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Articles 1 - 13 of 13
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Phishing In The Free Waters: A Study Of Phishing Attacks Created Using Free Website Building Services, Sayak Saha Roy, Karanjit Unique, Shirin Nilizadeh
Phishing In The Free Waters: A Study Of Phishing Attacks Created Using Free Website Building Services, Sayak Saha Roy, Karanjit Unique, Shirin Nilizadeh
Computer Science and Engineering Faculty Publications
Free Website Building services (FWBs) provide individuals with a cost-effective and convenient way to create a website without requiring advanced technical knowledge or coding skills. However, malicious actors often abuse these services to host phishing websites. In this work, we propose FreePhish, a scalable framework to continuously identify phishing websites that are created using FWBs. Using FreePhish, we were able to detect and characterize more than 31.4K phishing URLs that were created using 17 unique free website builder services and shared on Twitter and Facebook over a period of six months. We find that FWBs provide attackers with several features …
Expert Knowledge-Aware Image Difference Graph Representation Learning For Difference-Aware Medical Visual Question Answering, Xinyue Hu, Lin Gu, An Qiyuan, Mengliang Zhang, Liu Liangchen, Kobayashi Kazuma, Harada Tatsuya, M. Ronald Summers, Yingying Zhu
Expert Knowledge-Aware Image Difference Graph Representation Learning For Difference-Aware Medical Visual Question Answering, Xinyue Hu, Lin Gu, An Qiyuan, Mengliang Zhang, Liu Liangchen, Kobayashi Kazuma, Harada Tatsuya, M. Ronald Summers, Yingying Zhu
Computer Science and Engineering Faculty Publications
To contribute to automating the medical vision-language model, we propose a novel Chest-Xray Difference Visual Question Answering (VQA) task. Given a pair of main and reference images, this task attempts to answer several questions on both diseases and, more importantly, the differences between them. This is consistent with the radiologist’s diagnosis practice that compares the current image with the reference before concluding the report. We collect a new dataset, namely MIMIC-Diff-VQA, including 700,703 QA pairs from 164,324 pairs of main and reference images. Compared to existing medical VQA datasets, our questions are tailored to the Assessment Diagnosis-Intervention-Evaluation treatment procedure used …
Remote Operated Human Robot Interactive System Using Hand Gestures For Persons With Disabilities, Enamul Karim, Harish Nambiappan, Sneh Acharya, Fillia Makedon
Remote Operated Human Robot Interactive System Using Hand Gestures For Persons With Disabilities, Enamul Karim, Harish Nambiappan, Sneh Acharya, Fillia Makedon
Computer Science and Engineering Faculty Publications
This paper proposes a novel Human-Robot Interactive System where users can interact with the robotic system using hand gestures, even from a distance, through a smartphone-based IoT-Controller Framework. The system is primarily designed to help people with vocal and hearing impairments. A mobile application records user gestures shown in front of a smartphone and sends the data to a server. The server performs gesture recognition and forms a command which is sent to the robotic system. The robotic system performs the required task based on the given command. The robotic system is set to carry out an object pick and …
Smartfunction: An Immersive Vr System To Assess Attention Using Embodied Cognition, Ashish Jaiswal, Aref Hebri, Pavel Hamza Reza, Zadeh Mohammad Zaki, Fillia Makedon
Smartfunction: An Immersive Vr System To Assess Attention Using Embodied Cognition, Ashish Jaiswal, Aref Hebri, Pavel Hamza Reza, Zadeh Mohammad Zaki, Fillia Makedon
Computer Science and Engineering Faculty Publications
In traditional neuropsychological tests, executive functions (EFs) are typically evaluated using paper and pencil or computer-based sit-down tasks. However, a new assessment framework, the Automated Test of Embodied Cognition (ATEC), has been developed to measure EFs and embodied cognition through physical tasks. This paper proposes integrating the ATEC system with virtual reality (VR) to evaluate and diagnose attention-deficit disorders using embodied cognition (EC) principles. The VR system will utilize Meta Quest 2 VR headsets and controllers with motion sensors to accurately capture users’ physical movements. The collected motion data will be transmitted to a remote server for evaluation through machine …
Detecting Cognitive Fatigue In Subjects With Traumatic Brain Injury From Fmri Scans Using Self-Supervised Learning, Ashish Jaiswal, Ramesh Babu Ashwin, Zadeh Mohammad Zaki, Glenn Wylie, Fillia Makedon
Detecting Cognitive Fatigue In Subjects With Traumatic Brain Injury From Fmri Scans Using Self-Supervised Learning, Ashish Jaiswal, Ramesh Babu Ashwin, Zadeh Mohammad Zaki, Glenn Wylie, Fillia Makedon
Computer Science and Engineering Faculty Publications
Understanding cognitive states from fMRI data have yet to be investigated to its full extent due to its complex nature. In this work, the problem of understanding cognitive fatigue among TBI patients has been formulated as a multi-class classification problem. We built a Spatio-temporal encoder model using convolutions and LSTMs as the building blocks to extract spatial features and to model the 4D nature of fMRI scans. To learn a better representation of the data and the condition, we used a self-supervised learning technique called "Contrastive Learning" to pretrain our encoder with a public dataset BOLD5000 and further fine-tuned our …
An Eeg-Based Cognitive Fatigue Detection System, Karim Enamul, Pavel Hamza Reza, Ashish Jaiswal, Zadeh Mohammad Zaki, Michail Theodanidis, Glenn Wylie, Fillia Makedon
An Eeg-Based Cognitive Fatigue Detection System, Karim Enamul, Pavel Hamza Reza, Ashish Jaiswal, Zadeh Mohammad Zaki, Michail Theodanidis, Glenn Wylie, Fillia Makedon
Computer Science and Engineering Faculty Publications
Mental or Cognitive fatigue (CF) is the exhaustion of the neurological system brought on by prolonged cognitive tasks. It causes performance to decline in day-to-day life. Throughout this paper, we present an experimental setup where we artificially induce cognitive fatigue to participants. During the experimental process, we collected electroencephalogram (EEG) signals from the subjects that participated in the experiment. The goal of the study is to detect the presence or absence of cognitive fatigue. Our proposed solution was able to classify cognitive fatigue of the subjects with an accuracy of 88.17%.
A Teleoperation Framework For Robots Utilizing Control Barrier Functions In Virtual Reality, Aref Hebri, Sneh Acharya, Fillia Makedon
A Teleoperation Framework For Robots Utilizing Control Barrier Functions In Virtual Reality, Aref Hebri, Sneh Acharya, Fillia Makedon
Computer Science and Engineering Faculty Publications
This paper describes a novel shared control teleoperation framework for mobile robots that utilizes Control Barrier Functions (CBFs) as filtering mechanism to prevent a human operator from making dangerous actions. The proposed framework demonstrates the potential to create a CBF controller that enables users with no prior knowledge of robotics to safely tele-navigate mobile robots with limited situational awareness. As formal methods, we utilize a hand-crafted CBF, which acts as a repulsive field to describe unsafe regions withing the robot’s vicinity. The implementation of the application was deemed possible by creating a Virtual Reality (VR) simulation in the Unity Engine …
An Rgb-D Fusion System For Indoor Wheelchair Navigation, Christos Sevastopoulos, Sneh Acharya, Fillia Makedon
An Rgb-D Fusion System For Indoor Wheelchair Navigation, Christos Sevastopoulos, Sneh Acharya, Fillia Makedon
Computer Science and Engineering Faculty Publications
We present a method for extracting high-level semantic information through successful landmark detection using feature fusion between RGB and depth information. We focus on the classification of specific labels (open path, humans, staircases, doorways, obstacles) in the encountered scene, which can be a fundamental source of information enhancing scene understanding, and acting towards the safe navigation of the mobile unit. Experiments are conducted using a manual wheelchair equipped with a stereo RGB-D camera that captures image instances consisting of multiple labels before fine-tuning on a pre-trained Vision Transformer (ViT).
Mining Themes In Clinical Notes To Identify Phenotypes And To Predict Length Of Stay In Patients Admitted With Heart Failure, Ankita Agarwal, Tanvi Banerjee, William Romine, Krishnaprasad Thirunarayan, Lingwei Chen, Mia Cajita
Mining Themes In Clinical Notes To Identify Phenotypes And To Predict Length Of Stay In Patients Admitted With Heart Failure, Ankita Agarwal, Tanvi Banerjee, William Romine, Krishnaprasad Thirunarayan, Lingwei Chen, Mia Cajita
Computer Science and Engineering Faculty Publications
Heart failure is a syndrome which occurs when the heart is not able to pump blood and oxygen to support other organs in the body. Identifying the underlying themes in the diagnostic codes and procedure reports of patients admitted for heart failure could reveal the clinical phenotypes associated with heart failure and to group patients based on their similar characteristics which could also help in predicting patient outcomes like length of stay. These clinical phenotypes usually have a probabilistic latent structure and hence, as there has been no previous work on identifying phenotypes in clinical notes of heart failure patients …
A Preliminary Study Of The Efficacy Of Using A Wrist-Worn Multiparameter Sensor For The Prediction Of Cognitive Flow States In University-Level Students, Josephine Graft, William Romine, Brooklynn Watts, Noah Schroeder, Tawsik Jawad, Tanvi Banerjee
A Preliminary Study Of The Efficacy Of Using A Wrist-Worn Multiparameter Sensor For The Prediction Of Cognitive Flow States In University-Level Students, Josephine Graft, William Romine, Brooklynn Watts, Noah Schroeder, Tawsik Jawad, Tanvi Banerjee
Computer Science and Engineering Faculty Publications
Engagement is enhanced by the ability to access the state of flow during a task, which is described as a full immersion experience. We report two studies on the efficacy of using physiological data collected from a wearable sensor for the automated prediction of flow. Study 1 took a two-level block design where activities were nested within its participants. A total of five participants were asked to complete 12 tasks that aligned with their interests while wearing the Empatica E4 sensor. This yielded 60 total tasks across the five participants. In a second study representing daily use of the device, …
Predicting Thermoelectric Power Factor Of Bismuth Telluride During Laser Powder Bed Fusion Additive Manufacturing, Ankita Agarwal, Tanvi Banerjee, Joy Gockel, Saniya Leblanc, Joe Walker, John Middendorf
Predicting Thermoelectric Power Factor Of Bismuth Telluride During Laser Powder Bed Fusion Additive Manufacturing, Ankita Agarwal, Tanvi Banerjee, Joy Gockel, Saniya Leblanc, Joe Walker, John Middendorf
Computer Science and Engineering Faculty Publications
An additive manufacturing (AM) process, like laser powder bed fusion, allows for the fabrication of objects by spreading and melting powder in layers until a freeform part shape is created. In order to improve the properties of the material involved in the AM process, it is important to predict the material characterization property as a function of the processing conditions. In thermoelectric materials, the power factor is a measure of how efficiently the material can convert heat to electricity. While earlier works have predicted the material characterization properties of different thermoelectric materials using various techniques, implementation of machine learning models …
Overcoming Uncertainties In Molecular Visualization, Thomas Wischgoll
Overcoming Uncertainties In Molecular Visualization, Thomas Wischgoll
Computer Science and Engineering Faculty Publications
Uncertainties are difficult if not impossible to avoid. Capturing data from the analog world almost always results in some form of uncertainty. The amount of uncertainty depends on the method of measurement and its accuracy. When visualizing data that has some associated uncertainty, it is essential to properly process and convey such uncertainty and especially the amount of uncertainty keeping in mind that additional processing steps can amplify the uncertainty. There are various sources of uncertainty, such as numerical limitations or limitations of the capture device. However, there are other sources of uncertainty. Some of these uncertainties stem from model …
Code Execution Capability As A Metric For Machine Learning–Assisted Software Vulnerability Detection Models, Daniel Grahn, Lingwei Chen, Junjie Zhang
Code Execution Capability As A Metric For Machine Learning–Assisted Software Vulnerability Detection Models, Daniel Grahn, Lingwei Chen, Junjie Zhang
Computer Science and Engineering Faculty Publications
In this paper, we consider how the ability to learn Code Execution Tasks affects a model’s accuracy on software vulnerability detection (SVD) benchmark datasets. We initially find that models can achieve near state-of-the-art accuracy on SVD benchmarks regardless of their ability to learn Code Execution Tasks. However, these models fail to generalize well across SVD benchmarks. The results indicate a bias in the datasets that allows models to predict non- SVD signals. Under the theory that different collection methods will reduce biases, we investigate combining the SVD datasets. When trained on combined datasets, SVD accuracy is reduced but correlation with …