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Register a new userتطوير موقع ويب تفاعلي يساهم بشكل منهجي في العلاج النفسي السلوكي للأطفال الذين يعانون من مرض التوحد
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Syrian Virtual University رسالة ماجستير
Publication date
2014
and research's language is
العربية
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يعرف التوحد بأنه أحد الاضطرابات النمائية الشاملة يتسم بقصور نوعي في مهارات التواصل والانتباه ومهارات التفاعل الاجتماعي
No English abstract
References used
ابراهيم , فوليت فؤاد (2005) مدخل إلى التربية الخاصة , القاهرة : مكتبة الأنجلو المصرية
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This study aimed at comparative in Communication Skills between who are under the
control of Behavioral Therapeutic and Behavioral & medicinal Therapeutic with Attention
Deficit Hyperactivity Disorder children.
A random sample were selected consis
t of 34 children with ADHD, who visit the psychoclinics
: 14 for first group and 20 for second group aged 6-9 years old.
Children with ADHD scaled by DSM-5, C. Kconners and Vineland Adaptive Behavior
scales (Communication).
The results didn’t reveal statistically significant differences in total score of
Communication between both groups. Besides there weren't statistically significant
differences in branch dimensions of Communication (the Expressive language, the
Receptive language, the Reading and writing) for children with ADHD between both
groups.
Visual Question Answering (VQA) systems are increasingly adept at a variety of tasks, and this technology can be used to assist blind and partially sighted people. To do this, the system's responses must not only be accurate, but usable. It is also v
ital for assistive technologies to be designed with a focus on: (1) privacy, as the camera may capture a user's mail, medication bottles, or other sensitive information; (2) transparency, so that the system's behaviour can be explained and trusted by users; and (3) controllability, to tailor the system for a particular domain or user group. We have therefore extended a conversational VQA framework, called Aye-saac, with these objectives in mind. Specifically, we gave Aye-saac the ability to answer visual questions in the kitchen, a particularly challenging area for visually impaired people. Our system can now answer questions about quantity, positioning, and system confidence in regards to 299 kitchen objects. Questions about the spatial relations between these objects are particularly helpful to visually impaired people, and our system output more usable answers than other state of the art end-to-end VQA systems.
The Study is directed to reveal how effective the behavioral-cognitive therapy in reducing the symptoms of obsession through a program applied on individuals with compulsive behavior and/or obsessive thinking involved in the study.
The study uses co
gnitive therapy techniques and the (intense) exposure and response prevention technique (ERP) that has proved to be efficient in many researches and clinical studies so as to know whether the statistically significant. Differences between the averages of the means of the sample to be studied on a scale for measuring the obsession symptoms before and after applying the therapeutically program on the
individuals involved in the sample are attributed to the effect of the program designed.
In this study, the sample involves individuals with obsessive compulsive disorder according to Yale Brown Scale, and it includes 12 patients (3) males and (9) females aging (20-25) who were supervised by psychiatrists. The researcher uses the one-group system; i.e., premeasurement – therapy or intervention – post-measurement.
One challenge in evaluating visual question answering (VQA) models in the cross-dataset adaptation setting is that the distribution shifts are multi-modal, making it difficult to identify if it is the shifts in visual or language features that play a
key role. In this paper, we propose a semi-automatic framework for generating disentangled shifts by introducing a controllable visual question-answer generation (VQAG) module that is capable of generating highly-relevant and diverse question-answer pairs with the desired dataset style. We use it to create CrossVQA, a collection of test splits for assessing VQA generalization based on the VQA2, VizWiz, and Open Images datasets. We provide an analysis of our generated datasets and demonstrate its utility by using them to evaluate several state-of-the-art VQA systems. One important finding is that the visual shifts in cross-dataset VQA matter more than the language shifts. More broadly, we present a scalable framework for systematically evaluating the machine with little human intervention.
Timeline Summarisation (TLS) aims to generate a concise, time-ordered list of events described in sources such as news articles. However, current systems do not provide an adequate way to adapt to new domains nor to focus on the aspects of interest t
o a particular user. Therefore, we propose a method for interactively learning abstractive TLS using Reinforcement Learning (RL). We define a compound reward function and use RL to fine-tune an abstractive Multi-document Summarisation (MDS) model, which avoids the need to train using reference summaries. One of the sub-reward functions will be learned interactively from user feedback to ensure the consistency between users' demands and the generated timeline. The other sub-reward functions contribute to topical coherence and linguistic fluency. We plan experiments to evaluate whether our approach could generate accurate and precise timelines tailored for each user.
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