Taming The Data In The Internet Of Vehicles,
2022
California State University, Fresno
Taming The Data In The Internet Of Vehicles, Shahab Tayeb
Mineta Transportation Institute
As an emerging field, the Internet of Vehicles (IoV) has a myriad of security vulnerabilities that must be addressed to protect system integrity. To stay ahead of novel attacks, cybersecurity professionals are developing new software and systems using machine learning techniques. Neural network architectures improve such systems, including Intrusion Detection System (IDSs), by implementing anomaly detection, which differentiates benign data packets from malicious ones. For an IDS to best predict anomalies, the model is trained on data that is typically pre-processed through normalization and feature selection/reduction. These pre-processing techniques play an important role in training a neural network to optimize …
User Experience Design Practices In Industry (Case Study From Indonesian Information Technology Companies),
2021
UIN Sunan Kalijaga Yogyakarta, Indonesia
User Experience Design Practices In Industry (Case Study From Indonesian Information Technology Companies), Isnan Nugraha, Agung Fatwanto
Elinvo (Electronics, Informatics, and Vocational Education)
User Experience (UX) is a term that has received a lot of attention in the last decade. The number of industries whose consider the importance of implementing the UX design process within their development cycle has increased. Therefore, we think it is important to investigate how UX design processes are implemented in the industries. In this research, we take a qualitative approach with descriptive methods by investigating six information technology companies in Indonesia. As a result, we found that most of these information technology companies implement the UX design process as part of their operation and consider that the UX …
Evaluating Technology-Mediated Collaborative Workflows For Telehealth,
2021
Rochester Institute of Technology
Evaluating Technology-Mediated Collaborative Workflows For Telehealth, Christopher Bondy Ph.D., Pengcheng Shi, Pamela Grover Md, Vicki Hanson, Linlin Chen, Rui Li
Articles
Goals: This paper discusses the need for a predictable method to evaluate gains and gaps of collaborative technology-mediated workflows and introduces an evaluation framework to address this need. Methods: The Collaborative Space Analysis Framework (CS-AF), introduced in this research, is a cross-disciplinary evaluation method designed to evaluate technology-mediated collaborative workflows. The 5-step CS-AF approach includes: (1) current-state workflow definition, (2) current-state (baseline) workflow assessment, (3) technology-mediated workflow development and deployment, (4) technology-mediated workflow assessment, (5) analysis, and conclusions. For this research, a comprehensive, empirical study of hypertension exam workflow for telehealth was conducted using the CS-AF approach. Results: The CS-AF …
What Interactive Web Features Are Most Used,
2021
Harrisburg University of Science and Technology
What Interactive Web Features Are Most Used, Travis Tyler
Experiential Learning Projects
The use of interactive features in websites has become common place on the internet. People use these tools to help navigate and understand the content related to that website. However, due the large variety of websites it can be tricky to understand what features are best to utilize based on the topic of your site. This paper seeks to address this issue by researching how users interact and utilized different features on different websites. Research is gathered via scholarly articles and direct data gathered from volunteers. This data shows users tend to favor more interactive tools to help with navigation, …
Evaluation Of Gpu Acceleration For Wrf–Sfire,
2021
San Jose State University
Evaluation Of Gpu Acceleration For Wrf–Sfire, Joshua Benz
Master's Projects
WRF–SFIRE is an open source, atmospheric–wildfire model that couples the WRF model with the level set fire spread model to simulate wildfires in real time. This model has many applications and more scientific questions can be asked and answered if the model can be run faster. Nvidia has put a lot of effort into easing the barrier of entry for accelerating applications with their tools to be run on GPUs. Various physical simulations have been successfully ported to utilize GPUs and have benefited from the speed increase. In this research, we take a look at WRF-SFIRE and try to use …
Winter 2021,
2021
DePaul University
Winter 2021
In The Loop
2021 Emmy Nominees; Animator Tapped by Cartoon Network; IndieCade Horizons 2021; Hack4Space; Security Daemons Prevail; Role Models: DePaul Originals Game Studio students build industry-level skills that benefit themselves and others; Frames and Fortune: Eugene Bush programmed his indie video studio with patience and planning; Reality Check: Heather Snyder Quinn augments reality to question systems of unchecked power
Comparative Analysis Of Rgb-Based Eye-Tracking For Large-Scale Human-Machine Applications,
2021
Northern Kentucky University
Comparative Analysis Of Rgb-Based Eye-Tracking For Large-Scale Human-Machine Applications, Brett Thaman, Trung Cao
Posters-at-the-Capitol
Gaze tracking has become an established technology that enables using an individual’s gaze as an input signal to support a variety of applications in the context of Human-Computer Interaction. Gaze tracking primarily relies on sensing devices such as infrared (IR) cameras. Nevertheless, in the recent years, several attempts have been realized at detecting gaze by acquiring and processing images acquired from standard RGB cameras. Nowadays, there are only a few publicly available open-source libraries and they have not been tested extensively. In this paper, we present the result of a comparative analysis that studied a commercial eye-tracking device using IR …
Markdown To Question & Test Interoperability,
2021
San Jose State University
Markdown To Question & Test Interoperability, Su Kim
Master's Projects
As the classroom setting shifted to a virtual one as a result of Covid-19, numerous software are readily available to accommodate for the change, including Canvas, the online course management system. Canvas has a core feature that allows teachers to generate and administer quizzes for students through their interface, but it does not fully utilize the potential with online exams. The first step to exploring this potential is this project, known as Markdown to Question & Test Interoperability (M2QTI). Based on the QTI specifications, this tool lets users to plan and write quizzes in Markdown format. Combined with Canvas’s ability …
Automated Discovery And Interpretation Of Ada-Compliant Door Placards,
2021
Kutztown University of Pennsylvania
Automated Discovery And Interpretation Of Ada-Compliant Door Placards, John J. Feilmeier
Computer Science and Information Technology Faculty
A familiar difficulty to any new student on campus is making one’s way from classroom A to classroom B. Facilities with different wings, multiple floors, and irregular floorplans can magnify this challenge, while students with vision impairments are impacted even more by the challenge of identifying the destination. This thesis explored different methods of discovering Americans with Disabilities Act (ADA)- compliant room identifying placards (“plaques”) and identifying the text on the sign. The plaque detection was accomplished with both standard image manipulation techniques and a Histogram of Oriented Gradients (HOG) (Dalal & Triggs, 2005) object detector. The text reading utilized …
Contrastive Learning For Unsupervised Auditory Texture Models,
2021
University of Arkansas, Fayetteville
Contrastive Learning For Unsupervised Auditory Texture Models, Christina Trexler
Computer Science and Computer Engineering Undergraduate Honors Theses
Sounds with a high level of stationarity, also known as sound textures, have perceptually relevant features which can be captured by stimulus-computable models. This makes texture-like sounds, such as those made by rain, wind, and fire, an appealing test case for understanding the underlying mechanisms of auditory recognition. Previous auditory texture models typically measured statistics from auditory filter bank representations, and the statistics they used were somewhat ad-hoc, hand-engineered through a process of trial and error. Here, we investigate whether a better auditory texture representation can be obtained via contrastive learning, taking advantage of the stationarity of auditory textures to …
Vireo @ Trecvid 2021 Ad-Hoc Video Search,
2021
Singapore Management University
Vireo @ Trecvid 2021 Ad-Hoc Video Search, Jiaxin Wu, Phuong Anh Nguyen, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
In this paper, we summarize our submitted runs and results for Ad-hoc Video Search (AVS) task at TRECVid 2020
Self-Supervised Learning Disentangled Group Representation As Feature,
2021
Singapore Management University
Self-Supervised Learning Disentangled Group Representation As Feature, Tan Wang, Zhongqi Yue, Jianqiang Huang, Qianru Sun, Hanwang Zhang
Research Collection School Of Computing and Information Systems
A good visual representation is an inference map from observations (images) to features (vectors) that faithfully reflects the hidden modularized generative factors (semantics). In this paper, we formulate the notion of “good” representation from a group-theoretic view using Higgins’ definition of disentangled representation [38], and show that existing Self-Supervised Learning (SSL) only disentangles simple augmentation features such as rotation and colorization, thus unable to modularize the remaining semantics. To break the limitation, we propose an iterative SSL algorithm: Iterative Partition-based Invariant Risk Minimization (IP-IRM), which successfully grounds the abstract semantics and the group acting on them into concrete contrastive learning. …
A Theory-Driven Self-Labeling Refinement Method For Contrastive Representation Learning,
2021
Singapore Management University
A Theory-Driven Self-Labeling Refinement Method For Contrastive Representation Learning, Pan Zhou, Caiming Xiong, Xiao-Tong Yuan
Research Collection School Of Computing and Information Systems
For an image query, unsupervised contrastive learning labels crops of the same image as positives, and other image crops as negatives. Although intuitive, such a native label assignment strategy cannot reveal the underlying semantic similarity between a query and its positives and negatives, and impairs performance, since some negatives are semantically similar to the query or even share the same semantic class as the query. In this work, we first prove that for contrastive learning, inaccurate label assignment heavily impairs its generalization for semantic instance discrimination, while accurate labels benefit its generalization. Inspired by this theory, we propose a novel …
Fine-Grained Generalization Analysis Of Inductive Matrix Completion,
2021
Singapore Management University
Fine-Grained Generalization Analysis Of Inductive Matrix Completion, Antoine Ledent, Rodrigo Alves, Yunwen Lei, Marius Kloft
Research Collection School Of Computing and Information Systems
In this paper, we bridge the gap between the state-of-the-art theoretical results for matrix completion with the nuclear norm and their equivalent in \textit{inductive matrix completion}: (1) In the distribution-free setting, we prove bounds improving the previously best scaling of \widetilde{O}(rd2) to \widetilde{O}(d3/2√r), where d is the dimension of the side information and rr is the rank. (2) We introduce the (smoothed) \textit{adjusted trace-norm minimization} strategy, an inductive analogue of the weighted trace norm, for which we show guarantees of the order \widetilde{O}(dr) under arbitrary sampling. In the inductive case, a similar rate was previously achieved only under uniform sampling …
Component Damage Source Identification For Critical Infrastructure Systems,
2021
University of Arkansas, Fayetteville
Component Damage Source Identification For Critical Infrastructure Systems, Nathan Davis
Graduate Theses and Dissertations
Cyber-Physical Systems (CPS) are becoming increasingly prevalent for both Critical Infrastructure and the Industry 4.0 initiative. Bad values within components of the software portion of CPS, or the computer systems, have the potential to cause major damage if left unchecked, and so detection and locating of where these occur is vital. We further define features of these computer systems and create a use-based system topology. We then introduce a function to monitor system integrity and the presence of bad values as well as an algorithm to locate them. We then show an improved version, taking advantage of several system properties …
Acceleration Skinning: Kinematics-Driven Cartoon Effects For Articulated Characters,
2021
Clemson University
Acceleration Skinning: Kinematics-Driven Cartoon Effects For Articulated Characters, Niranjan Kalyanasundaram
All Theses
Secondary effects are key to adding fluidity and style to animation. This thesis introduces the idea of “Acceleration Skinning” following a recent well-received technique, Velocity Skinning, to automatically create secondary motion in character animation by modifying the standard pipeline for skeletal rig skinning. These effects, which animators may refer to as squash and stretch or drag, attempt to create an illusion of inertia. In this thesis, I extend the Velocity Skinning technique to include acceleration for creating a wider gamut of cartoon effects. I explore three new deformers that make use of this Acceleration Skinning framework: followthrough, centripetal stretch, and …
Let's Read: Designing A Smart Display Application To Support Codas When Learning Spoken Language,
2021
Chapman University
Let's Read: Designing A Smart Display Application To Support Codas When Learning Spoken Language, Katie Rodeghiero, Yingying Yuki Chen, Annika M. Hettmann, Franceli L. Cibrian
Engineering Faculty Articles and Research
Hearing children of Deaf adults (CODAs) face many challenges including having difficulty learning spoken languages, experiencing social judgment, and encountering greater responsibilities at home. In this paper, we present a proposal for a smart display application called Let's Read that aims to support CODAs when learning spoken language. We conducted a qualitative analysis using online community content in English to develop the first version of the prototype. Then, we conducted a heuristic evaluation to improve the proposed prototype. As future work, we plan to use this prototype to conduct participatory design sessions with Deaf adults and CODAs to evaluate the …
Feel And Touch: A Haptic Mobile Game To Assess Tactile Processing,
2021
Center for Scientific Research and Higher Education of Ensenada (CICESE)
Feel And Touch: A Haptic Mobile Game To Assess Tactile Processing, Ivonne Monarca, Monica Tentori, Franceli L. Cibrian
Engineering Faculty Articles and Research
Haptic interfaces have great potential for assessing the tactile processing of children with Autism Spectrum Disorder (ASD), an area that has been under-explored due to the lack of tools to assess it. Until now, haptic interfaces for children have mostly been used as a teaching or therapeutic tool, so there are still open questions about how they could be used to assess tactile processing of children with ASD. This article presents the design process that led to the development of Feel and Touch, a mobile game augmented with vibrotactile stimuli to assess tactile processing. Our feasibility evaluation, with 5 children …
Facilitating Heuristic Evaluation For Novice Evaluators,
2021
DePaul University
Facilitating Heuristic Evaluation For Novice Evaluators, Anas Abulfaraj
College of Computing and Digital Media Dissertations
Heuristic evaluation (HE) is one of the most widely used usability evaluation methods. The reason for its popularity is that it is a discount method, meaning that it does not require substantial time or resources, and it is simple, as evaluators can evaluate a system guided by a set of usability heuristics. Despite its simplicity, a major problem with HE is that there is a significant gap in the quality of results produced by expert and novice evaluators. This gap has made some scholars question the usefulness of the method as they claim that the evaluation results are a product …
Learning To Teach And Learn For Semi-Supervised Few-Shot Image Classification,
2021
Singapore Management University
Learning To Teach And Learn For Semi-Supervised Few-Shot Image Classification, Xinzhe Li, Jianqiang Huang, Yaoyao Liu, Qin Zhou, Shibao Zheng, Bernt Schiele, Qianru Sun
Research Collection School Of Computing and Information Systems
This paper presents a novel semi-supervised few-shot image classification method named Learning to Teach and Learn (LTTL) to effectively leverage unlabeled samples in small-data regimes. Our method is based on self-training, which assigns pseudo labels to unlabeled data. However, the conventional pseudo-labeling operation heavily relies on the initial model trained by using a handful of labeled data and may produce many noisy labeled samples. We propose to solve the problem with three steps: firstly, cherry-picking searches valuable samples from pseudo-labeled data by using a soft weighting network; and then, cross-teaching allows the classifiers to teach mutually for rejecting more noisy …
