A Comparative Study of Desktop, Fishtank, and Cave Systems for the Exploration of Volume Rendered Confocal Data Sets

We present a participant study that compares biological data exploration tasks using volume renderings of laser confocal microscopy data across three environments that vary in level of immersion: a desktop, fishtank, and cave system. For the tasks, data, and visualization approach used in our study, we found that subjects qualitatively preferred and quantitatively performed better in the cave compared with the fishtank and desktop. Subjects performed real-world biological data analysis tasks that emphasized understanding spatial relationships including characterizing the general features in a volume, identifying colocated features, and reporting geometric relationships such as whether clusters of cells were coplanar. After analyzing data in each environment, subjects were asked to choose which environment they wanted to analyze additional data sets in - subjects uniformly selected the cave environment.

Problematic Internet use in British adolescents: An exploration of the addictive symptomatology

Research into online addictions has increased substantially over the last decade, particularly amongst youth. This study adapted the Problematic Internet Entertainment Use Scale for Adolescents [PIEUSA] for use with a British population. The adapted scale was used to (i) validate the instrument for English-speaking adolescent samples, (ii) estimate the prevalence of adolescent online problem users and describe their profile, and (iii) assess the accuracy of the scale"s classification of symptomatology. A survey was administered to 1097 adolescents aged between 11 and 18 years. The results indicated that (i) reliability of the adapted scale was excellent; factor validity showed unidimensionality, and construct validity was adequate. The findings also indicated that (ii) prevalence of online problem users was 5.2% and that they were more likely to younger males that engaged in online gaming for more than two hours most days. The majority of online problem users displayed negative addictive symptoms, especially"loss of control" and"conflict". The adapted scale showed (iii) very good sensitivity, specificity, and classification accuracy, and was able to clearly differentiate between problem and non-problem users. The results suggest certain differences between adolescent and adult online problem users based in the predominance of slightly different psychological components.

The Importance of Semantics: Visual World Studies on Drawing Inferences and Resolving Anaphors

The present thesis investigated the importance of semantics in generating inferences during discourse processing. Three aspects of semantics, gender stereotypes, implicit causality information and proto-role properties, were used to investigate whether semantics is activated elaboratively during discourse comprehension and what its relative importance is in backward inferencing compared to discourse/structural cues. Visual world eye-tracking studies revealed that semantics plays an important role in both backward and forward inferencing: Gender stereotypes and implicit causality information is activated elaboratively during online discourse comprehension. Moreover, gender stereotypes, implicit causality and proto-role properties of verbs are all used in backward inferencing. Importantly, the studies demonstrated that semantic cues are weighed against discourse/structural cues. When the structural cues consist of a combination of cues that have been independently shown to be important in backward inferencing, semantic effects may be masked, whereas when the structural cues consist of a combination of fewer prominent cues, semantics can have an earlier effect than structural factors in pronoun resolution. In addition, the type of inference matters, too: During anaphoric inferencing semantics has a prominent role, while discourse/structural salience attains more prominence during non-anaphoric inferencing. Finally, semantics exhibits a strong role in inviting new inferences to revise earlier made inferences even in the case the additional inference is not needed to establish coherence in discourse. The findings are generally in line with the Mental Model approaches. Two extended model versions are presented that incorporate the current findings into the earlier literature. These models allow both forward and backward inferencing to occur at any given moment during the course of processing; they also allow semantic and discourse/structural cues to contribute to both of these processes. However, while the Mental Model 1 does not assume interactions between semantic and discourse/structural factors in forward inferencing, the Mental Model 2 does assume such a link.

Advancing towards inclusive social research: visual methods as opportunities for people with severe mental illness to participate in research

This article explores the possibilities offered by visual methods in the move towards inclusive research, reviewing some methodological implications of said research and reflecting on the potential of visual methods to meet these methodological requirements. A study into the impact of work on social inclusion and the social relationships of people suffering from severe mental illness (SMI) serves to illustrate the use of visual methods such as photo elicitation and graphic elicitation in the context of in-depth interviews with the aim of improving the aforementioned target group’s participation in research, participation understood as one of the basic elements of inclusive approaches. On the basis of this study, we reflect on the potential of visual methods to improve the inclusive approach to research and conclude that these methods are open and flexible in awarding participantsa voice, allowingpeople with SMI to express their needs, and therefore adding value to said approach

Uma experiência didática de corrosão usando colorimetria visual

In this paper, a simple and rapid method of evaluating galvanized steel sheet corrosion in a CuSO4 solution, as an experimentation proposal for corrosion teaching. Galvanized steel corrosion is present in tanks and tubing by leading of natural or industrial waters which contain soluble copper compounds. This was the rationale for choosing the Cu2+ ions solution as an oxidizing agent. The method principle is based on visual colorimetry because the used oxidant has an intense blue color. Thus, a change in its concentration as a result of the corrosive process can be followed by a color intensity change in the solution thereby allowing evaluation of the corrosion rate.

Visual demonstration of the ionic strength effect in the classroom: the Debye-Hückel limiting law

The effects of ionic strength on ions in aqueous solutions are quite relevant, especially for biochemical systems, in which proteins and amino acids are involved. The teaching of this topic and more specifically, the Debye-Hückel limiting law, is central in chemistry undergraduate courses. In this work, we present a description of an experimental procedure based on the color change of aqueous solutions of bromocresol green (BCG), driven by addition of electrolyte. The contribution of charge product (z+|z-|) to the Debye-Hückel limiting law is demonstrated when the effects of NaCl and Na2SO4 on the color of BCG solutions are compared.

Demonstration Platform for Visual Quality Metrics

This thesis presents two graphical user interfaces for the project DigiQ - Fusion of Digital and Visual Print Quality, a project for computationally modeling the subjective human experience of print quality by measuring the image with certain metrics. After presenting the user interfaces, methods for reducing the computation time of several of the metrics and the image registration process required to compute the metrics, and details of their performance are given. The weighted sample method for the image registration process was able to signifigantly decrease the calculation times while resulting in some error. The random sampling method for the metrics greatly reduced calculation time while maintaining excellent accuracy, but worked with only two of the metrics.

Learning Robot Motions from Visual Sensing

Learning from demonstration becomes increasingly popular as an efficient way of robot programming. Not only a scientific interest acts as an inspiration in this case but also the possibility of producing the machines that would find application in different areas of life: robots helping with daily routine at home, high performance automata in industries or friendly toys for children. One way to teach a robot to fulfill complex tasks is to start with simple training exercises, combining them to form more difficult behavior. The objective of the Master’s thesis work was to study robot programming with visual input. Dynamic movement primitives (DMPs) were chosen as a tool for motion learning and generation. Assuming a movement to be a spring system influenced by an external force, making this system move, DMPs represent the motion as a set of non-linear differential equations. During the experiments the properties of DMP, such as temporal and spacial invariance, were examined. The effect of the DMP parameters, including spring coefficient, damping factor, temporal scaling, on the trajectory generated were studied.

Computational visual quality of digitally printed images

The problem of understanding how humans perceive the quality of a reproduced image is of interest to researchers of many fields related to vision science and engineering: optics and material physics, image processing (compression and transfer), printing and media technology, and psychology. A measure for visual quality cannot be defined without ambiguity because it is ultimately the subjective opinion of an “end-user” observing the product. The purpose of this thesis is to devise computational methods to estimate the overall visual quality of prints, i.e. a numerical value that combines all the relevant attributes of the perceived image quality. The problem is limited to consider the perceived quality of printed photographs from the viewpoint of a consumer, and moreover, the study focuses only on digital printing methods, such as inkjet and electrophotography. The main contributions of this thesis are two novel methods to estimate the overall visual quality of prints. In the first method, the quality is computed as a visible difference between the reproduced image and the original digital (reference) image, which is assumed to have an ideal quality. The second method utilises instrumental print quality measures, such as colour densities, measured from printed technical test fields, and connects the instrumental measures to the overall quality via subjective attributes, i.e. attributes that directly contribute to the perceived quality, using a Bayesian network. Both approaches were evaluated and verified with real data, and shown to predict well the subjective evaluation results.

Comparison of Local Feature Detectors and Descriptors for Visual Object Categorization

Local features are used in many computer vision tasks including visual object categorization, content-based image retrieval and object recognition to mention a few. Local features are points, blobs or regions in images that are extracted using a local feature detector. To make use of extracted local features the localized interest points are described using a local feature descriptor. A descriptor histogram vector is a compact representation of an image and can be used for searching and matching images in databases. In this thesis the performance of local feature detectors and descriptors is evaluated for object class detection task. Features are extracted from image samples belonging to several object classes. Matching features are then searched using random image pairs of a same class. The goal of this thesis is to find out what are the best detector and descriptor methods for such task in terms of detector repeatability and descriptor matching rate.