109 research outputs found
Time exceptions in sequence diagrams
UML sequence diagrams partially describe a system. We show how the description may be augmented with exceptions triggered by the violation of timing constraints and compare our approach to those of the UML 2.1 simple time model, the UML Testing Profile and the UML profile for Schedulability, Performance and Time. We give a formal definition of time exceptions in sequence diagrams and show that the concepts are compositional. An ATM example is used to explain and motivate the concepts
Phadiatop Infant in the Diagnosis of Atopy in Children with Allergy-Like Symptoms
Background and Objective. Allergy-like symptoms such as wheezing and eczema are common in young children and an early diagnosis is important to initiate correct management. The objective of this study was to evaluate the diagnostic performance of Phadiatop Infant, an in vitro test for determination of early sensitisation to food and inhalant allergens. Patients and Methods. The study was conducted, retrospectively, using frozen sera from 122 children (median age 2.7 years) admitted to the hospital with suspected allergic symptoms. The doctor's diagnosis atopic/nonatopic was based on routinely used procedures such as clinical evaluation, SPT, total and allergen-specific IgE antibodies. The performance of Phadiatop Infant was evaluated in a blinded manner against this diagnosis. Results. Eighty-four of the 86 children classified as atopic showed a positive Phadiatop Infant test. Thirty-six were classified as nonatopic, 32 of who had a negative test. With a prevalence of atopy of 70% in this population, this gives a sensitivity of 98%, a specificity of 89%, and a positive and negative predictive value of 95% and 94%, respectively. Conclusion. The results from the present study suggest that Phadiatop Infant could be recommended as a complement to the clinical information in the differential diagnosis on IgE-mediated disease in young children with allergy-like symptoms
Cortisol levels and cognitive profile in major depression: A comparison of currently and previously depressed patients
Source at https://doi.org/10.1016/j.psyneuen.2018.08.024.The association between depressive symptoms and elevated cortisol levels, and depression and cognitive functioning, has been less robust in outpatients with symptoms in the mild to moderate range. Furthermore, the association between elevated cortisol levels and cognitive functioning is unclear. In the present study, currently depressed (nâ=â37), previously depressed (nâ=â81) and never depressed controls (nâ=â50) were assessed on a range of neuropsychological measures. Salivary cortisol was measured in the morning and evening. Participants with current depression were non-hospitalized and had symptoms predominately in the mild to moderate range. Elevated salivary evening cortisol, but not morning cortisol, was significantly related to depressive symptoms. The difference in cortisol levels between the previously depressed group and the never depressed controls was not significant. The groups had significantly different cognitive profiles, with the currently depressed performing poorer on tasks related to working memory compared to the never depressed controls. Both the currently and previously depressed performed worse on attentional tasks. The findings indicate that outpatients with mild to moderate depression have elevated cortisol levels and limited mild cognitive impairments. Furthermore, mild impairments in attention may persist after remission, indicating that this could be a trait-marker in depression. The present study did not find support for a significant relationship between cortisol and cognitive functioning
Adaptive Media Streaming to Mobile Devices: Challenges, Enhancements, and Recommendations
Video streaming is predicted to become the dominating traffic in mobile broadband networks. At
the same time, adaptive HTTP streaming is developing into the preferred way of streaming media
over the Internet. In this paper, we evaluate how different components of a streaming system can be
optimized when serving content to mobile devices in particular. We first analyze the media traffic from
a Norwegian network and media provider. Based on our findings, we outline benefits and challenges for
HTTP streaming, on the sender and the receiver side, and we investigate how HTTP-based streaming
affects server performance. Furthermore, we discuss various aspects of efficient coding of the video
segments from both performance and user perception point of view. The final part of the paper
studies efficient adaptation and delivery to mobile devices over wireless networks. We experimentally
evaluate and improve adaptation strategies, multilink solutions, and bandwidth prediction techniques. Based on the results from our evaluations, we make recommendations for how an adaptive streaming
system should handle mobile devices. Small changes, or simple awareness of how users perceive quality,
can often have large effects
Enhancing questioning skills through child avatar chatbot training with feedback
Training child investigative interviewing skills is a specialized task. Those being
trained need opportunities to practice their skills in realistic settings and receive
immediate feedback. A key step in ensuring the availability of such opportunities
is to develop a dynamic, conversational avatar, using artificial intelligence (AI)
technology that can provide implicit and explicit feedback to trainees. In the
iterative process, use of a chatbot avatar to test the language and conversation
model is crucial. The model is fine-tuned with interview data and realistic
scenarios. This study used a pre-post training design to assess the learning
effects on questioning skills across four child interview sessions that involved
training with a child avatar chatbot fine-tuned with interview data and realistic
scenarios. Thirty university students from the areas of child welfare, social
work, and psychology were divided into two groups; one group received direct
feedback (nâ=â12), whereas the other received no feedback (nâ=â18). An automatic
coding function in the language model identified the question types. Information
on question types was provided as feedback in the direct feedback group only.
The scenario included a 6-year-old girl being interviewed about alleged physical
abuse. After the first interview session (baseline), all participants watched a video
lecture on memory, witness psychology, and questioning before they conducted
two additional interview sessions and completed a post-experience survey. One
week later, they conducted a fourth interview and completed another postexperience survey. All chatbot transcripts were coded for interview quality. The
language modelâs automatic feedback function was found to be highly reliable
in classifying question types, reflecting the substantial agreement among the
raters [Cohenâs kappa (Îş)â=â0.80] in coding open-ended, cued recall, and closed
questions. Participants who received direct feedback showed a significantly
higher improvement in open-ended questioning than those in the non-feedback
group, with a significant increase in the number of open-ended questions used
between the baseline and each of the other three chat sessions. This study
demonstrates that child avatar chatbot training improves interview quality with
regard to recommended questioning, especially when combined with direct
feedback on questioning
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