Do graphical overviews facilitate or hinder comprehension in hypertext?

Educational hypertexts usually include graphical overviews, conveying the structure of the text schematically with the aim of fostering comprehension. Despite the claims about their relevance, there is currently no consensus on the impact that hypertext overviews have on the reader’s comprehension. In the present paper we have explored how hypertext overviews might affect comprehension with regard to (a) the time at which students read the overview and (b) the hypertext difficulty. The results from two eye-tracking studies revealed that reading a graphical overview at the beginning of the hypertext is related to an improvement in the participant’s comprehension of quite difficult hypertexts, whereas reading an overview at the end of the hypertext is linked to a decrease in the student’s comprehension of easier hypertexts. These findings are interpreted in light of the Assimilation Theory and the Active Processing model. Finally, the key educational and hypertext design implications of the results are discussed.     

Are visual programming languages better? The role of imagery in program comprehension

This paper presents one experiment to explain why and under which circumstances visual programming languages would be easier to understand than textual programming languages. Towards this goal we bring together research from psychology of programming and image processing. According to current theories of imagery processing imagery facilitates a quicker access to semantic information. Thus, visual programming languages should allow for quicker construction of a mental representation based on data flow relationships of a program than procedural languages. To test this hypothesis the mental models of C and spreadsheet programmers were assessed in different program comprehension situations. The results showed that spreadsheet programmers developed data flow based mental representations in all situations, while C programmers seemed to access first a control flow and then data flow based mental representations. These results could help to expand theories of mental models from psychology of programming to account for the effect of imagery.     

Does training in the cold improve cold performance?

Despite the well-described physiological response to cold, little is known about how to best train persons to perform motor tasks in cold conditions. It is unclear if principles of training specificity would apply to motor skill training when cold because cold exposure reduces tactile sensitivity and cognitive function, which may reduce rather than enhance training efficacy. The purpose of this study is to determine whether training in the cold facilitates performance in the cold. To do this, we investigated the effect of cold or thermoneutral training on performance of the Grooved Pegboard Task. Twenty persons (11M, 9F, mean age 31.2 ± 5.44 years) visited the lab on two separate days and were randomly assigned to either a cold (5M, 5F) or thermoneutral (6M, 4F) training group. On day one, participants were tested at baseline and then performed 20 repetitions of the task according to their respective group assignment. Prior to each task repetition during training, the cold training group immersed their hand in cold water (2 °C) while the thermoneutral group immersed their hand in thermoneutral water (34 °C). Following training, participants were tested once again (immediate retention test). During testing, participants performed the task twice; once after immersing their hands in cold water and once after immersing their hands in thermoneutral water. On day two, delayed retention tests were performed. Time to completion and number of errors were recorded during testing. There were no differences in time to completion at delayed retention tests between thermoneutral and cold-trained groups (p = 0.434). The incidence of errors was significantly less in the cold-trained group than the thermoneutral training group at delayed retention testing (p = 0.035). The main finding of this study was that dexterity but not speed was improved by cold training. Further research is required but the findings presented here suggest that industries that require motor tasks in the cold could benefit from training employees in cold conditions.     

How do colors influence the haptic perception of textured surfaces?

Multimodality is considered a promising approach for universal access, and haptic interaction has the potential to constitute an added dimension to multimodal interfaces. This paper describes the influence of colors on the haptic perception of textured surfaces, based on 8 experiments. Our results show that (1) colors do have an influence on haptic perception, but they do not make the perception error rate higher than when no color is used; (2) up to 6 different types of colors can be used in haptic interfaces without worsening the haptic perception; (3) yellow has an error rate that is statistically significantly lower than that of 3 other color conditions, and can be used without worsening the haptic perception; (4) our finding of two special orders for haptic perception demonstrates that human haptic perception is very sensitive to continuously increasing or decreasing changes of roughness, but has difficulty discerning randomly changed roughness.     

Do automated program repair techniques repair hard and important bugs?

Existing evaluations of automated repair techniques focus on the fraction of the defects for which the technique can produce a patch, the time needed to produce patches, and how well patches generalize to the intended specification. However, these evaluations have not focused on the applicability of repair techniques and the characteristics of the defects that these techniques can repair. Questions such as “Can automated repair techniques repair defects that are hard for developers to repair?” and “Are automated repair techniques less likely to repair defects that involve loops?” have not, as of yet, been answered. To address such questions, we annotate two large benchmarks totaling 409 C and Java defects in real-world software, ranging from 22K to 2.8M lines of code, with measures of the defect’s importance, the developer-written patch’s complexity, and the quality of the test suite. We then analyze relationships between these measures and the ability to produce patches for the defects of seven automated repair techniques —AE, GenProg, Kali, Nopol, Prophet, SPR, and TrpAutoRepair. We find that automated repair techniques are less likely to produce patches for defects that required developers to write a lot of code or edit many files, or that have many tests relevant to the defect. Java techniques are more likely to produce patches for high-priority defects. Neither the time it took developers to fix a defect nor the test suite’s coverage correlate with the automated repair techniques’ ability to produce patches. Finally, automated repair techniques are less capable of fixing defects that require developers to add loops and new function calls, or to change method signatures. These findings identify strengths and shortcomings of the state-of-the-art of automated program repair along new dimensions. The presented methodology can drive research toward improving the applicability of automated repair techniques to hard and important bugs.     

Do information systems improve the quality of clinical research? Results of a randomized trial in a cooperative multi-institutional cancer group

A facsimile communications network was established to serve eight randomly selected medical centers belonging to the Southeastern Cancer Study Group (SEG) to test whether clinical algorithms could augment protocol compliance and patient safety. An SEG protocol (75HD0103) for testing alternative chemotherapy regimens in Advanced Hodgkin's Disease was rewritten as a clinical algorithm. The algorithm generates treatment advice rules, emulating how the clinical researcher would accurately and appropriately apply the general protocol to an individual patient's specific visit, considering his prior response to therapy. The visit-specific advice rules were typed onto general encounter forms and sent to the oncologists over the facsimile equipment prior to each therapy visit. A facsimile of the completed form was transmitted back. Protocol compliance, as judged by explicit criteria on a visit-by-visit basis, was 94% in the algorithm user group and 64% in the nonuser group (p < 0.001). Two measures of hematologic toxicity, “low” counts and “toxic” nadirs, were associated more often with protocol noncompliance. We conclude that prospective information management can improve the “control” in cooperative controlled clinical trials.     

Do you believe in the advantage of expert systems in industrial ergonomics?

Reasons for reservations about accepting the recommendations of industrial ergonomics are first explored. A knowledge deficiency is ascertained which results in a general dependency on ergonomic experts. The experts, however, are rarely able to communicate their knowledge in a form applicable by a practitioner. The development and employment of expert systems suitable for use in work design problems are proposed to resolve this dilemma. The question of whether an interest in expert systems for industrial ergonomics can be assumed is considered. The necessary conditions for the successful development and introduction of expert systems for industrial ergonomics are derived. The extent to which currently available expert system technology can support the typical procedures in industrial ergonomics is subsequently examined.     

Do visual word segmentation cues improve reading performance in Chinese reading？

Abstract

It is controversial whether providing visual word segmentation cues can improve Chinese reading performance. This study investigated this topic by examining how visual word segmentation cues such as grey highlighting, red colour and interword spacing influence global sentence reading and local word recognition during reading Chinese text in three experiments. The results showed that interword spacing could facilitate local word recognition but could not increase reading speed. In contrast, grey highlighting and red colour could improve neither local word recognition nor global sentence reading performance. Instead, these cues increased the number of fixations and saccades, resulting in slower reading speed. These results suggest that even red colour is not a practically visual cue for Chinese word segmentation and the corresponding mechanisms were discussed.

Practitioner Summary: We studied how visual cues such as grey highlighting, red colour and interword spacing influenced Chinese reading performance. Our data showed that even the red colour was not an efficient cue for Chinese word segmentation. The corresponding mechanisms and future direction were discussed regarding how to improve Chinese reading performance.     

Do men and women differ in privacy? Gendered privacy and (in)equality in the Internet

This paper investigates how personal privacy behavior and confidence differ by gender, focusing on the dimensions of online privacy data protection and release. A hierarchical regression analysis of cross-sectional survey of a national sample (n = 419) revealed that men and women differed on the level of privacy protection; however, gender had no direct effect on the extent to which data release was exercised. Additionally, gender had a positive association with confidence in privacy protection, but not in the dimension of release. Our study suggests that the gender may affect subjective well-being of online privacy and potentially exacerbate the disparity rooted in socialization of gender. Implications of the findings are discussed in light of Internet access, skill and effort required for building and maintaining privacy, and the important role played by gender in indicating the need for gender-sensitive policy awareness.     

Is three the magic number? The role of ergonomic principles in cross country comprehension of road traffic signs

Abstract

Road sign comprehension plays an important part in road safety management, particularly for those drivers who are travelling in an unfamiliar country. Previous research has established that comprehension can be improved if signs are designed to adhere to ergonomic principles. However, it may be difficult for sign designers to incorporate all the principles into a single sign and may thus have to make a judgement as to the most effective ones. This study surveyed drivers in three countries to ascertain their understanding of a range of road signs, each of which conformed in varying degrees and combinations to the ergonomic principles. We found that using three of the principles was the most effective and that the most important one was that relating to standardisation; the colours and shapes used were key to comprehension. Other concepts which related to physical and spatial characteristics were less important, whilst conceptual compatibility did not aid comprehension at all.

Practitioner Summary: This study explores how road sign comprehension can be improved using ergonomic principles, with particular reference to cross-border drivers. It was found that comprehension can be improved significantly if standardisation is adhered to and if at least three principles are used.     

Can computational biology improve the phylogenetic analysis of insulin?

Using computational biology, we have depicted the insulin phylogenetics. We have also analyzed the sequence alignment and sequence logos formation for both the insulin chain A and B for three groups namely, the mammalian group, vertebrates group and fish group. We have also analyzed cladograms of insulin for the mammalian group. In accordance with that path lengths, matrix for distance analysis, matching representation of nodes of the cladogram and dissimilarity between two nodes have been performed for both of the A and B chains of the mammalian group. Our results show that 12 amino acid residues (GlyA1, IleA2, ValA3, TyrA19, CysA20, AsnA21, LeuB6, GlyB8, LeuB11, ValB12, GlyB23 and PheB24) are highly conserved for all groups and among them some (GlyA1, IleA2, ValA3);(TyrA19, CysA20, AsnA21) are continuous. This study shows a rapid method to calculate the amino acid sequences in terms of evolutionary conservation rates as well as molecular phylogenetics.     

Do Markov-switching models capture nonlinearities in the data?: Tests using nonparametric methods

Markov-switching models have become popular alternatives to linear autoregressive models. Many papers which estimate nonlinear models make little attempt to demonstrate whether the nonlinearities they capture are of interest or if the models differ substantially from the linear option. By simulating the models and nonparametrically estimating functions of the simulated data, we can evaluate if and how the nonlinear and linear models differ.     

Do Accelerating Turing Machines Compute the Uncomputable?

Accelerating Turing machines have attracted much attention in the last decade or so. They have been described as “the work-horse of hypercomputation” (Potgieter and Rosinger 2010: 853). But do they really compute beyond the “Turing limit”—e.g., compute the halting function? We argue that the answer depends on what you mean by an accelerating Turing machine, on what you mean by computation, and even on what you mean by a Turing machine. We show first that in the current literature the term “accelerating Turing machine” is used to refer to two very different species of accelerating machine, which we call end-stage-in and end-stage-out machines, respectively. We argue that end-stage-in accelerating machines are not Turing machines at all. We then present two differing conceptions of computation, the internal and the external, and introduce the notion of an epistemic embedding of a computation. We argue that no accelerating Turing machine computes the halting function in the internal sense. Finally, we distinguish between two very different conceptions of the Turing machine, the purist conception and the realist conception; and we argue that Turing himself was no subscriber to the purist conception. We conclude that under the realist conception, but not under the purist conception, an accelerating Turing machine is able to compute the halting function in the external sense. We adopt a relatively informal approach throughout, since we take the key issues to be philosophical rather than mathematical.     

Does segmentation always improve model performance in credit scoring?

Credit scoring allows for the credit risk assessment of bank customers. A single scoring model (scorecard) can be developed for the entire customer population, e.g. using logistic regression. However, it is often expected that segmentation, i.e. dividing the population into several groups and building separate scorecards for them, will improve the model performance. The most common statistical methods for segmentation are the two-step approaches, where logistic regression follows Classification and Regression Trees (CART) or Chi-squared Automatic Interaction Detection (CHAID) trees etc. In this research, the two-step approaches are applied as well as a new, simultaneous method, in which both segmentation and scorecards are optimised at the same time: Logistic Trees with Unbiased Selection (LOTUS). For reference purposes, a single-scorecard model is used. The above-mentioned methods are applied to the data provided by two of the major UK banks and one of the European credit bureaus. The model performance measures are then compared to examine whether there is improvement due to the segmentation methods used. It is found that segmentation does not always improve model performance in credit scoring: for none of the analysed real-world datasets, the multi-scorecard models perform considerably better than the single-scorecard ones. Moreover, in this application, there is no difference in performance between the two-step and simultaneous approaches.     

Do we need formal education in visualization?

The following three reasons are sufficient to answer this question in the affirmative: careless mapping from data to pictures may lead to erroneous interpretation; a substantial amount of knowledge is necessary to generate images depicting complex information in a way that prevents erroneous interpretation; and decision making is increasingly based on visual representations. The organization and content of the core topics of visualization were finalized at a 1997 workshop at the Colorado School of Mines. These comprise the following eight themes: introduction to visualization; the data; the user and the task; mapping process; the representations; interaction issues; concepts of the visualization process; and systems and tools. The needs of educators and students vary too widely to bring one curriculum into focus. Instead, the eight themes recommended can be expanded into a curriculum, or compressed into several subtopics of a high-performance computing or computer graphics course. The themes can stand as separate modules, taught in a different order from that suggested. While my collaborators and I strongly recommend covering each of the core topics, we also encourage educators to expand individual themes to encompass the particular objectives of their students     

Can the crowd tell how I feel? Trait empathy and ethnic background in a visual pain judgment task

Many advocate for artificial agents to be empathic. Crowdsourcing could help, by facilitating human-in-the-loop approaches and data set creation for visual emotion recognition algorithms. Although crowdsourcing has been employed successfully for a range of tasks, it is not clear how effective crowdsourcing is when the task involves subjective rating of emotions. We examined relationships between demographics, empathy, and ethnic identity in pain emotion recognition tasks. Amazon MTurkers viewed images of strangers in painful settings, and tagged subjects’ emotions. They rated their level of pain arousal and confidence in their responses, and completed tests to gauge trait empathy and ethnic identity. We found that Caucasian participants were less confident than others, even when viewing other Caucasians in pain. Gender correlated to word choices for describing images, though not to pain arousal or confidence. The results underscore the need for verified information on crowdworkers, to harness diversity effectively for metadata generation tasks.     

What Do the Sun and the Sky Tell Us About the Camera?

As the main observed illuminant outdoors, the sky is a rich source of information about the scene. However, it is yet to be fully explored in computer vision because its appearance in an image depends on the sun position, weather conditions, photometric and geometric parameters of the camera, and the location of capture. In this paper, we analyze two sources of information available within the visible portion of the sky region: the sun position, and the sky appearance. By fitting a model of the predicted sun position to an image sequence, we show how to extract camera parameters such as the focal length, and the zenith and azimuth angles. Similarly, we show how we can extract the same parameters by fitting a physically-based sky model to the sky appearance. In short, the sun and the sky serve as geometric calibration targets, which can be used to annotate a large database of image sequences. We test our methods on a high-quality image sequence with known camera parameters, and obtain errors of less that 1% for the focal length, 1° for azimuth angle and 3° for zenith angle. We also use our methods to calibrate 22 real, low-quality webcam sequences scattered throughout the continental US, and show deviations below 4% for focal length, and 3° for the zenith and azimuth angles. Finally, we demonstrate that by combining the information available within the sun position and the sky appearance, we can also estimate the camera geolocation, as well as its geometric parameters. Our method achieves a mean localization error of 110 km on real, low-quality Internet webcams. The estimated viewing and illumination geometry of the scene can be useful for a variety of vision and graphics tasks such as relighting, appearance analysis and scene recovery.     

REACTKIN—a program for modelling the chemical reactions in electrolytes solutions

In this paper, REACTKIN, the new computer program for modelling the kinetics of complex homogeneous chemical reactions in electrolyte and non-electrolyte solutions has been presented. This program makes possible the creation of a model of a reaction in the convenient form of a graph as well as simulating the course of a reaction on the basis of the model created. REACTKIN allows the determination of the rate constants of elementary reactions using experimental kinetic data concerning the influence of the ionic strength of the solution. The program REACTKIN can be of importance in the studies of multi-step chemical reactions in electrolyte solutions as well as in chemistry education.