NUAA-QMUL-AIIT at Memotion 3: Multi-modal Fusion with Squeeze-and-Excitation for Internet Meme Emotion Analysis

This paper describes the participation of our NUAA-QMUL-AIIT team in the Memotion 3 shared task on meme emotion analysis. We propose a novel multi-modal fusion method, Squeeze-and-Excitation Fusion (SEFusion), and embed it into our system for emotion classification in memes. SEFusion is a simple fusion method that employs fully connected layers, reshaping, and matrix multiplication. SEFusion learns a weight for each modality and then applies it to its own modality feature. We evaluate the performance of our system on the three Memotion 3 sub-tasks. Among all participating systems in this Memotion 3 shared task, our system ranked first on task A, fifth on task B, and second on task C. Our proposed SEFusion provides the flexibility to fuse any features from different modalities. The source code for our method is published on https://github.com/xxxxxxxxy/memotion3-SEFusion

Cluster-based Deep Ensemble Learning for Emotion Classification in Internet Memes

Memes have gained popularity as a means to share visual ideas through the Internet and social media by mixing text, images and videos, often for humorous purposes. Research enabling automated analysis of memes has gained attention in recent years, including among others the task of classifying the emotion expressed in memes. In this paper, we propose a novel model, cluster-based deep ensemble learning (CDEL), for emotion classification in memes. CDEL is a hybrid model that leverages the benefits of a deep learning model in combination with a clustering algorithm, which enhances the model with additional information after clustering memes with similar facial features. We evaluate the performance of CDEL on a benchmark dataset for emotion classification, proving its effectiveness by outperforming a wide range of baseline models and achieving state-of-the-art performance. Further evaluation through ablated models demonstrates the effectiveness of the different components of CDEL

Modelling mitral valvular dynamics–current trend and future directions

Dysfunction of mitral valve causes morbidity and premature mortality and remains a leading medical problem worldwide. Computational modelling aims to understand the biomechanics of human mitral valve and could lead to the development of new treatment, prevention and diagnosis of mitral valve diseases. Compared with the aortic valve, the mitral valve has been much less studied owing to its highly complex structure and strong interaction with the blood flow and the ventricles. However, the interest in mitral valve modelling is growing, and the sophistication level is increasing with the advanced development of computational technology and imaging tools. This review summarises the state-of-the-art modelling of the mitral valve, including static and dynamics models, models with fluid-structure interaction, and models with the left ventricle interaction. Challenges and future directions are also discussed

Rfid-based business process and workflow management in healthcare:design and implementation

The healthcare system in the United States is considered one of the most complex systems and has encountered challenges related to patient safety concerns, escalating costs, and unpredictable outcomes. Many of these problems share a common cause - a lack of efficient business process management and visibility into the real-time location, status, and condition of medical resources. The goal of this research is to propose a newly integrated system to model, automate, and monitor healthcare business processes using an automatic data collection technology to record the timing and location of activities and identify their various resources. This dissertation makes several contributions to the design and implementation of RFID-based business process and workflow management in healthcare. First, I propose a road map to implement RFID in hospitals with performance matrixes for technology evaluation, key criteria for resolution level setting, and business rules for information extraction. Second, RFID-based business process management (BPM) concepts and workflow technologies are used to transform the reprocessing procedures in a Sterile Processing Department (SPD) for the purpose of reducing infections caused by unclean reusable medical equipment. In the proposed pattern for healthcare business process management, the importance of execution status control is emphasized as a key component to handle complex and dynamic healthcare processes. A five-level framework for service-oriented business process management is designed for SPDs to share information, integrate distributed systems, and manage heterogeneous resources among multiple stakeholders. This research proposes a healthcare workflow system as a deliverable solution to manage the execution phase of reprocessing procedures, which supports the design, execution, monitoring, and automation of services supplied in SPDs. RFID techniques are adopted to collect relative real-time data for SPD performance management. Finally, by identifying key architectural requirements, the subsystems of a service-oriented architecture for the SPD workflow prototyping system, SPDFLOW, are discussed in detail. This research is the first attempt to explore healthcare workflow technologies in the SPD domain to improve the quality of reusable medical equipment and ensure patient safety

ConceptScope: Organizing and Visualizing Knowledge in Documents based on Domain Ontology

Current text visualization techniques typically provide overviews of document content and structure using intrinsic properties such as term frequencies, co-occurrences, and sentence structures. Such visualizations lack conceptual overviews incorporating domain-relevant knowledge, needed when examining documents such as research articles or technical reports. To address this shortcoming, we present ConceptScope, a technique that utilizes a domain ontology to represent the conceptual relationships in a document in the form of a Bubble Treemap visualization. Multiple coordinated views of document structure and concept hierarchy with text overviews further aid document analysis. ConceptScope facilitates exploration and comparison of single and multiple documents respectively. We demonstrate ConceptScope by visualizing research articles and transcripts of technical presentations in computer science. In a comparative study with DocuBurst, a popular document visualization tool, ConceptScope was found to be more informative in exploring and comparing domain-specific documents, but less so when it came to documents that spanned multiple disciplines.Comment: 19 pages, 5 figure