Categorizing Developer Information Needs in Software Ecosystems

We present the results of an investigation into the nature of the information needs of software developers who work in projects that are part of larger ecosystems. In an open- question survey we asked framework and library developers about their information needs with respect to both their upstream and downstream projects. We investigated what kind of information is required, why is it necessary, and how the developers obtain this information. The results show that the downstream needs are grouped into three categories roughly corresponding to the different stages in their relation with an upstream: selection, adop- tion, and co-evolution. The less numerous upstream needs are grouped into two categories: project statistics and code usage. The current practices part of the study shows that to sat- isfy many of these needs developers use non-specific tools and ad hoc methods. We believe that this is a largely unexplored area of research.

Prometheus Framework for Fuzzy Information Retrieval in Semantic Spaces

This paper introduces a novel vision for further enhanced Internet of Things services. Based on a variety of data (such as location data, ontology-backed search queries, in- and outdoor conditions) the Prometheus framework is intended to support users with helpful recommendations and information preceding a search for context-aware data. Adapted from artificial intelligence concepts, Prometheus proposes user-readjusted answers on umpteen conditions. A number of potential Prometheus framework applications are illustrated. Added value and possible future studies are discussed in the conclusion.

Repeatedly experiencing information overload in a product customization: a case of sequential overchoice

The present study demonstrates how consumers can suffer from sequential overchoice. Customizing a tailor-made suit from combined-attribute choices (e.g., deciding on color and fabric in combination) leads to less satisfaction and less additional consumption than customizing it from single-attribute choices (e.g., deciding on color, then on fabric). The effect is mediated by information overload and moderated by consideration set size.

Applications of random set theory in econometrics

In recent years, the econometrics literature has shown a growing interest in the study of partially identified models, in which the object of economic and statistical interest is a set rather than a point. The characterization of this set and the development of consistent estimators and inference procedures for it with desirable properties are the main goals of partial identification analysis. This review introduces the fundamental tools of the theory of random sets, which brings together elements of topology, convex geometry, and probability theory to develop a coherent mathematical framework to analyze random elements whose realizations are sets. It then elucidates how these tools have been fruitfully applied in econometrics to reach the goals of partial identification analysis.

A Quantitative Analysis of Developer Information Needs in Software Ecosystems

We present the results of an investigation into the nature of information needs of software developers who work in projects that are part of larger ecosystems. This work is based on a quantitative survey of 75 professional software developers. We corroborate the results identified in the sur- vey with needs and motivations proposed in a previous sur- vey and discover that tool support for developers working in an ecosystem context is even more meager than we thought: mailing lists and internet search are the most popular tools developers use to satisfy their ecosystem-related information needs.

Information needs in parents of long-term childhood cancer survivors.

BACKGROUND Parents' knowledge about cancer, treatment, potential late effects and necessary follow-up is important to reassure themselves and motivate their child to participate in regular follow-up. We aimed to describe (i) parents' perception of information received during and after treatment; (ii) parents' current needs for information today, and to investigate; and (iii) associations between information needs and socio-demographic and clinical characteristics. METHODS As part of the Swiss Childhood Cancer Survivor Study, a follow-up questionnaire was sent to parents of survivors, diagnosed < 16 years and after 1990, and aged 11-17 years at study. We assessed parents' perception of information received and information needs, concerns about consequences of the cancer and socio-demographic information. Information on clinical data was available from the Swiss Childhood Cancer Registry. RESULTS Of 309 eligible parents, 189 responded (67%; mean time since diagnosis: 11.3 years, SD = 2.5). Parents perceived to have received verbal information (on illness: verbal 91%, written 40%; treatment: verbal 88%, written 46%; follow-up: verbal 85% written 27%; late effects: verbal 75%, written 19%). Many parents reported current information needs, especially on late effects (71%). The preferred source was written general (28%) or verbal information (25%), less favored was online information (12%). Information needs were associated with migration background (P = 0.039), greater concerns about consequences of cancer (P = 0.024) and no information received (P = 0.035). CONCLUSION Parents reported that they received mainly verbal information. However, they still needed further information especially about possible late effects. Individual long-term follow-up plans, including a treatment summary, should be provided to each survivor, preferably in written format.

Decomposing speed of information processing in elementary cognitive tasks

Many studies obtained reliable individual differences in speed of information processing (SIP) as measured by elementary cognitive tasks (ECTs). ECTs usually employ response times (RT) as measure of SIP, but different ECTs target different cognitive processes (e.g., simple or choice reaction, inhibition). Here we used modified versions of the Hick and the Eriksen Flanker task to examine whether these tasks assess dissociable or common aspects of SIP. In both tasks, task complexity was systematically varied across three levels. RT data were collected from 135 participants. Applying fixed-links modeling, RT variance increasing with task complexity was separated from RT variance unchanging across conditions. For each task, these aspects of variance were represented by two independent latent variables. The two latent variables representing RT variance not varying with complexity of the two tasks were virtually identical (r = .83). The latent variables representing increasing complexity in the two tasks were also highly correlated (r = .72) but clearly dissociable. Thus, RT measures contain both task-unspecific, person-related aspects of SIP as well as task-specific aspects indicating the cognitive processes manipulated with the respective task. Separating these aspects of SIP facilitates the interpretation of individual differences in RT.

Perception of causality in schizophrenia spectrum disorder

Patients with schizophrenia spectrum disorders often maintain deviating views on cause-effect relationships, especially when positive and disorganization symptoms are manifest. Altered perceived causality is prominent in delusional ideation, in ideas of reference, and in the mentalizing ability (theory of mind [ToM]) of patients. Perceiving causal relationships may be understood either as higher order cognitive reasoning or as low-level information processing. In the present study, perception of causality was investigated as a low-level, preattentional capability similar to gestalt-like perceptual organization. Thirty-one patients (24 men and 7 women with mean age 27.7 years) and the same number of healthy control subjects matched to patients with respect to age and sex were tested. A visual paradigm was used in which 2 identical discs move, from opposite sides of a monitor, steadily toward and then past one another. Their coincidence generates an ambiguous, bistable percept (discs either "stream through" or "bounce off" one another). The bouncing perception, ie, perceived causality, is enhanced when auditory stimuli are presented at the time of coincidence. Psychopathology was measured using the Positive and Negative Syndrome Scale. It was found that positive symptoms were strongly associated with increased perceived causality and disorganization with attenuated perceived causality. Patients in general were not significantly different from controls, but symptom subgroups showed specifically altered perceived causality. Perceived causality as a basic preattentional process may contribute to higher order cognitive alterations and ToM deficiencies. It is suggested that cognitive remediation therapy should address both increased and reduced perception of causality.

Unifying energy minimization and mutual information maximization for robust 2D/3D registration of X-ray and CT images

Similarity measure is one of the main factors that affect the accuracy of intensity-based 2D/3D registration of X-ray fluoroscopy to CT images. Information theory has been used to derive similarity measure for image registration leading to the introduction of mutual information, an accurate similarity measure for multi-modal and mono-modal image registration tasks. However, it is known that the standard mutual information measure only takes intensity values into account without considering spatial information and its robustness is questionable. Previous attempt to incorporate spatial information into mutual information either requires computing the entropy of higher dimensional probability distributions, or is not robust to outliers. In this paper, we show how to incorporate spatial information into mutual information without suffering from these problems. Using a variational approximation derived from the Kullback-Leibler bound, spatial information can be effectively incorporated into mutual information via energy minimization. The resulting similarity measure has a least-squares form and can be effectively minimized by a multi-resolution Levenberg-Marquardt optimizer. Experimental results are presented on datasets of two applications: (a) intra-operative patient pose estimation from a few (e.g. 2) calibrated fluoroscopic images, and (b) post-operative cup alignment estimation from single X-ray radiograph with gonadal shielding.