1,720,964 research outputs found
AI-driven design exploration: use of Reinforcement learning-based recommender system for parametric design space exploration
No full textThesis (Master's)--University of Washington, 2023In the current practice of architectural design, performance analysis is an essential step that involves simulating various design options to identify the most optimal solution. However, the process can be time-consuming, especially when the design space is vast. To address this issue, designers often use optimization algorithms to find the best solution, but simulating each design option is still a significant bottleneck. Surrogate models offer a potential solution by creating a simplified model that approximates the behaviors of the actual system. This model can then be used to simulate multiple design options efficiently. While surrogate models can help speed up the performance analysis process, they still require a significant amount of data to train effectively. Additionally, optimization done with surrogate models cannot account for aesthetic preferences, which are essential for architectural design.The paper proposes a novel design framework that leverages AI and machine learning models to address the aforementioned challenges. To demonstrate the efficacy of the framework, a parametric model is developed to generate a large number of design alternatives for a multi-story office building in Seattle. Multiple design spaces of different sizes are investigated to validate the framework. The proposed framework consists of two sections. The first section involves three consecutive layers to enable faster and more accurate prediction of performance for all design alternatives. The annual energy consumption is simulated using EnergyPlus. The first step is to convert the design parameters into weighted parameters to aid the machine learning models in understanding their distinct behaviours. The number of weighted parameters is then reduced to three using different dimensionality reduction algorithms to visualize clusters in the last step. The final step involves clustering the entire design space effectively so that the performance outcome of the centroid of the cluster can be a proper representative of all other data points in that cluster. Multiple combinations of weighting parameters, dimensionality reduction methods, and clustering models are experimented with to identify the set of algorithms that can predict the performance outcome of the entire design space with the least amount of error using a smaller number of clusters.
The second section of the proposed framework involves an online dashboard that enables the exploration of the design space. The dashboard includes a reinforcement learning-based recommender system that seeks to understand user preferences through interaction and recommends similar design alternatives in each iteration. The reward function of the recommender system is customized to prioritize high-performing alternatives and pull the designer's preference in that direction. The proposed framework enables designers to explore a massive design space strategically and effectively within a short amount of time
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Deep learning-based severity analysis of pneumoconiosis in Chest X-Rays
Full text linkThe thesis objective is to develop a deep learning-based system for severity analysis of pneumoconiosis, which would contribute to the monitoring and management of disease progression. For severity analysis of pneumoconiosis, the first step is accurate lung segmentation in chest X-ray images, which aids in highlighting important regions within the lungs. The second step is the multi-class classification of pneumoconiosis. Both segmentation and classification of pneumoconiosis using chest X-ray images are challenging tasks. Furthermore, an imbalanced and small dataset exacerbates the challenge. This thesis presents methods for lung segmentation, data augmentation, and multi-class classification of pneumoconiosis.
To perform lung segmentation on chest X-ray images, this thesis proposes three novel deep learning-based methods. The first two methods involve modifications to the standard U-Net architecture, including the substitution of skip connections with a bidirectional convolutional-LSTM module and a dilated inception block, and the integration of a multikernel pooling block at the lowest level of the U-Net structure. In the third, basic building blocks in the UNet++ architecture are replaced with a multi-scale residual block, and a soft attention-gate module is inserted between the convolution blocks.
This thesis presents three distinct data augmentation techniques. Two conventional data augmentation methods are proposed that involve a combination of various data augmentation techniques to simulate chest X-ray images with diverse disease features. The third is a Multi-Scale Attention-based Generative Adversarial Network by modifying Cycle- GAN. The modification involves replacing the generator with the proposed multi-scale attention-based generator, introducing a local-global discriminator structure, and incorporating Structural Similarity loss as the cycle consistency loss.
For severity analysis of pneumoconiosis, two methods are proposed. The first is a classification network which utilises a novel lesion attention module to extract features from affected lung regions. The second is a two-stage network that comprises two blocks that extract rich semantic information in the encoder and effectively combine features from lowlevel detailed and high-level global semantic information in the decoder. A pilot study was also conducted to evaluate the effectiveness of the multi-class classification system in a real-world environment
Kingdom of Saudi Arabia: A potential destination for medical tourism
No full textAbstractTo perform a comparative study of Medical tourism in the Arab world with special reference to Saudi Arabia and find ways to upgrade medical tourism in Saudi Arabia. A comprehensive literature review and analysis of statistical data from Saudi Ministry of Health is performed.With more than 37 million health-related trips and the generation of more than £ 33 billion each year, medical tourism has become an important element in the global economy. Travelling abroad to seek medical care is increasing steadily in both developing and developed countries: people in developing countries seek new technology and skills in developed countries, while people in rich developed countries seek medical care elsewhere because of high costs and long waiting lists in their home countries. India, Malaysia, Singapore and Thailand dominate the Asian market, and the United Arab Emirates, with the construction of the Dubai Health Care City, attracts clients from western, Gulf Cooperation Council, Middle Eastern and North African countries. Kingdom of Saudi Arabia is not one of the most popular countries, even though it has all the basic attributes for a successful medical tourism industry, including modern, well-equipped hospitals, a well-established private health care sector, foreign-trained doctors and specialists and a stable, peaceful environment. It is also home to the main holy places of Islam and an important religious center. Kingdom of Saudi Arabia could take the lead in this market by combining medical tourism with religious tourism, not only for the 1.6 billion (23% of the world's population) Muslims but also for the rest of the world. Recent accreditation of many Saudi hospitals by the Joint Commission International in the United States shows their commitment to promoting medical tourism. If properly managed, medical tourism could open the door for an income generation revolution in Kingdom of Saudi Arabia
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
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