A hybrid knowledge and ensemble classification approach for prediction of venous thromboembolism

Clinical narratives such as progress summaries, lab reports, surgical reports, and other narrative texts contain key biomarkers about a patient's health. Evidence-based preventive medicine needs accurate semantic and sentiment analysis to extract and classify medical features as the input to appropriate machine learning classifiers. However, the traditional approach of using single classifiers is limited by the need for dimensionality reduction techniques, statistical feature correlation, a faster learning rate, and the lack of consideration of the semantic relations among features. Hence, extracting semantic and sentiment-based features from clinical text and combining multiple classifiers to create an ensemble intelligent system overcomes many limitations and provides a more robust prediction outcome. The selection of an appropriate approach and its interparameter dependency becomes key for the success of the ensemble method. This paper proposes a hybrid knowledge and ensemble learning framework for prediction of venous thromboembolism (VTE) diagnosis consisting of the following components: a VTE ontology, semantic extraction and sentiment assessment of risk factor framework, and an ensemble classifier. Therefore, a component-based analysis approach was adopted for evaluation using a data set of 250 clinical narratives where knowledge and ensemble achieved the following results with and without semantic extraction and sentiment assessment of risk factor, respectively: a precision of 81.8% and 62.9%, a recall of 81.8% and 57.6%, an F measure of 81.8% and 53.8%, and a receiving operating characteristic of 80.1% and 58.5% in identifying cases of VTE.     

A fog-based security framework for intelligent traffic light control system

Multimedia Tools and Applications - The world is facing many problems including that of traffic congestion. To highlight the issue of traffic congestion worldwide specially in urban areas and to...     

Software assurance practices for mobile applications

Mobile software applications have to cope with a particular environment that involves small size, limited resources, high autonomy requirements, competitive business models and many other challenges. To provide development guidelines that respond to these needs, several practices have been introduced; however, it is not clear how these guidelines may contribute to solve the issues present in the mobile domain. Furthermore, the rapid evolution of the mobile ecosystem challenges many of the premises upon which the proposed practices were designed. In this paper, we present a survey of the literature on software assurance practices for mobile applications, with the objective of describing them and assessing their contribution and success. We identified, organized and reviewed a body of research that spans in three levels: software development processes, software product assurance practices, and software implementation practices. By carrying out this literature survey, we reviewed the different approaches that researchers on Software Engineering have provided to address the needs that raise in the mobile software development arena. Moreover, we review the evolution of these practices, identifying how the constant changes and modernization of the mobile execution environment has impacted the methods proposed in the literature. Finally, we introduced discussion on the application of these practices in a real productive setting, opening an area for further research that may determine if practitioners have followed the proposed assurance paradigms.     

Intrinsic CFRP-metal-hybrids with rubber interface for the improvement of the damping behaviour

This paper presents an integrated passive damping approach in hybrid metal-CFRP parts for structural applications. In this concept a viscoelastic material is embedded in the joint zone of the hybrid component. To examine the connection strength single-lap-joint specimens were produced and tested and the influence of the used material combinations, different surface structures, and different process parameters i.e. the moment of cross-linking were evaluated. Afterwards, the metal-CFRP hybrids were tested in quasi-static tests to assess their connection strength and failure behaviour. Dynamic cyclic tensile tests with step-wise increased loading conditions were performed to determine the specimens damping behaviour and to estimate their fatigue performance. Finally, these results are compared to a state of the art metal-CFRP hybrid with rivets connecting both materials.     

On stochastic comparisons of finite mixtures for some semiparametric families of distributions

In this paper, we consider the classical finite mixture model, which is an effective tool for modeling lifetime distributions for random samples from heterogeneous populations. We discuss new results on stochastic comparison for two finite mixtures when each of them is drawn from one of the following semiparametric families, i.e., proportional hazards, accelerated lifetime and proportional reversed hazards.     

Is the List of Incomplete Open Cubes Complete?

Variations of Incomplete Open Cubes is the major project by the twentieth-century conceptual artist Sol LeWitt. In this paper we interpret the enumerative component of the project as embeddings of graphs. This formulation permits use of an algorithm to check the completeness of the list of the structures produced by the artist. Our conclusion is that the artist found the correct number of structures (that is, 122), but that his list contains a mistake in the presentation of a pair of incomplete cubes, a discovery that appears not to have been noted before.     

Semantic word shifts in a scientific domain

Understanding semantic word shifts in scientific domains is essential for facilitating interdisciplinary communication. Using a data set of published papers in the field of information retrieval (IR), this paper studies the semantic shifts of words in IR based on mining per-word topic distribution over time. We propose that semantic word shifts not only occur over time, but also over topics. The shifts are examined from two perspectives, the topic-level and the context-level. According to the over-time word-topic distribution, stable words and unstable words are recognized. The diverging and converging trends in the unstable type reveal characteristics of the topic evolution process. The context-level shifts are further detected by similarities between word vectors. Our work associates semantic word shifts with the evolving of topics, which facilitates a better understanding of semantic word shifts from both topics and contexts.