AT 250 WORDS)

Experimental investigation on rock mechanical properties and infrared radiation characteristics with freeze-thaw cycle treatment

Barrier effects in the cognitive maps of children and adults

Various psychological frameworks are presented as alternatives to cognitivism, the currently dominant theoretical framework in cognitive science. The plurality of the alternative frameworks is emphasised. These include net work models, action models, as well as models presented in ecological psychology, social cognition, and phenomenology. The various frameworks are presented as the different variables in a typology defined by two dimensions—the basic objects of psychological theory and the locus of cognitive activity. It is suggested that the various models, including cognitivism and behaviourism, may be viewed as the different solutions to one basic conceptual problem in the study of psychology. The methodological ramifications of phenomenological research are studied in further detail.

Experience of building an architecture-based generator using GenVoca for distributed systems

This paper focuses on the role that judgmental modelling played in helping a large international manufacturer plan its future production environment. Two strategic decisions had to be made, relating to which production process to choose, and which projects to allocate to the process. Different members of the management team were responsible for different elements of the decision. There was extensive interchange and negotiation between these various parties throughout the decision process. In both cases the use of judgmental modelling had advantages in terms of structuring the decision process and in rank ordering the potential solutions. The paper compares the rank orders of the different potential outcomes before and after the use of the judgmental modelling, and comments on the differences between them. In addition, we introduce the use of psychological profiling as an approach to understanding how individuals interact and negotiate their way through a major strategic decision. >

Rokeach, Miller, and Snyder (1971) have reported evidence for a “value gap” between samples of police and citizens in the midwest. The objectives of the present study were: (1) to examine the generality of this finding for another section of the country, the southeast; (2) to extend the analysis from the comparisons of individual values to the comparison of configurations of values between police and citizens; and (3) to compare the police sample from the Rokeach et al. study with the police sample from this study. The Rokeach Value Survey was administered to 104 South Carolina police officers and to 316 citizens sampled in a variety of South Carolina community settings. Group comparisons were made on the rank ordered individual values using the median test. In addition, group median rank orders were compared using the Spearman correlation. The results for the individual values generally supported the findings of Rokeach et al. (1971). For the value configurations, the police‐community correlations were uniformly high, indicating general agreement on the relative order of most values. Results of the cross‐sectional comparison of police samples revealed a very high degree of correspondance for both individual values and configurations.

Quantifying tibial plafond fracture severity: absorbed energy and fragment displacement agree with clinical rank ordering.