344 research outputs found
Bagging ensemble selection for regression
Bagging ensemble selection (BES) is a relatively new ensemble learning strategy. The strategy can be seen as an ensemble of the ensemble selection from libraries of models (ES) strategy. Previous experimental results on binary classiïŹcation problems have shown that using random trees as base classiïŹers, BES-OOB (the most successful variant of BES) is competitive with (and in many cases, superior to) other ensemble learning strategies, for instance, the original ES algorithm, stacking with linear regression, random forests or boosting. Motivated by the promising results in classiïŹcation, this paper examines the predictive performance of the BES-OOB strategy for regression problems. Our results show that the BES-OOB strategy outperforms Stochastic Gradient Boosting and Bagging when using regression trees as the base learners. Our results also suggest that the advantage of using a diverse model library becomes clear when the model library size is relatively large. We also present encouraging results indicating that the non negative least squares algorithm is a viable approach for pruning an ensemble of ensembles
âTrapped in an Empty Waiting RoomââThe Existential Human Core of Loneliness in Old Age: A Meta-Synthesis
Loneliness in old age has a negative influence on quality of life, health and survival. To understand the phenomenon of loneliness in old age, the voices of lonely older adults should be heard. Therefore, the purpose of this meta-synthesis was to synthesize scientific studies of older adultsâ experiences of loneliness. Eleven qualitative articles that met the inclusion criteria were analyzed and synthesized according to Noblit and Hareâs meta-ethnographic approach. The analysis revealed the overriding meaning of the existential human core of loneliness in old age expressed through the metaphor "trapped in an empty waiting room". Four interwoven themes were found: 1) the negative emotions of loneliness, 2) the loss of meaningful interpersonal relationships, 3) the influence of loneliness on self-perception and 4) the older adultsâ endeavors to deal with loneliness. The joint contribution of family members, health care providers, and volunteers is necessary to break the vicious circle of loneliness
Bedside theatre performance and its effects on hospitalised children's well-being
This article reports on practice-based pilot research being undertaken at Birmingham Children's Hospital in England on the impact of bedside theatre performance on hospitalised children's well-being. It discusses the process of creating theatre for sick children, connecting with the hospital and working within the hospital tight routines, dealing with ethics, working with theatre artists and performing to children bedside. It also reports on evidence collected by questionnaire and interviews about the perceived benefits of bedside theatre by children and their parent/carers. This emphasis on the process is appropriate for theatre practitioners, arts therapists and clinical staff who work with hospitalised children
Self-organizing ontology of biochemically relevant small molecules
<p>Abstract</p> <p>Background</p> <p>The advent of high-throughput experimentation in biochemistry has led to the generation of vast amounts of chemical data, necessitating the development of novel analysis, characterization, and cataloguing techniques and tools. Recently, a movement to publically release such data has advanced biochemical structure-activity relationship research, while providing new challenges, the biggest being the curation, annotation, and classification of this information to facilitate useful biochemical pattern analysis. Unfortunately, the human resources currently employed by the organizations supporting these efforts (e.g. ChEBI) are expanding linearly, while new useful scientific information is being released in a seemingly exponential fashion. Compounding this, currently existing chemical classification and annotation systems are not amenable to automated classification, formal and transparent chemical class definition axiomatization, facile class redefinition, or novel class integration, thus further limiting chemical ontology growth by necessitating human involvement in curation. Clearly, there is a need for the automation of this process, especially for novel chemical entities of biological interest.</p> <p>Results</p> <p>To address this, we present a formal framework based on Semantic Web technologies for the automatic design of chemical ontology which can be used for automated classification of novel entities. We demonstrate the automatic self-assembly of a structure-based chemical ontology based on 60 MeSH and 40 ChEBI chemical classes. This ontology is then used to classify 200 compounds with an accuracy of 92.7%. We extend these structure-based classes with molecular feature information and demonstrate the utility of our framework for classification of functionally relevant chemicals. Finally, we discuss an iterative approach that we envision for future biochemical ontology development.</p> <p>Conclusions</p> <p>We conclude that the proposed methodology can ease the burden of chemical data annotators and dramatically increase their productivity. We anticipate that the use of formal logic in our proposed framework will make chemical classification criteria more transparent to humans and machines alike and will thus facilitate predictive and integrative bioactivity model development.</p
Examining the Link Between Domestic Violence Victimization and Loneliness in a Dutch Community Sample: A Comparison Between Victims and Nonvictims by Type D Personality
The current study investigated whether differences in loneliness scores between individuals with a distressed personality type (type D personality) and subjects without such a personality varied by domestic violence victimization. Participants (Nâ=â625) were recruited by random sampling from the Municipal Basic Administration of the Dutch city of âs-Hertogenbosch and were invited to fill out a set of questionnaires on health status. For this study, only ratings for domestic violence victimization, type D personality, feelings of loneliness, and demographics were used. Statistical analyses yielded main effects on loneliness for both type D personality and history of domestic violence victimization. Above and beyond these main effects, their interaction was significantly associated with loneliness as well. However, this result seemed to apply to emotional loneliness in particular. Findings were discussed in light of previous research and study limitations
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Multi-modal classifier fusion with feature cooperation for glaucoma diagnosis
Background: Glaucoma is a major public health problem that can lead to an optic nerve lesion, requiring systematic screening in the population over 45 years of age. The diagnosis and classification of this disease have had a marked and excellent development in recent years, particularly in the machine learning domain. Multimodal data have been shown to be a significant aid to the machine learning domain, especially by its contribution to improving data driven decision-making.
Method: Solving classification problems by combinations of classifiers has made it possible to increase the robustness as well as the classification reliability by using the complementarity that may exist between the classifiers. Complementarity is considered a key property of multimodality. A Convolutional Neural Network (CNN) works very well in pattern recognition and has been shown to exhibit superior performance, especially for image classification which can learn by themselves useful features from raw data. This article proposes a multimodal classification approach based on deep Convolutional Neural Network and Support Vector Machine (SVM) classifiers using multimodal data and multimodal feature for glaucoma diagnosis from retinal fundus images from RIM-ONE dataset. We make use of handcrafted feature descriptors such as the Gray Level Co-Occurrence Matrix, Central Moments and Hu Moments to co-operate with features automatically generated by the CNN in order to properly detect the optic nerve and consequently obtain a better classification rate, allowing a more reliable diagnosis of glaucoma.
Results: The experimental results confirm that the combination of classifiers using the BWWV technique is better than learning classifiers separately. The proposed method provides a computerized diagnosis system for glaucoma disease with impressive results comparing them to the main related studies that allow us to continue in this research path
Tourism as connectedness.
Late modernity in developed nations is characterized by changing social and psychological conditions, including individualization, processes of competition and loneliness. Remaining socially connected is becoming increasingly important. In this situation, travel provides meaning through physical encounters, inclusion in traveller Gemeinschaft based on shared norms, beliefs and interests, and social status in societies increasingly defined by mobilities. As relationships are forged and found in mobility, travel is no longer an option, rather a necessity for sociality, identity construction, affirmation or alteration. Social contexts and the underlying motivations for tourism have changed fundamentally in late modernity: non-tourism has become a threat to self-conceptions. By integrating social and psychological perspectives, this paper expands and deepens existing travel and mobilities discussions to advance the understanding of tourism as a mechanism of social connectedness, and points to implications for future tourism research
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