Text clustering with important words using normalization

Important words, which usually exist in part of Title, Subject and Keywords, can briefly reflect the main topic of a document. In recent years, it is a common practice to exploit the semantic topic of documents and utilize important words to achieve document clustering, especially for short texts such as news articles. This paper proposes a novel method to extract important words from Subject and Keywords of articles, and then partition documents only with those important words. Considering the fact that frequencies of important words are usually low and the scale matrix dataset for important words is small, a normalization method is then proposed to normalize the scale dataset so that more accurate results can be achieved by sufficiently exploiting the limited information. The experiments validate the effectiveness of our method.

Theorizing normalization as hidden privilege

This chapter provides a theoretical overview of some of the ways in which the process of normalization functions as forms of hidden privilege. It outlines how privileged groups come to represent the dominant norm whereby white, male, able-bodied, heterosexual, middle-class people in Western societies come to embody what it means to be normal. It also explores strategies for challenging the normalization of privilege by encouraging the development of responsibility not only for individual actions but also for the social practices which create them.

On self-propagating methodological flaws in performance normalization for strength and power sports

Performance in strength and power sports is greatly affected by a variety of anthropometric factors. The goal of performance normalization is to factor out the effects of confounding factors and compute a canonical (normalized) performance measure from the observed absolute performance. Performance normalization is applied in the ranking of elite athletes, as well as in the early stages of youth talent selection. Consequently, it is crucial that the process is principled and fair. The corpus of previous work on this topic, which is significant, is uniform in the methodology adopted. Performance normalization is universally reduced to a regression task: the collected performance data are used to fit a regression function that is then used to scale future performances. The present article demonstrates that this approach is fundamentally flawed. It inherently creates a bias that unfairly penalizes athletes with certain allometric characteristics, and, by virtue of its adoption in the ranking and selection of elite athletes, propagates and strengthens this bias over time. The main flaws are shown to originate in the criteria for selecting the data used for regression, as well as in the manner in which the regression model is applied in normalization. This analysis brings into light the aforesaid methodological flaws and motivates further work on the development of principled methods, the foundations of which are also laid out in this work.

Young people, pleasure, and the normalization of pornography: sexual health and well-being in a time of proliferation?

It has been argued that pornography is the most prominent sex educator for young people today (Flood, M. (2010). Young men using pornography. In E. Boyle (Ed.), Everyday Pornography (pp. 164–178). Oxford: Routledge). Research indicates that first exposure to pornography can be as young as 11 years of age. There is evidence that exposure to pornography is shaping young people’s sexual expectations and practices (H€aggstro ̈ m-Nordin et al. 2005). Many young people are learning what sex looks like from what they – or their partner or peers – observe in pornography. Significantly,pornography is normalizing sex acts that most women do not enjoy and may experience as degrading, painful, or violating. This raises serious implications for young people’s capacity to develop a sexuality that incorporates mutual pleasure, respect, and negotiation of free and full consent.While the results are complex and nuanced, research into the effects of pornography consumption provides reliable evidence that exposure to pornography increases aggressive attitudes and behavior towards women for some viewers (Malamuth et al. Annual Review of Sex Research 11, 26–91, 2000). Pornography consumption also has been found to be associated with sexual health risk taking and can impact negatively on body image and sense of self (Dean, L. (2007). Young Men, Pornography and Sexual Health Promotion, MA Research, Brighton University, Brighton, in possession of the author), and as such is a serious health and well-being issue, particularly for young women.This chapter explores preservice teachers’ reactions to pornography education using two examples from teaching of an elective Teaching Sexuality in the Middle Years, in 2011. These examples explore the complex emotions such teaching can generate and the challenges faced by preservice teachers when they are encouraged to confront the gendered and violent consequences of the normalization of pornography in a coeducational setting.

Effect of creatine supplementation on housekeeping genes in human skeletal muscle using real-time RT-PCR

The present study examined the validity and reliability of measuring the expression of various genes in human skeletal muscle using quantitative real-time RT-PCR on a GeneAmp 5700 sequence detection system with SYBR Green 1 chemistry. In addition, the validity of using some of these genes as endogenous controls (i.e., housekeeping genes) when human skeletal muscle was exposed to elevated total creatine levels and exercise was also examined. For all except 28S, linear relationships between the logarithm of the starting RNA concentrations and the cycle threshold (C_T) values were established for ß-actin, ß2-microglobulin (ß₂M), cyclophilin (CYC), and glyceraldehyde-3-phosphate dehydrogenase (GAPDH). We found a linear response between C_T values and the logarithm of a given amount of starting cDNA for all the genes tested. The overall intra-assay coefficient of variance for these genes was 1.3% and 21% for raw C_T values and the linear value of 2^-C_T, respectively. Interassay variability was 2.3% for raw C_T values and 34% for the linear value of 2^-C_T. We also examined the expression of various housekeeping genes in human skeletal muscle at days 0, 1, and 5 following oral supplementation with either creatine or a placebo employing a double-blind crossover study design. Treatments were separated by a 5-wk washout period. Immediately following each muscle sampling, subjects performed two 30-s all-out bouts on a cycle ergometer. Creatine supplementation increased (P < 0.05) muscle total creatine content above placebo levels; however, there were no changes (P > 0.05) in C_T values across the supplementation periods for any of the genes. Nevertheless, 95% confidence intervals showed that GAPDH was variable, whereas ß-actin, ß₂M, and CYC were the least varying genes. Normalization of the data to these housekeeping genes revealed variable behavior for ß₂M with more stable expressions for both ß-actin and CYC. We conclude that, using real-time RT-PCR, ß-actin or CYC may be used as housekeeping genes to study gene expression in human muscle in experiments employing short-term creatine supplementation combined with high-intensity exercise.

Improved support vector machine generalization using normalized input space

Data pre-processing always plays a key role in learning algorithm performance. In this research we consider data pre-processing by normalization for Support Vector Machines (SVMs). We examine the normalization affect across 112 classification problems with SVM using the rbf kernel. We observe a significant classification improvement due to normalization. Finally we suggest a rule based method to find when normalization is necessary for a specific classification problem. The best normalization method is also automatically selected by SVM itself.

Species-specific cell-matrix interactions are essential for differentiation of alveoli like structures and milk gene expression in primary mammary cells of the Cape fur seal (Arctocephalus pusillus pusillus)

Few models are in place for analysis of extreme lactation patterns such as that of the fur seals which are capable of extended down regulation of milk production in the absence of involution. During a 10–12 month lactation period, female fur seals suckle pups on shore for 2–3 days, and then undertake long foraging trips at sea for up to 28 days, resulting in the longest intersuckling bouts recorded. During this time the mammary gland down regulates milk production. We have induced Cape fur seal (Arctocephalus pusillus pusillus) mammary cells in vitro to form mammospheres up to 900 μm in diameter, larger than any of their mammalian counterparts. Mammosphere lumens were shown to form via apoptosis and cells comprising the cellular boundary stained vimentin positive. The Cape fur seal GAPDH gene was cloned and used in RT-PCR as a normalization tool to examine comparative expression of milk protein genes (αS2-casein, β-lactoglobulin and lysozyme C) which were prolactin responsive. Cape fur seal mammary cells were found to be unique; they did not require Matrigel for rapid mammosphere formation and instead deposited their own matrix within 2 days of culture. When grown on Matrigel, cells exhibited branching/stellate morphogenesis highlighting the species-specific nature of cell–matrix interactions during morphological differentiation. Matrix produced in vitro by cells did not support formation of human breast cancer cell line, PMC42 mammospheres. This novel model system will help define the molecular pathways controlling the regulation of milk protein expression and species specific requirements of the extracellular matrix in the cape fur seal.

Complementing a region descriptor for shape retrieval

In this paper, we propose to complement a region descriptor for shape retrieval with a contour descriptor; the descriptor thus obtained is a composite descriptor. We use a combination of a region descriptor and contour descriptor to obtain the proposed descriptor. A contour extraction technique is also proposed; it is required for extracting the contour of the image prior to applying a contour descriptor. Normalization of descriptors is required before disparate descriptors can be combined into a single descriptor. Hence, we test the performance of two common methods for normalization of descriptors and adopt the better performing method. Experiments are performed to test the effectiveness of the proposed descriptor for retrieval of 2d images. Sets of composite descriptors, obtained by assigning different weights to the region component and the contour component, are also evaluated. Item S8 within the MPEG-7 Still Images Content Set is used for performing experiments; this dataset consists of 3621 still images. Experimental results show that the proposed descriptor is effective.

Stereo correspondence estimation using multiwavelets scale-space representation-based multiresolution analysis

A multiresolution technique based on multiwavelets scale-space representation for stereo correspondence estimation is presented. The technique uses the well-known coarse-to-fine strategy, involving the calculation of stereo correspondences at the coarsest resolution level with consequent refinement up to the finest level. Vector coefficients of the multiwavelets transform modulus are used as corresponding features, where modulus maxima defines the shift invariant high-level features (multiscale edges) with phase pointing to the normal of the feature surface. The technique addresses the estimation of optimal corresponding points and the corresponding 2D disparity maps. Illuminative variation that can exist between the perspective views of the same scene is controlled using scale normalization at each decomposition level by dividing the details space coefficients with approximation space. The problems of ambiguity, explicitly, and occlusion, implicitly, are addressed by using a geometric topological refinement procedure. Geometric refinement is based on a symbolic tagging procedure introduced to keep only the most consistent matches in consideration. Symbolic tagging is performed based on probability of occurrence and multiple thresholds. The whole procedure is constrained by the uniqueness and continuity of the corresponding stereo features. The comparative performance of the proposed algorithm with eight famous existing algorithms, presented in the literature, is shown to validate the claims of promising performance of the proposed algorithm.

Stability and convergence analysis of transform-domain LMS adaptive filters with second-order autoregressive process

In this paper, the stability and convergence properties of the class of transform-domain least mean square (LMS) adaptive filters with second-order autoregressive (AR) process are investigated. It is well known that this class of adaptive filters improve convergence property of the standard LMS adaptive filters by applying the fixed data-independent orthogonal transforms and power normalization. However, the convergence performance of this class of adaptive filters can be quite different for various input processes, and it has not been fully explored. In this paper, we first discuss the mean-square stability and steady-state performance of this class of adaptive filters. We then analyze the effects of the transforms and power normalization performed in the various adaptive filters for both first-order and second-order AR processes. We derive the input asymptotic eigenvalue distributions and make comparisons on their convergence performance. Finally, computer simulations on AR process as well as moving-average (MA) process and autoregressive-moving-average (ARMA) process are demonstrated for the support of the analytical results.

New work ethics? The corporate athlete's back end index and organisational performance

Drawing on Michel Foucault’s later genealogies of the Self the paper will illustrate particular dimensions of the increasingly powerful individualizing and normalizing processes shaping the lifeworlds of worker-citizens in a globalizing risk society. Processes that require those who wish to be positively identified as professional, entrepreneurial, resilient, effective, athletic to do particular sorts of work on themselves. Here the paper argues that we can identify the emergence of what we call New Work Ethics. We illustrate this more general argument via an analysis of the ways in which a large Information Technology (IT) organization seeks to produce—via a workplace health and fitness program—employees who imagine themselves as embodying the behaviours and dispositions that mark the person as a corporate athlete. Knowledge of the Self in these terms can, it is promised, enhance the performance of the Self, and the organization.

On performance of transform domain adaptive filters with Markov-2 inputs

In this paper, the analysis for the performance of the discrete Fourier transform LMS adaptive filter (DFT-LMS) and the discrete cosine transform LMS adaptive filter (DCT-LMS) for the Markov-2 inputs is presented. To improve the convergence property of the least mean squares (LMS) adaptive filter, the DFT-LMS and DCT-LMS preprocess the inputs with the fixed orthogonal transforms and power normalization. We derive the asymptotic results for the eigenvalues and eigenvalue distributions of the preprocessed input autocorrelation matrices with DFT-LMS and DCT-LMS for Markov-2 inputs. These results explicitly show the superior decorrelation property of DCT-LMS over that of DFT-LMS, and also provide the upper bounds for the eigenvalue spreads of the finite-length DFT-LMS and DCT-LMS adaptive filters. Simulation results are demonstrated to support the analytic results.

The effects of treating male hypogonadism on couples' sexual desire and function

Introduction: Hypogonadism is a common endocrine condition characterized by low levels of testosterone (T) and marked by numerous symptoms, one of which is low sexual desire. Studies comparing T delivery systems have suggested that hypogonadal men’s partners may be at risk from exposure to T gels. Little other mention is found of the impact of hypogonadism and its treatment on a man’s partner and the couple’s sexual function.

Aim: To assess sexual desire and sexual function in hypogonadal men and their woman partners before and after treatment with T replacement therapy.

Methods: Twenty-one hypogonadal men and 18 partners were recruited from a   tertiary endocrine clinic, and were compared with a control group of 20 eugonadal age-matched men and their partners. All men had baseline blood tests to confirm their status as hypogonadal or eugonadal, and hypogonadal men repeated tests at 3-month intervals. All participants completed the Sexual Desire Inventory (SDI) and sexual function questionnaires at baseline and at 3-month intervals until the hypogonadal men attained normal T levels.

Main Outcome Measures: Pre- and post-treatment SDI and sexual function questionnaires were compared once T normalization was achieved. Between- and within-group comparisons were carried out.

Results: Pretreatment hypogonadal men recorded lower levels of sexual desire and function than controls, but significantly improved once hypogonadism was corrected. Eugonadal controls recorded no significant changes in either sexual desire or function during the study. Partners of the hypogonadal men reported no changes on the SDI, but significant improvements in sexual function as their partners recovered.

Conclusion: SDI and sexual function measures reflect sexual changes that  accompany rising serum T levels during correction of male hypogonadism. Women partners reported more satisfaction, less pain, and improved sexual function following the men’s treatment. Treatments affecting one partner potentially have important effects on the other.

Stereo image matching using wavelet scale-space representation

A multi-resolution technique for matching a stereo pair of images based on translation invariant discrete multi-wavelet transform is presented. The technique uses the well known coarse to fine strategy, involving the calculation of matching points at the coarsest level with consequent refinement up to the finest level. Vector coefficients of the wavelet transform modulus are used as matching features, where modulus maxima defines the shift invariant high-level features (multiscale edges) with phase pointing to the normal of the feature surface. The technique addresses the estimation of optimal corresponding points and the corresponding 2D disparity maps. Illuminative variation that can exist between the perspective views of the same scene is controlled using scale normalization at each decomposition level by dividing the details space coefficients with approximation space and then using normalized correlation. The problem of ambiguity, explicitly, and occlusion, implicitly, is addressed by using a geometric topological refinement procedure and symbolic tagging.