Alexander Piazza

Color-encoded distance visualization of cranial nerve-vessel contacts

PurposeVisualization of pathological contact between cranial nerves and vascular structures at the surface of the brainstem is important for diagnosis and treatment of neurovascular compression (NVC) syndromes. We developed a method for improved visualization of this abnormality.MethodsDistance fields were computed using preoperative MRI scans of individuals with NVC syndromes to support the topological representation of brainstem surface structures with quantitative information. Polygonal models of arteries, cranial nerves and the brainstem were generated using segmented T2 weighted MR data. After color-coding the polygonal models with the respective distances, enhanced color visualization of vessel-nerve locations with possible contacts was achieved.ResultsThe proposed method was implemented and applied to surgical planning in a dozen cases of NVC syndrome. Two selected cases were chosen to demonstrate the feasibility and subjective improvement provided by our visualization technique. Expert neurosurgeons found the improvement valuable and useful for these cases.ConclusionColor-encoded distance information significantly improves the perceptibility of potential nerve-vessel contacts. This method contributes to a better understanding of the complex anatomical situation at the surface of the brainstem and assists in planning of surgery.

SciencOmat: A Gamified Research Platform for Evaluating Visual Attractiveness

There are many platforms on the market that support researchers and practitioners to create surveys and market studies. Nevertheless, nearly all of them focus on providing answers to textual questions. In contrast to existing systems this paper presents the concept, prototype, and evaluation of a new mobile platform for quantitative research strictly focusing on images: the SciencOmat. This platform uses pictures to evaluate products, marketing content, and other elements based on their visual attractiveness. Particular emphasis was placed on a high level of usability and user experience. The system integrates methods known from popular online dating applications (e.g., liking/disliking a product by swiping left or right) and also applies gamification elements to further drive user motivation. Next to the application and its evaluation using the User Experience Questionnaire provided by Schrepp et al. we also present the results of two exemplary image data sets.

Analysis and Visualization of Nerve Vessel Contacts for Neurovascular Decompression

Neurovascular compression syndromes are caused by a pathological contact between cranial nerves and vascular structures at the surface of the brainstem. Aiming at improved pre-operative analysis of the target structures, we propose calculating distance fields to provide quantitative information of the important nerve-vessel contacts. Furthermore, we suggest reconstructing polygonal models for the nerves and vessels. Color-coding with the respective distance information is used for enhanced visualization. Overall, our new strategy contributes to a significantly improved clinical understanding.

Emotionalizing e-Commerce Pages: Empirical Evaluation of Design Strategies for Increasing the Affective Customer Response

The interdisciplinary research of neuromarketing shows that the conscious and rational consumer is only an illusion, whereas emotions have a significant influence on consumer behavior. Therefore, this study examines the effect of emotionalized e-com pages on visitors’ emotions as well as on their behavioral intention in hedonic situations. Three landing pages are conceptualized using diverse techniques of emotional boosting along with different procedures of triggering distinct levels of neuronal activity. The impact of these landing pages is examined in an online survey, generating a sample of 391 participants. The resulting dataset is analyzed by using structural equation modeling to test the proposed hypotheses. The results confirm that emotions can be triggered only by seeing a landing page of an e-com store and that these emotions influence the behavioral intentions. Additionally, the study shows a moderating effect of long-term involvement and mood and provides recommendations for appropriate and well-designed websites.

Do You Like According to Your Lifestyle? A Quantitative Analysis of the Relation Between Individual Facebook Likes and the Users’ Lifestyle

The performance of companies depends on the ability to leverage data to create insights and to target consumers with personalized messages Like marketing content or product offerings. One key element for personalized targeting are expressive user profiles, which are the basis for predictive models to estimate individual consumers’ preferences. Traditionally user profiles are mainly based on demographic attributes like age, gender, or occupation. Due to changes in society, consumers’ behaviors are less stable, and therefore these demographic factors are less effective. Alternatively, the consumers’ lifestyle has a significant impact on their purchase and consumption behavior. This paper investigates the relationship between Facebook Likes and the lifestyle of individuals based on the activity, interests, and opinion (AIO) model. Therefore, 14482 user-Like combinations from 214 participants were collected together with lifestyle information and a correlation analysis is conducted. The results indicate weak monotonic correlations between the AIO and the Like information.

Do You Write What You Are in Business Communications? Deriving Psychometrics from Enterprise Social Networks

In this paper, we explore the discriminability of psychometrics derived from an automated linguistic analysis within a business setting. To this end, a commercial natural language processing application is used to analyse messages posted to the Enterprise Social Network (ESN) of an Australian professional services firm. Comparing the psychometrics derived for individual users with those of other users, we find that the text posted to the ESN facilitates the detection of distinguishable personality profiles. Also, our analysis indicates the derived psychometrics to remain stable from year to year.