The College of Engineering and Computer Science: Recent submissions
Now showing items 61-80 of 192
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VinDr-CXR: An open dataset of chest X-rays with radiologist’s annotations
(2022-12)Most of the existing chest X-ray datasets include labels from a list of findings without specifying their locations on the radiographs. This limits the development of machine learning algorithms for the detection and ... -
Understanding Hierarchical Processes
(2022-12)Hierarchical stochastic processes, such as the hierarchical Dirichlet process, hold an important position as a modelling tool in statistical machine learning, and are even used in deep neural networks. They allow, for ... -
Semi-supervised machine learning of optical in-situ monitoring data for anomaly detection in laser powder bed fusion
(2023)Laser powder bed fusion (L-PBF) is one of the most widely used metal additive manufacturing technology for fabrication of functional and structural components. However, inconsistency in quality and reliability of L-PBF ... -
Concurrent multiscale topology optimisation towards design and additive manufacturing of bio-mimicking porous structures
(2023)This paper presents a novel multiscale explicit topology optimisation approach for concurrently optimizing the structure at the macro level and the bio-mimicking porous infillings at the micro level. Solid bar components ... -
Machine learning for the detection of social anxiety disorder using effective connectivity and graph theory measures
(2023)Introduction: The early diagnosis and classification of social anxiety disorder (SAD) are crucial clinical support tasks for medical practitioners in designing patient treatment programs to better supervise the progression ... -
Flexible HTTP-based Video Adaptive Streaming for good QoE during sudden bandwidth drops
(2023)We have observed a boom in video streaming over the Internet, especially during the Covid-19 pandemic, that could exceed the network resource availability. In addition to upgrading the network infrastructure, finding a way ... -
Corrigendum: Machine learning for the detection of social anxiety disorder using effective connectivity and graph theory measures (Frontiers in Psychiatry, (2023), 14, (1155812), 10.3389/fpsyt.2023.1155812)
(2023)In the published article, there was an error in the Funding statement. The correct Funding and Acknowledgment statements appear below. -
A smart, textile-driven, soft exosuit for spinal assistance
(2023-10-09)Work-related musculoskeletal disorders (WMSDs) are often caused by repetitive lifting, making them a significant concern in occupational health. Although wearable assist devices have become the norm for mitigating the risk ... -
Wavelet radiomics features from multiphase CT images for screening hepatocellular carcinoma: analysis and comparison
(2023)Early detection of liver malignancy based on medical image analysis plays a crucial role in patient prognosis and personalized treatment. This task, however, is challenging due to several factors, including medical data ... -
Glucose sensors based on chitosan capped ZnS doped Mn nanomaterials
(2023-02)A typical glucose sensor is a glucose oxidase (GOx) enzyme-based sensor due to its high sensitivity and selectivity. However, activating and stabilizing the enzyme presents challenges. To enhance the stability of GOx-based ... -
Optical glucose sensors based on chitosan-capped ZnS-doped Mn nanomaterials
(2923-03-06)The primary goal of glucose sensing at the point of care is to identify glucose concentrations within the diabetes range. However, lower glucose levels also pose a severe health risk. In this paper, we propose quick, simple, ... -
Asymmetric hashing for fast ranking via neural network measures
(2022-11)Fast item ranking is an important task in recommender systems. In previous works, graph-based Approximate Nearest Neighbor (ANN) approaches have demonstrated good performance on item ranking tasks with generic searching/matching ... -
LightX3ECG: A lightweight and explainable deep learning system for 3-lead electrocardiogram classification
(2022-07-25)Cardiovascular diseases (CVDs) are a group of heart and blood vessel disorders that is one of the most serious dangers to human health, and the number of such patients is still growing. Early and accurate detection plays ... -
High accurate and explainable multi-pill detection framework with graph neural network-assisted multimodal data fusion
(2023-09-28)Due to the significant resemblance in visual appearance, pill misuse is prevalent and has become a critical issue, responsible for one-third of all deaths worldwide. Pill identification, thus, is a crucial concern that ... -
PediCXR: An open, large-scale chest radiograph dataset for interpretation of common thoracic diseases in children
(2023)Computer-aided diagnosis systems in adult chest radiography (CXR) have recently achieved great success thanks to the availability of large-scale, annotated datasets and the advent of high-performance supervised learning ... -
A systematic review of the use of topic models for short text social media analysis
(2023-05-01)Recently, research on short text topic models has addressed the challenges of social media datasets. These models are typically evaluated using automated measures. However, recent work suggests that these evaluation measures ... -
VinDr-Mammo: A large-scale benchmark dataset for computer-aided diagnosis in full-field digital mammography
(2023)Mammography, or breast X-ray imaging, is the most widely used imaging modality to detect cancer and other breast diseases. Recent studies have shown that deep learning-based computer-assisted detection and diagnosis (CADe/x) ... -
Absorbance biosensors‑based hybrid MoS2 nanosheets for Escherichia coli detection
(2023)Detecting Escherichia coli is essential in biomedical, environmental, and food safety applications. In this paper, we have developed a simple, rapid, sensitive, and selective E. coli DNA sensor based on the novel hybrid-type ... -
Clearing payments in dynamic financial networks
(2023-12)This paper proposes a novel dynamical model for determining clearing payments in financial networks. We extend the classical Eisenberg–Noe model of financial contagion to multiple time periods, allowing financial operations ... -
Joint RIS-Aided Precoding and Multislot Scheduling for Maximum User Admission in Smart Cities
(2024-01-01)Reconfigurable intelligent surfaces (RISs) have emerged as a game-changing technology to improve wireless network performance by intelligently manipulating and customizing the physical propagation environment. Such capability ...
