A Study of the Effect of Doughnut Chart Parameters on Proportion Estimation Accuracy

Pie and doughnut charts nicely convey the part–whole relationship and they have become the most recognizable chart types for representing proportions in business and data statistics. Many experiments have been carried out to study human perception of the pie chart, while the corresponding aspects of the doughnut chart have seldom been tested, even though the doughnut chart and the pie chart share several similarities. In this paper, we report on a series of experiments in which we explored the effect of a few fundamental design parameters of doughnut charts, and additional visual cues, on the accuracy of such charts for proportion estimates. Since mobile devices are becoming the primary devices for casual reading, we performed all our experiments on such device. Moreover, the screen size of mobile devices is limited and it is therefore important to know how such size constraint affects the proportion accuracy. For this reason, in our first experiment we tested the chart size and we found that it has no significant effect on proportion accuracy. In our second experiment, we focused on the effect of the doughnut chart inner radius and we found that the proportion accuracy is insensitive to the inner radius, except the case of the thinnest doughnut chart. In the third experiment, we studied the effect of visual cues and found that marking the centre of the doughnut chart or adding tick marks at 25% intervals improves the proportion accuracy. Based on the results of the three experiments, we discuss the design of doughnut charts and offer suggestions for improving the accuracy of proportion estimates

Cognitively diagnostic analysis using the G-DINA model in R

Cognitive diagnosis models (CDMs) have increasingly been applied in education and other fields. This article provides an overview of a widely used CDM, namely, the G-DINA model, and demonstrates a hands-on example of using multiple R packages for a series of CDM analyses. This overview involves a step-by-step illustration and explanation of performing Q-matrix evaluation, CDM calibration, model fit evaluation, item diagnosticity investigation, classification reliability examination, and the result presentation and visualization. Some limitations of conducting CDM analysis in R are also discusse

Saccadic eye movements estimate prolonged time awake

Prolonged time awake increases the need to sleep. Sleep pressure increases sleepiness, impairs human alertness and performance and increases the probability of human errors and accidents. Human performance and alertness during waking hours are influenced by homeostatic sleep drive and the circadian rhythm. Cognitive functions, especially attentional ones, are vulnerable to circadian rhythm and increasing sleep drive. A reliable, objective and practical metrics for estimating sleepiness could therefore be valuable. Our aim is to study whether saccades measured with electro-oculography (EOG) outside the laboratory could be used to estimate the overall time awake without sleep of a person. The number of executed saccades was measured in 11 participants during an 8-min saccade task. The saccades were recorded outside the laboratory (Naval Academy, Bergen) using EOG every sixth hour until 54 hr of time awake. Measurements were carried out on two occasions separated by 10 weeks. Five participants participated in both measurement weeks. The number of saccades decreased during sustained wakefulness. The data correlated with the three-process model of alertness; performance differed between participants but was stable within individual participants. A mathematically monotonous relation between performance in the saccade task and time awake was seen after removing the circadian rhythm component from measured eye movement data. The results imply that saccades measured with EOG can be used as a time-awake metric outside the laboratory.Peer reviewe

InvVis: Large-Scale Data Embedding for Invertible Visualization

We present InvVis, a new approach for invertible visualization, which is reconstructing or further modifying a visualization from an image. InvVis allows the embedding of a significant amount of data, such as chart data, chart information, source code, etc., into visualization images. The encoded image is perceptually indistinguishable from the original one. We propose a new method to efficiently express chart data in the form of images, enabling large-capacity data embedding. We also outline a model based on the invertible neural network to achieve high-quality data concealing and revealing. We explore and implement a variety of application scenarios of InvVis. Additionally, we conduct a series of evaluation experiments to assess our method from multiple perspectives, including data embedding quality, data restoration accuracy, data encoding capacity, etc. The result of our experiments demonstrates the great potential of InvVis in invertible visualization.Comment: IEEE VIS 202

Acrylamide in Popular West African Foods

Acrylamide (AA) is a toxic compound, present in a wide range of heat-processed foods prepared from materials rich in reducing sugar and asparagine. Since the time of discovery of AA in foods, no study has considered the effect of precursors, commonly used methods and temperatures of cooking on the formation of the contaminant in popular West African (WA) foods. Consequently, this study focused on the impact of these parameters on the acrylamide levels in WA foods including akara, bread, buns, chin-chin, doughnut, fish-roll, meat-pie, plantain-chips, puff-puff, and yam-chips. The study evaluated the effect of baking and frying at 150, 180 and 210°C for 5, 10 and 15 mins on the AA levels in the selected WA foods. Potentiometric method based on the use of ammonium ion selective electrode and immobilised acrylamide amidohydrolase was used to test 150 samples of each WA food prepared using the different cooking temperatures. In addition, recognised methods requiring glucose oxidase and asparaginase were used for measuring the amount of precursors including glucose and asparagine in the unprocessed food materials.The relationship between the contaminant and the precursors was then determined through correlation and regression analysis of the data obtained. Independent T-test of equality of sample means at α=0.05 showed no statistical significant difference (p ˃ 0.05) in the AA produced by using baking and frying at the same temperature. However, ANOVA for the AA concentrations indicated that increasing baking and frying temperatures significantly affected the amount of the process contaminants i.e. (p < 0.05). Highest readings for the contaminant was noted for WA foods processed for longer times at 210°C, while the lowest measurements were obtained for those processed for 5mins at 150°C. The lowest amounts of acrylamide (25±7 μg/kg) was detected in buns baked at 150°C, while the highest levels of the contaminant (703±27 and 706±13 μg/kg) were noticed in yam and plantain chips fried at 210°C. Overall, a significant positive relationship (p < 0.01) was observed between AA present in the food products and the precursors measured in the food materials. The strongest and weakest determination coefficients (r2) of 0.88 and 0.30 were observed for WA plantain-chips and bread respectively. In conclusion, the temperature of cooking, asparagine and glucose levels in WA food materials are major determinants of the AA formed in the selected WA food products

Comprehending Inclinations Towards Autonomous Vehicles

Many of today's autonomous vehicle (AVs) improvements involve overcoming technology barriers to AV readiness. However, once AVs are out, acceptance and people's willingness (APW) to use remain a concern. As a result, the question arises. Are we attentive enough towards humans' aspects in the evolution of AV technology? Do we need to? The present dilemma around autonomous vehicles is of their acceptance rather than technological advancements. Many academics have investigated autonomous vehicles using questionnaires and different studies to discover how individuals can act. The issue is that individuals do not always do what they say, which does not usually describe a definite image. Nevertheless, on the other hand, we believe psychological aspects signify people's state of being. So, as a response, we seek to attain an understanding by studying human psychological aspects. This study seeks to streamline interdependency between human psychological elements and how people receive the information through various mediums and channels. With these two aspects combined, we attempt to comprehend people's inclinations towards AVs. The study resulted in a theoretical comparative estimation table (CET) and CET Hierarchical Concept Map through our reviewed literature. The study thus intended to understand the riddle of acceptability via people's psychological elements through the proposed extended theoretical comparative estimation table (CET) table. Further, through the application of the extended CET table, we present our findings comprised of our studied references with the visualization to showcase the people's viewpoints on the tendency towards autonomous vehicles. We believe the study provides vision and puts psychological elements into consideration of tackling challenges and skeptical side of concerns of APW of AVs. It also fosters interested future researchers to comprehend APW challenges better with corresponding attributes used in the CET table and CET Hierarchical Concept Map

The effect of image position on the Independent Components of natural binocular images

Human visual performance degrades substantially as the angular distance from the fovea increases. This decrease in performance is found for both binocular and monocular vision. Although analysis of the statistics of natural images has provided significant insights into human visual processing, little research has focused on the statistical content of binocular images at eccentric angles. We applied Independent Component Analysis to rectangular image patches cut from locations within binocular images corresponding to different degrees of eccentricity. The distribution of components learned from the varying locations was examined to determine how these distributions varied across eccentricity. We found a general trend towards a broader spread of horizontal and vertical position disparity tunings in eccentric regions compared to the fovea, with the horizontal spread more pronounced than the vertical spread. Eccentric locations above the centroid show a strong bias towards far-tuned components, eccentric locations below the centroid show a strong bias towards near-tuned components. These distributions exhibit substantial similarities with physiological measurements in V1, however in common with previous research we also observe important differences, in particular distributions of binocular phase disparity which do not match physiologypublishersversionPeer reviewe

150,000-year palaeoclimate record from northern Ethiopia supports early, multiple dispersals of modern humans from Africa

Climatic change is widely acknowledged to have played a role in the dispersal of modern humans out of Africa, but the timing is contentious. Dispersal is often linked to climatic change at ~60,000 years ago, despite increasing evidence for earlier presence of modern humans in Asia. Here we report a deep seismic and near-continuous core record of the last 150,000 years from Lake Tana in the Ethiopian highlands, close to the earliest modern human fossil sites and to postulated dispersal routes. The record shows varied climate at the end of the penultimate glacial, followed by an abrupt change to relatively stable moist climate during the last interglacial. These conditions would have favored population growth and range expansion, supporting models of early, multiple dispersals of modern humans from AfricapublishersversionPeer reviewe

What Makes a Data-GIF Understandable?

GIFs are enjoying increasing popularity on social media as a format for data-driven storytelling with visualization; simple visual messages are embedded in short animations that usually last less than 15 seconds and are played in automatic repetition. In this paper, we ask the question, "What makes a data-GIF understandable?" While other storytelling formats such as data videos, infographics, or data comics are relatively well studied, we have little knowledge about the design factors and principles for "data-GIFs". To close this gap, we provide results from semi-structured interviews and an online study with a total of 118 participants investigating the impact of design decisions on the understandability of data-GIFs. The study and our consequent analysis are informed by a systematic review and structured design space of 108 data-GIFs that we found online. Our results show the impact of design dimensions from our design space such as animation encoding, context preservation, or repetition on viewers' understanding of the GIF's core message. The paper concludes with a list of suggestions for creating more effective Data-GIFs

Prediction of explosive yield and other characteristics of liquid propellant rocket explosions Final report

Explosive hazards and yield predictions for liquid rocket propellant