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Annotating Reflections for Health Behavior Change Therapy
Article presents work on annotating reflections, an essential counselor behavioral code in motivational interviewing for psychotherapy on conversations that are a combination of casual and therapeutic dialogue.
I Cannot See You—The Perspectives of Deaf Students to Online Learning during COVID-19 Pandemic: Saudi Arabia Case Study
This article investigates the e-learning experiences of deaf students, focusing on the college of the Technical and Vocational Training Corporation (TVTC) in the Kingdom of Saudi Arabia (KSA). Particularly, it studies the challenges and concerns faced by deaf students during the sudden shift to online learning. Results report problems with internet access, inadequate support, and inaccessibility of content from learning systems, among other issues. The authors argue that institutions should consider a procedure to create more accessible technology that is adaptable during the pandemic to serve individuals with diverse needs.
Enhancement of COVID-19 Diagnosis using Machine Learning and Texture Analyses of Lung Imaging
Article proposing CoviSegNet, an enhanced U-Net model to segment ground-glass opacities and consolidations in CT scans of Covid-19 positive patients. The performance of CoviSegNet was evaluated on three public CT datasets. The experimental results show that the proposed CoviSegNet is highly promising.
Everything You Wanted to Know About Continuous Glucose Monitoring
Article providing a brief review about various approaches of continuous glucose measurement with noninvasive manner. This article covers the state-of-the-art glucose measurement methods and its control mechanism. The study of various consumer products have also been discussed along with the open challenges. This is the Accepted Manuscript version.
GlobeChain: An Interoperable Blockchain for Global Sharing of Healthcare Data - A COVID-19 Perspective
Article introducing a Blockchain-based medical data-sharing framework (called GlobeChain) to overcome the technical challenges to handle outbreak records. The challenges that might arise due to the proposed Blockchain-based framework are also presented as a future direction that grabs the proposal's effectiveness. This is the accepted manuscript version of the article.
HAR-Depth: A Novel Framework for Human Action Recognition Using Sequential Learning and Depth Estimated History Images
This is the Accepted Manuscript version of an article that proposes HAR-Depth with sequential and shape learning along with the novel concept of depth history image (DHI) to address the challenges of Human action recognition (HAR). Results suggest that the proposed work of this paper performs better in terms of overall accuracy, kappa parameter and precision compared to the other state-of-the-art algorithms present in the earlier reported literature.
An Interactive Model for Vector Borne Diseases: A Simulation for Zika in French Polynesia
Post presented at Contagion 2016, a satellite meeting at the 2016 Conference on Complex Systems. This poster presents a stochastic agent-based model that simulates the transmission of ZIKA via mosquitoes in 11 islands in the French Polynesia.
MyWear: A Novel Smart Garment for Automatic Continuous Vital Monitoring
Accepted Manuscript version of an article presenting the design and development of a smart garment called MyWear that continuously monitors and collects physiological data. It can analyze muscle activity, stress levels, and heart rate variations and send all the data to the cloud. With a in-built alert system, it can notify the associated medical officials if necessary. The authors also propose a deep neural network model that classifies heartbeat data into abnormalities with 96.9% accuracy and 97.3% precision.
sCrop: A Novel Device for Sustainable Automatic Disease Prediction, Crop Selection, and Irrigation in Internet-of-Agro-Things for Smart Agriculture
Accepted Manuscript version of an article introducing the innovative idea of the Internet-of-Agro-Things (IoAT) with an explanation of the automatic detection of plant disease for the development of Agriculture Cyber-Physical System (ACPS). An accuracy of 99.24% is achieved by the proposed plant disease prediction framework.
Toward Next-Generation Robust Cryptosystems
Accepted Manuscript version of an article that presents thoughts on paradigm-shift next generation cryptosystems to overcome the vulnerabilities of the omnipresent conventional cryptosystems.
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