Transfer Learning for Human & AI

Medical imaging has been employed to support medical diagnosis and treatment . It may also provide crucial information to surgeons to facilitate optimalsurgical preplanning and perioperative management . This paper addresses to propose the most efficient DL architectures for Liversegmentation by adapting and comparing state-of-the-art DL frameworks, studiedin different disciplines .…

Alignment of contrast and non-contrast-enhanced imaging is essential for thequantification of changes in several biomedical applications . Existing deep learning-based methods for alignment require a commontemplate or are limited in rotation range . We present a novel network, D-net, to estimate arbitrary rotation and translation between 3D CTscans that additionally does not require a prior standard template .…

This study addresses the current issues in online assessments, which are particularly relevant during the Covid-19 pandemic . The intelligence agent monitors the behaviour of the students and hasthe ability to prevent and detect any malicious practices . It can be used toassign randomised multiple-choice questions in a course examination and beintegrated with online learning programs .…

Early screening of patients is a critical issue in order to assess immediate and fast responses against the spread of COVID-19 . The use of nasopharyngealswabs has been considered the most viable approach, but the result is notimmediate or, in the case of fast exams, sufficiently accurate .…

We propose a deep learning-based regularized segmentation method for multi-structure bone delineation in MR images . The novel shape priors based adversarial regularization (SPAR)exploits latent shape codes arising from ground truth and predicted masks to guide the segmentation network towards more consistent and plausible predictions .…

We introduce a new reconstruction technique for two-dimensional BraggScattering Tomography . Our method uses a combination of ideas frommultibang control and microlocal analysis to construct an objective function which can regularize the BST artifacts . We then test our algorithm in avariety of Monte Carlo (MC) simulated examples of practical interest in airportbaggage screening and threat detection .…

The coronavirus disease 2019 (COVID-19) pandemic has caused an unprecedented health crisis for the global. Digital contact tracing, as a transmissionintervention measure, has shown its effectiveness on pandemic control. Despite intensive research on digital contact tracing,. existing solutions can hardlymeet users’ requirements on privacy and convenience .…

The authenticity ofinformation on a social networking service (SNS) is unknown, and falseinformation can be easily spread . Many studies have been conducted on methods to control the spread of misinformation on socialnetworking sites . This study models the impact of the reduction of misinformation and the diffusion of corrective information on society .…

This study analyzed a large set ofspatio-temporal Bangladeshi newspaper data related to the COVID-19 pandemic . Newspapers are trustworthy media where people get the most reliable and credible information compared with other sources . Socialmedia often spread rumors and misleading news to get more traffic and attention .…

Mobile contact tracing apps are — in principle — a perfect aid to condemnthe human-to-human spread of an infectious disease such as COVID-19 due to thewide use of smartphones worldwide . Yet, the unknown accuracy of contactestimation by wireless technologies hinders the broad use of wireless technologies .…

The COVID-19 pandemic has influenced virtually all aspects of our lives . We postulate thatmulti-agent systems can provide a common platform to study (and balance) theiressential properties . We also show how to obtain a comprehensive list of theproperties by “distilling” them from media snippets .…

The COVID-19 outbreak has caused a major disruption worldwide . But what happened to companies developing digital services? Were they interrupted as much or at all? And how has the enforcedWorking-From-Home (WFH) mode impacted their ability to deliver software? We hear that some managers are concerned that their engineers are not working effectively from home, or even lack the motivation to work in general, that teams lose touch and that managers do not notice when things go wrong .…

In our paper we analyze the attack surface of German hospitals and healthcareproviders in 2020 during the COVID-19 Pandemic . Primary analysis shows that 32 percent of the analyzed services were determined as vulnerable to variousdegrees and 36 percent of all hospitals showed numerous vulnerabilities .…

Controversial understandings of the coronavirus pandemic have turned datavisualizations into a battleground . People who mistrust the scientific establishment often deploy the same rhetorics of data-drivendecision-making used by experts, but to advocate for radical policy changes . We document an epistemological gap that leads pro- and anti-mask groups to drawdrastically different inferences from similar data .…

Deep learning methods for chest X-ray interpretation typically rely onpretrained models developed for ImageNet . This paradigm assumes that betterImageNet-pretrained weights provide a performance boost over randominitialization . We find that,for models without pretraining, the choice of model family influencesperformance more than size within a family for medical imaging tasks .…

The currently deployed contact-tracing mobile apps have failed as an efficient solution in the context of the COVID-19 pandemic . None of them has managed to attract the number of active users required to achieve an efficientoperation . This urges the research community to re-open the debate and explore new avenues that lead to efficient contact-Tracing solutions .…

Since March 2020, companies nationwide have started work from home (WFH) dueto the rapid increase of COVID-19 confirmed cases in an attempt to help prevent the coronavirus from spreading and rescue the economy from the pandemic . We perform an ordinary least square regression to investigate therelationship between the sentiment about WFH and user characteristics including gender, age, ethnicity, median household income, and population density .…

Computed tomography (CT) image provides useful information for radiologiststo diagnose Covid-19 . However, visual analysis of CT scans is time-consuming . In this paper, we propose a belief function-based convolutionalneural network with semi-supervised training . Our results are more reliable andexplainable than those of traditional deep learning-based classification models.…

Functional Near-Infrared Spectroscopy (fNIRS) is a non-invasive form ofBrain-Computer Interface (BCI) It is used for the imaging of brainhemodynamics and has gained popularity due to the certain pros it poses overother similar technologies . Since hemodynamic responses arecontaminated by physiological noises, several methods have been implemented inthe past literature to classify the responses in focus from the unwanted ones .…

Taking advantage of social media platforms, such as Twitter, this paper provides an effective framework for emotion detection among those who are quarantined . Early detection of emotional feelings and their trends helpimplement timely intervention strategies . Our findings revealed Stay-At-Home restrictions result in people expressing on twitter both negative and positive emotional semantics .…

It has been one year since the outbreak of the COVID-19 pandemic . The proportion of Reddit comments predominated by conspiracy theories outweighed that of any other topics . Each subreddit has its own user bases, so information posted in one subreddit may not reach those from others .…

The mass shift to working at home during the COVID-19 pandemic radicallychanged the way many software development teams collaborate and communicate . To investigate how team culture and team productivity may also have been affected, we conducted two surveys at a large software company .…

COVID-19 has disrupted normal life and has enforced a substantial change inthe policies, priorities and activities of individuals, organisations andgovernments . These changes are proving to be a catalyst for technology andinnovation . In this paper, we discuss the pandemic’s impact on the adoption of the Internet of Things (IoT) in various broad sectors namely \sectors .…

We propose a design pattern for tackling text ranking problems, dubbed”Expando-Mono-Duo”, that has been empirically validated for a number of ad hocretrieval tasks in different domains . At the core, our design relies onpretrained sequence-to-sequence models within a standard multi-stage rankingarchitecture .…

Differences in political ideology are increasingly appearing as an impediment to successful bipartisan communication from local leadership . We find that conservatives adhere to health directives when they express more fear of the virus . We analyze both official and citizen communications and find that press releases from local and federalgovernment, along with the number of confirmed COVID-19 cases, lead to anincrease in expressions of fear on Twitter .…

The paper is devoted to the participation of the TUDublin team in the COVID19 Fake News Detection Challenge . The number of fake news is increasing rapidly and it is necessary to create AItools that allow us to identify and prevent the spread of false information about COVID-19 urgently .…

We present an approach for forecasting mental health conditions andemotions of a given population during the COVID-19 pandemic . This approach permits anticipating highprevalence periods in short- to medium-term time horizons . Mentalhealth conditions and emotions are captured via markers, which link socialmedia contents with lexicons .…

Social media platforms like Facebook, Twitter, and Instagram have led to an increase in the creation and spread of fake news . The fake news has not only influencedpeople in the wrong direction but also claimed human lives . During thesecritical times of the Covid19 pandemic, it is easy to mislead people and makethem believe in fatal information .…

Phase retrieval (PR) is an important component in modern computational imaging systems . Recent advances in deep learning have opened up a new possibility for robust and fast PR . Unfolded algorithms, powered by data learning, have shown remarkable performance and convergence speed improvement over the original algorithms .…

The COVID-19 pandemic led Brazil to recommend and, at times, imposes social distancing, with the partial closure of economic activities, schools,and restrictions on events and public services . Preliminary evidence shows thatintense coexistence increases domestic violence, while social distancingmeasures may have prevented access to public services and networks,information, and help .…

This work proposes a scalable, blockchain-based platform for the securesharing of COVID-19 or other disease vaccination certificates . We simulate a large-scale deployment by considering the countries of the European Union . The proposed platform is evaluated through extensivesimulations in terms of computing resource usage, network response time and bandwidth .…

We aim to achieve a robust model for the COVID-19 fake-news detection task proposed at CONSTRAINT 2021 (FakeNews-19) The world is facing unprecedented infodemic with the proliferation of both fake and real information . We suggest the importance of model generalization ability in thistask to step forward to tackle the problem in online socialmedia platforms .…

The solution was within 1.5% of the best performing solution . The proposed solution employs a heterogeneousrepresentation ensemble, adapted for the classification task via an additionalneural classification head comprised of multiple hidden layers . The solution is freely available and the solution is free to download and use it as a guide to identifying Fake News in the future .…

In this system paper we present our contribution to the Constraint 2021COVID-19 Fake News Detection Shared Task . We find our best performing system to be based on alinear SVM, which obtains a weighted average F1 score of 95.19% on test data, lands a place in the middle of the leaderboard (place 80 of 167) In terms of pre-processing, we experiment with various steps like stop word removal, stemming/lemmatization,link removal and more.…

The COVID-19 pandemic has caused ~ 2 million fatalities . Within Mexico City,there is a clear south, north divide with higher mortality in the northernmunicipalities . Deceased patients in these northern municipalities have the highest pre-existing health conditions . The use of hexagonal cartograms is a better approach for spatial mapping of the data in Mexico as it addresses bias in area size and population .…

Remote photoplethysmography (rPPG) is a known family of techniques formonitoring blood volume changes from a camera . We foundthat occlusions from face masks affect face video-based rPPG as the meanabsolute error of blood volume estimation is nearly doubled when the face is partially occluded by protective masks .…

The global pandemic caused by the COVID virus led universities to a change inthe way they teach classes, moving to a distance mode . 13 videos were analyzed, which had 16,340 views, coming from at least 1,486 viewers . It was obtained that the visualizations depend on the proximity to the test dates and that although the visualizationtime has a curve that accompanies the duration of the videos, it is limited and the average number of visualizations is 10 minutes and 4 seconds .…

We propose a BlackBox that is explicitly developed for medical imaging applications . Classical approaches assessing feature importance do not explain how a particular anatomical region is relevant to the outcome . We design the loss function to ensure thatessential and potentially relevant details, such as support devices, are preserved in the counterfactually generated images .…

Time-series forecasting has been an important research domain for so many years . Its applications include ECG predictions, sales forecasting, weatherconditions, even COVID-19 spread predictions . Forecasting of telemetry data is acritical feature of network and data center management products .…

The World Health Organization recommends wearing a face mask and practicing physical distancing to mitigate the virus’s spread . This paper developed a computer vision system to automatically detect the violation offace mask wearing and physical distance among construction workers .…

COVID-19 testing remains paramount as an intervention tool to curb the spread of the epidemic . Invasion of privacy remains a crucial concern . Test efficacy has been overstated. Test results are poorly understood resulting in inappropriate follow-uprecommendations . Digital toolswill play a critical role in resolving these challenges.…

Federal investments in intelligent infrastructure will increase safety and resilience, improve efficiencies and civic services, andbroaden employment opportunities and job growth nationwide . The technologiesthat comprise intelligent infrastructure can also provide keys to solving some of the most vexing challenges we face today, including confronting futurepandemics and natural disasters, achieving sustainability and energy efficiency goals .…

Governments require regional or national lockdowns in order to prevent thespread of COVID-19, which causes large economic stagnation in wide areas . This study examines how governments mitigate the economic losses whenthey are obliged to implement lockdowns, using supply-chain data for 1.6million firms in Japan .…

Fluid-filled soft visuotactile sensors alleviate key challenges for robust manipulation . They enable reliable grasps along with the ability to obtain high-resolution sensory feedback on contact geometry and forces . We investigate the application of state-of-the-art monocular depthestimation to infer dense internal (tactile) depth maps directly from theinternal single small IR imaging sensor .…

In the context of the COVID-19 pandemic, the rapid roll-out of a vaccine and implementation of a worldwide immunization campaign is critical . We present such system implementation in which .blockchain technology is used for assuring data integrity and immutability incase of beneficiary registration for vaccination, eliminating identity theft and impersonations .…

We use 54,383 Twitter messages (out of 784K geolocated messages) from Sept. 10 – 12, 2017 to develop 4 independent models to filter data for relevance . The data can be combined to quickly filter andvisualize tweets based on user-defined thresholds for each submodel .…

The COVID-19 crisis highlighted the importance of non-medical interventions in the control of epidemics . Here, we show how to minimize testing needs while maintaining thenumber of infected individuals below a desired threshold . We find that theoptimal policy is adaptive, with testing rates that depend on epidemic state .…

Recent works have demonstrated that L1/L2 is better than the classictotal variation (the L1 norm on the gradient) to enforce the sparsity of the image gradient . In this paper, we study the L1-L2 minimization for imaging applications . Experimentally, we demonstrate visible improvements of L1 over L1 and other nonconvex regularizations for image recovery from low-frequency measurements and two medical applications of MRI and CTreconstruction .…

The pandemic caused by the SARS-CoV-2 virus has exposed many flaws in the decision-making strategies used to distribute resources to combat global health crises . We propose a general model coupled with a tunable lookahead policy for making vaccine allocation decisions without perfect knowledge about the state of the world .…

Convolutional neural networks (CNNs) have led to significant improvements intasks involving semantic segmentation of images . CNNs are vulnerable in thearea of biomedical image segmentation because of distributional gap between twosource and target domains with different data modalities which leads to domainshift .…