O aluno com deficiência visual nas aulas de educação física : análise do processo inclusivo = The student with visual impairments : analysis of inclusive process

Universidade Estadual de Campinas . Faculdade de Educação Física

Visual functional analysis in medical imaging

Aims of study: 1) Describe the importance of human visual system on lesion detection in medical imaging perception research; 2) Discuss the relevance of research in medical imaging addressing visual function analysis; 3) Identify visual function tests which could be conducted on observers prior to participation in medical imaging perception research.

High-Content Analysis of Breast Cancer Using Single-Cell Deep Transfer Learning

High-content analysis has revolutionized cancer drug discovery by identifying substances that alter the phenotype of a cell, which prevents tumor growth and metastasis. The high-resolution biofluorescence images from assays allow precise quantitative measures enabling the distinction of small molecules of a host cell from a tumor. In this work, we are particularly interested in the application of deep neural networks (DNNs), a cutting-edge machine learning method, to the classification of compounds in chemical mechanisms of action (MOAs). Compound classification has been performed using image-based profiling methods sometimes combined with feature reduction methods such as principal component analysis or factor analysis. In this article, we map the input features of each cell to a particular MOA class without using any treatment-level profiles or feature reduction methods. To the best of our knowledge, this is the first application of DNN in this domain, leveraging single-cell information. Furthermore, we use deep transfer learning (DTL) to alleviate the intensive and computational demanding effort of searching the huge parameter's space of a DNN. Results show that using this approach, we obtain a 30% speedup and a 2% accuracy improvement.

Visual data analysis in air traffic management

Visual data mining, multi-dimensional scaling, POLARMAP, Sammon's mapping, clustering, outlier detection

The Patientʼs Perception of Eosinophilic Esophagitis Related Symptoms: a Qualitative Content Analysis

Background and Aims: The international EEsAI study group is currently developing an activity index for Eosinophilic Esophagitis (EoE). A potential discrepancy between patient and physician reported EoE symptoms has not been assessed yet. Therefore, we aimed to evaluate patient reported items describing their EoE activity and to compare these with the physicianʼs perception. Methods: A questionnaire was sent to 100 EoE patients in Switzerland. EoE-related symptoms dependent and independent of food intake were reported by patients. Results were analyzed using a qualitative content analysis and compared with symptoms reported by international EoE experts in Delphi rounds. Results: The questionnaire response rate was 64/100. The following items were developed by combining categories based on patients answers: food-consistency related dysphagia, frequency and severity of dysphagia, food impaction, strategies to avoid food impaction, food allergy, drinking-related retrosternal pain. The following food categories associated with dysphagia were identified: meat, rice, dry bread, French fries, raw, fibrous foods, others. Sports and psychological stress were identified as triggers for non-food intake related EoE symptoms. A good correlation was found between patient and physicianʼs reported EoE related symptoms. Conclusions: There is a good correlation between patient reported symptoms and the physicianʼs perception of clinical items as reported by international EoE experts. These patient reported outcomes will now be incorporated into the EEsAI questionnaire that measures EoE activity.

Inter-rater Reliability of Criteria-Based Content Analysis of Children's Statements of Abuse.

The evaluation of children's statements of sexual abuse cases in forensic cases is critically important and must and reliable. Criteria-based content analysis (CBCA) is the main component of the statement validity assessment (SVA), which is the most frequently used approach in this setting. This study investigated the inter-rater reliability (IRR) of CBCA in a forensic context. Three independent raters evaluated the transcripts of 95 statements of sexual abuse. IRR was calculated for each criterion, total score, and overall evaluation. The IRR was variable for the criteria, with several being unsatisfactory. But high IRR was found for the total CBCA scores (Kendall's W = 0.84) and for overall evaluation (Kendall's W = 0.65). Despite some shortcomings, SVA remains a robust method to be used in the comprehensive evaluation of children's statements of sexual abuse in the forensic setting. However, the low IRR of some CBCA criteria could justify some technical improvements.

Socially Constructed Environmental Issues and Sport: A Content Analysis of Ski Resort Environmental Communications

Due to the impact of sport on the natural environment (UN, 2010), it is important to examine the interplay between environmental issues and sport (Hums, 2010, Mallen & Chard, 2011; Nauright & Pope, 2009; Ziegler, 2007). This research content analyzed 82 ski resort environmental communications (SRECs). These communications were rated for their prominence, breadth, and depth using the delineation of environmental issues provided by the Sustainable Slopes Program (SSP) Charter. This data was compared to the resorts’ degree of environmentally responsible action as rated by the Ski Area Citizens’ Coalition (SACC). An adaptation of Hudson and Miller's (2005) model was then used to classify the ski resorts as inactive, reactive, exploitive, or proactive in their environmental activities. Recommendations have been made for standardization and transparency in environmental disclosures and an environmental management system to aid ski resorts in moving from ad hoc processes to a systematic and comprehensive framework for improving environmental performance.

The Representation of the Feminine in the Portuguese Press : A Content Analysis of the Diário de Notícias Newspaper

This is a brief report of a research project, coordinated by me and funded by the Portuguese Government. It studies ‘The Representation of the Feminine in the Portuguese Press’ (POCI/COM 55780/2004), and works on the content analysis of discourse on the feminine in various Portuguese newspapers, covering the time span of February 1st till April 30th 2006. The paper is divided into two parts: in the first part, I will briefly discuss the typology used to code the text units of selected articles; in the second part, I will explore the most expressive percentages of the first two weeks of February for the content analysis of the Diário de Notícias newspaper. These percentages were obtained with the NVivo 6 qualitative data treatment software programme.

Semantic-level Visual Content Descriptor combining visual and textual cues as collaterals

In this paper, we introduce a novel high-level visual content descriptor which is devised for performing semantic-based image classification and retrieval. The work can be treated as an attempt to bridge the so called “semantic gap”. The proposed image feature vector model is fundamentally underpinned by the image labelling framework, called Collaterally Confirmed Labelling (CCL), which incorporates the collateral knowledge extracted from the collateral texts of the images with the state-of-the-art low-level image processing and visual feature extraction techniques for automatically assigning linguistic keywords to image regions. Two different high-level image feature vector models are developed based on the CCL labelling of results for the purposes of image data clustering and retrieval respectively. A subset of the Corel image collection has been used for evaluating our proposed method. The experimental results to-date already indicates that our proposed semantic-based visual content descriptors outperform both traditional visual and textual image feature models.