Evaluation of Various DR Techniques in Massive Patient Datasets using HDFS

The objective of comparing various dimensionality techniques is to reduce feature sets in order to group attributes effectively with less computational processing time and utilization of memory. The various reduction algorithms can decrease the dimensionality of dataset consisting of a huge number of interrelated variables, while retaining the dissimilarity present in the dataset as much as possible. In this paper we use, Standard Deviation, Variance, Principal Component Analysis, Linear Discriminant Analysis, Factor Analysis, Positive Region, Information Entropy and Independent Component Analysis reduction algorithms using Hadoop Distributed File System for massive patient datasets to achieve lossless data reduction and to acquire required knowledge. The experimental results demonstrate that the ICA technique can efficiently operate on massive datasets eliminates irrelevant data without loss of accuracy, reduces storage space for the data and also the computation time compared to other techniques.

Who is it okay to punch?

A popular contemporary meme involves the social acceptability of “punching Nazis.” This phenomenon raises the question: what characteristics make a group or member of a group more or less “punch-able”? More broadly, what group attributes yield support for physical violence against them? In this study, we build on the extant psychology literature on intergroup processes to look at what leads individuals to find physical violence against a group acceptable, and if the factors that lead to such acceptance differ from those that lead to sheer affective intolerance. We use two experimental tasks to test expectations built on prominent theories. In a “real-world rating task,” participants evaluated a series of real-world groups and individuals with varying characteristics such as race, ideology, intelligence, warmth, and tendency toward violence. Also, in a conjoint experiment, participants chose between two groups in terms of which they would support being punched, as various attributes were manipulated such as race, expressed ideological values, partisanship, income, tendency toward violence, and being described as disgusting or threatening. We find consistent support for effects of political alignment (particularly, expressed ideological values related to dominance) and perceived tendency toward violence, as well as mixed findings for race and several other factors. These findings synthesize theories on intergroup conflict with contemporary findings on affective polarization.

A Review of seismic attribute taxonomies, discussion of their historical use, and the presentation of a seismic attribute communication framework using data analysis concepts

Beginning in the 1970s, seismic attributes have grown from a few simple measurements of wavelet amplitude, frequency, and phase, to an expanded attribute toolbox that measures not only wavelet properties but also their context within the 3D seismic volume. When using multiple seismic attributes to either support or to facilitate a geological or geophysical objective, the interpreter must understand not only each individual attribute but also the relationships between them. Researchers communicate these relationships via seismic attribute taxonomies, which group attributes by their signal property, mathematical formulation, or their interpretive value. The first significant attempt to organize seismic attributes began in the 1990s, and with new attributes and their increasing breadth of applications, continues to this day. The vast majority of scientific papers that use seismic attributes focus on either a specific application, new algorithms, or a novel interpretation workflow, rather than how a specific attribute fits within the greater whole, leading to confusion for the less experienced interpreter.To capture the commonly used practices, we analyzed over 2,100 citing works, identified the 231 papers that discuss the taxonomies specifically, and show how the authors use those citations. The result is a list of over a dozen seismic attribute taxonomies or classification systems, which we reduce to a smaller subset by including only those that apply to general use. An optimal seismic attribute taxonomy should not only be useful to the interpretation community today, but adapt to the ever-changing needs of the profession, including changes appropriate for their use of in modern machine learning algorithms. The adaptability of prior work to modern workflows remains a shortcoming. We present our work in two parts, the first covering the evolution of seismic attribute taxonomies and their use through time, and the second proposing a new seismic attribute communication framework.

Novel Hemocompatible Imine Compounds as Alternatives for Antimicrobial Therapy in Pharmaceutical Application

The aim of this study was to synthesize, characterize, and evaluate neoteric imine compounds for antimicrobial activity and hemocompatibility. Four compounds were synthesized using 3-thiophene carboxaldehyde, ethanol, amine, and acetic acid. The compounds were characterized using nuclear magnetic resonance (NMR) spectroscopy, Fourier transform infrared (FTIR) spectroscopy, differential scanning calorimetry (DSC), and powder X-ray diffraction (PXRD). A solubility study was conducted with various solvents and surfactants at 40 °C. An in vitro antimicrobial assay was performed against bacterial and fungal strains to determine the zone of inhibition and minimum inhibitory concentrations. Finally, an in vitro hemolysis study was conducted using rat erythrocytes. The structure of the compounds was confirmed by NMR, FTIR corroborated their functional group attributes, DSC determined their enthalpies of fusion and fusion temperatures, and PXRD confirmed their crystalline nature. These compounds were water-insoluble but soluble in chloroform, with a maximum solubility of ~80 mg/mL. The antimicrobial assay suggested that two of the products exerted potent activities against C. albicans and several bacterial strains. Finally, hemolysis analysis excluded the possibility of hemolysis at the assessed concentrations. In conclusion, two of the novel imine compounds showed promise as antimicrobial agents to control local and systemic microbial infections in a suitable dosage form.

Sales prediction on e-commerce platform, by using data mining model

In this paper we applied twinning algorithm for product that are sold via e-commerce platform. To establish relatively homogenous product groups that were on sale on this e-commerce platform during the last year, it was necessary to form predictive mathematical model. We determined set of relevant variables that will represent group attributes, and we applied K-means algorithm, Market Basket model and Vector Distance model. Based on analysis of basic and derived variables, fixed number of clusters was introduced. Silhouette index was used for the purposes of detecting whether these clusters are compact. Using these cluster separations, we created models that detect similar products, and try to analyze probability of sales for each product. Analysis results can be used for planning future sales campaigns, marketing expenses optimization, creation of new loyalty programs, and better understanding customer behavior in general.

Improving and Validating Survey Estimates of Religious Demography Using Bayesian Multilevel Models and Poststratification

Religious group size, demographic composition, and the dynamics thereof are of interest in many areas of social science including migration, social cohesion, parties and voting, and violent conflict. Existing estimates however are of varying and perhaps poor quality because many countries do not collect official data on religious identity. We propose a method for accurately measuring religious group demographics using existing survey data: Bayesian multilevel regression models with poststratification. We illustrate this method by estimating the demography of Muslims, Hindus, and Jews in Great Britain over a 20-year period and validate it by comparing our estimates to UK census data on religious demography. Our estimates are very accurate, differing from true population proportions by as little as 0.29 (Muslim) to 0.04 (Jewish) percentage points. These findings have implications for the measurement of religious demography as well as small group attributes more generally.

Norm Talk and Intergroup Communication

Norms are regularized patterns of attitudes and behavior that characterize a group of individuals, separate the group from other groups of individuals, and prescribe and describe attitudes and behaviors for group members. Relying on social identity theory and self-categorization theory, the role played by group norms within groups and the processes by which such norms are promulgated within groups are discussed. Norm talk or the communication of normative information within groups is explored, as a major proportion of communication within groups is dedicated to clarifying ingroup identities and group attributes such as attitudes and behaviors that characterize the group. Group members can glean normative information by attending to norm talk for instance, by listening to the content of fellow group members’ communications, from their behavior, and from influential or prototypical sources within the group. According to self-categorization theory, once individuals categorize themselves as members of a salient group or category, they represent normative information cognitively as ingroup prototypes. Prototypes are a fuzzy set of group attributes (such as attitudes and behaviors that characterize the group) and simultaneously minimize differences within groups while maximizing differences between groups. Thus, clear group prototypes help create distinct identities that are clearly demarcated from other groups. Group members should be especially attentive to information that flows from prototypical sources within groups—such as leaders and ingroup media sources—while efforts should be made to differentiate from marginal or deviant members who deviate from the prototype and reduce clarity of ingroup prototypes. The processes through which attending to information communicated by different sources within groups—both prototypical and non-prototypical—help group members seek normative information and clarification of ingroup prototypes are discussed.