Physical Sciences and Mathematics Commons^™

A Hybrid Approach For Detecting Prerequisite Relations In Multi-Modal Food Recipes, Liangming Pan, Jingjing Chen, Shaoteng Liu, Chong-Wah Ngo, Min-Yen Kan, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Modeling the structure of culinary recipes is the core of recipe representation learning. Current approaches mostly focus on extracting the workflow graph from recipes based on text descriptions. Process images, which constitute an important part of cooking recipes, has rarely been investigated in recipe structure modeling. We study this recipe structure problem from a multi-modal learning perspective, by proposing a prerequisite tree to represent recipes with cooking images at a step-level granularity. We propose a simple-yet-effective two-stage framework to automatically construct the prerequisite tree for a recipe by (1) utilizing a trained classifier to detect pairwise prerequisite relations that fuses …

Find Me If You Can: Aligning Users In Different Social Networks, Priyanka Kasbekar, Katerina Potika, Chris Pollett

Faculty Publications, Computer Science

Online Social Networks allow users to share experiences with friends and relatives, make announcements, find news and jobs, and more. Several have user bases that number in the hundred of millions and even billions. Very often many users belong to multiple social networks at the same time under possibly different user names. Identifying a user from one social network on another social network gives information about a user's behavior on each platform, which in turn can help companies perform graph mining tasks, such as community detection and link prediction. The process of identifying or aligning users in multiple networks is …

Simulation Approaches To X-Ray C-Arm-Based Interventions, Daniel R. Allen

Electronic Thesis and Dissertation Repository

Mobile C-Arm systems have enabled interventional spine procedures, such as facet joint injections, to be performed minimally-invasively under X-ray or fluoroscopy guidance. The downside to these procedures is the radiation exposure the patient and medical staff are subject to, which can vary greatly depending on the procedure as well as the skill and experience of the team. Standard training methods for these procedures involve the use of a physical C-Arm with real X-rays training on either cadavers or via an apprenticeship-based program. Many guidance systems have been proposed in the literature which aim to reduce the amount of radiation exposure …

Ntire 2020 Challenge On Video Quality Mapping: Methods And Results, D. Fuoli, Zhiwu Huang, M. Danelljan, R. Timofte, H. Wang, L. Jin, D. Su, J. Liu, J. Lee, M. Kudelski, L. Bala, D. Hryboy, M. Mozejko, M. Li, S. Li, B. Pang, C. Lu, Li C., He D., Li F.

Research Collection School Of Computing and Information Systems

This paper reviews the NTIRE 2020 challenge on video quality mapping (VQM), which addresses the issues of quality mapping from source video domain to target video domain. The challenge includes both a supervised track (track 1) and a weakly-supervised track (track 2) for two benchmark datasets. In particular, track 1 offers a new Internet video benchmark, requiring algorithms to learn the map from more compressed videos to less compressed videos in a supervised training manner. In track 2, algorithms are required to learn the quality mapping from one device to another when their quality varies substantially and weaklyaligned video pairs …

Adaptive Loss-Aware Quantization For Multi-Bit Networks, Zhongnan Qu, Zimu Zhou, Yun Cheng, Lothar Thiele

Research Collection School Of Computing and Information Systems

We investigate the compression of deep neural networks by quantizing their weights and activations into multiple binary bases, known as multi-bit networks (MBNs), which accelerate the inference and reduce the storage for the deployment on low-resource mobile and embedded platforms. We propose Adaptive Loss-aware Quantization (ALQ), a new MBN quantization pipeline that is able to achieve an average bitwidth below one-bit without notable loss in inference accuracy. Unlike previous MBN quantization solutions that train a quantizer by minimizing the error to reconstruct full precision weights, ALQ directly minimizes the quantizationinduced error on the loss function involving neither gradient approximation nor …

Evaluating An Ordinal Output Using Data Modeling, Algorithmic Modeling, And Numerical Analysis, Martin Keagan Wynne Brown

Murray State Theses and Dissertations

Data and algorithmic modeling are two different approaches used in predictive analytics. The models discussed from these two approaches include the proportional odds logit model (POLR), the vector generalized linear model (VGLM), the classification and regression tree model (CART), and the random forests model (RF). Patterns in the data were analyzed using trigonometric polynomial approximations and Fast Fourier Transforms. Predictive modeling is used frequently in statistics and data science to find the relationship between the explanatory (input) variables and a response (output) variable. Both approaches prove advantageous in different cases depending on the data set. In our case, the data …

Exploring Cybersecurity Awareness And Training Strategies To Protect Information Systems And Data, Michael Hanna

Walden Dissertations and Doctoral Studies

Ineffective security education, training, and awareness (SETA) programs contribute to compromises of organizational information systems and data. Inappropriate actions from users due to ineffective SETA programs may result in legal consequences, fines, reputational damage, adverse impacts on national security, and criminal acts. Grounded in social cognitive theory, the purpose of this qualitative multiple case study was to explore strategies hospitality organizational information technology (IT) leaders utilized to implement SETA successfully. The participants were organizational IT leaders from four organizations in Hampton Roads, Virginia. Data collection was performed using telephone and video teleconference interviews with organizational IT leaders (n = 6) …

Risk Assessment Strategies To Reduce Profitability Losses From Pipeline Accidents In The Natural Gas Industry, Cynthia Hurdle

Walden Dissertations and Doctoral Studies

Ineffective risk assessment strategies can negatively impact the natural gas industry.

Engineer project managers who struggle to maintain a risk assessment plan are at high risk of failure, which could result in devastating consequences for the business and environment. Grounded in the theory of risk assessment, the purpose of this qualitative single case study was to explore strategies engineer project managers in the natural gas industry use to improve risk assessment planning to reduce pipeline accidents and improve profitability. The participants comprised of 5 engineer project managers in Virginia, who effectively use risk assessment strategies to promote safety metrics and …

Implementing And Assessing The Use Of A New Strategy For Training Chemistry Graduate Teaching Assistants, Amanda Hyett

Electronic Theses and Dissertations

Graduate teaching assistants (GTAs) largely contribute to undergraduate education but are often underprepared for their role as educators. Most graduate students attend graduate school to perform research and are then asked to teach for the first time without sufficient pedagogy training. To assist in increasing the GTAs pedagogical knowledge, a scenario-based activity series was developed and implemented for first- and second-year GTAs. Developing scenario-based scenarios from actual laboratory events provided GTAs with the opportunity to practice prior to engaging in the laboratory classroom. The Teaching Assistant Intervention Activities (TAIAs) included topics such as interpersonal skills and behaviors, group process, working …

Exploring Strategies For Enforcing Cybersecurity Policies, Bayo Olushola Omoyiola

Walden Dissertations and Doctoral Studies

Some cybersecurity leaders have not enforced cybersecurity policies in their organizations. The lack of employee cybersecurity policy compliance is a significant threat in organizations because it leads to security risks and breaches. Grounded in the theory of planned behavior, the purpose of this qualitative case study was to explore the strategies cybersecurity leaders utilize to enforce cybersecurity policies. The participants were cybersecurity leaders from 3 large organizations in southwest and northcentral Nigeria responsible for enforcing cybersecurity policies. The data collection included semi-structured interviews of participating cybersecurity leaders (n = 12) and analysis of cybersecurity policy documents (n = 20). Thematic …

Shipbuilding Supply Chain Framework And Digital Transformation: A Project Portfolios Risk Evaluation, Rafael Diaz, Katherine Smith, Rafael Landaeta, Antonio Padovano

VMASC Publications

Program portfolio managers in digital transformation programs have a need for knowledge that can guide decisions related to the alignment of program investments with the sustainability and strategic objectives of the organization. The purpose of this research is to illustrate the utility of a framework capable of clarifying the cost-benefit tradeoffs stemming from assessing digitalization program investment risks in the military shipbuilding sector. Our approach uses Artificial Neural Network to quantify benefits and risks per project while employing scenario analysis to quantify the effects of operational constraints. A Monte Carlo model is used to generate data samples that support the …