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2023

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Articles 511 - 540 of 3503

Full-Text Articles in Computer Sciences

Formal Concept Analysis For Image Classification And Machine Learning Models For Anti-Crispr Protein Discovery In Bioinformatics, Minal Khatri Nov 2023

Formal Concept Analysis For Image Classification And Machine Learning Models For Anti-Crispr Protein Discovery In Bioinformatics, Minal Khatri

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

This study investigates two critical areas in bioinformatics: enhancing transparency in medical image analysis and advancing the discovery of Anti-CRISPR (Acr) proteins, which have potential in developing more precise and controlled CRISPR-Cas gene editing tools. While CNN’s are increasingly applied in critical fields like medical diagnosis, understanding their decision-making process remains a challenge. Although visualization techniques like Saliency maps offer insights into CNN’s decision-making for individual images, they do not explicitly establish a relationship between the high-level features learned by CNN’s and the class labels across dataset. To bridge this gap, Formal Concept Analysis (FCA) framework is leveraged as a …

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S-Net: A Multiple Cross Aggregation Convolutional Architecture For Automatic Segmentation Of Small/Thin Structures For Cardiovascular Applications, Nan Mu, Zonghan Lyu, Mostafa Rezaeitaleshmahalleh, Cassie Bonifas, Jordan Gosnell, Marcus Haw, Joseph Vettukattil, Jingfeng Jiang Nov 2023

S-Net: A Multiple Cross Aggregation Convolutional Architecture For Automatic Segmentation Of Small/Thin Structures For Cardiovascular Applications, Nan Mu, Zonghan Lyu, Mostafa Rezaeitaleshmahalleh, Cassie Bonifas, Jordan Gosnell, Marcus Haw, Joseph Vettukattil, Jingfeng Jiang

Michigan Tech Publications

With the success of U-Net or its variants in automatic medical image segmentation, building a fully convolutional network (FCN) based on an encoder-decoder structure has become an effective end-to-end learning approach. However, the intrinsic property of FCNs is that as the encoder deepens, higher-level features are learned, and the receptive field size of the network increases, which results in unsatisfactory performance for detecting low-level small/thin structures such as atrial walls and small arteries. To address this issue, we propose to keep the different encoding layer features at their original sizes to constrain the receptive field from increasing as the network …

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Evaluating Attack Surface Management In An Industrial Control System (Ics) Environment: Leveraging A Recon Ftw For Threat Classification And Incident Response, Nathalia De Sa Soares Nov 2023

Evaluating Attack Surface Management In An Industrial Control System (Ics) Environment: Leveraging A Recon Ftw For Threat Classification And Incident Response, Nathalia De Sa Soares

LSU Master's Theses

Protecting Industrial Control Systems (ICS) from cyber threats is paramount to
ensure the reliability and security of critical infrastructure. Organizations must proactively identify vulnerabilities and strengthen their incident response capabilities as attack vectors evolve. This research explores implementing an Attack Surface Management (ASM) approach, utilizing Recon FTW, to assess an operating ICS environment’s security posture comprehensively.
The primary objective of this research is to develop a tool for performing recon-
naissance in an ICS environment with a non-intrusive approach, enabling the realistic simulation of potential threat scenarios and the identification of critical areas requiring immediate attention and remediation. We aim …

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Impact Of Covid-19 On Security Vulnerabilities Of Learning Management Systems: A Study Towards Security And Sustainability Enhancement, Souheil Abdel-Latif Akacha Nov 2023

Impact Of Covid-19 On Security Vulnerabilities Of Learning Management Systems: A Study Towards Security And Sustainability Enhancement, Souheil Abdel-Latif Akacha

Thesis/ Dissertation Defenses

The rapid adoption of Learning Management Systems (LMSs) like Moodle, Chamilo, and Ilias became essential for online education due to the COVID-19 pandemic. While this transformation revolutionized online learning, it also exposed security vulnerabilities that require immediate attention. This thesis explores these security concerns within widely used LMSs, namely Moodle, Chamilo, and Ilias, across pre-pandemic, pandemic, and post-pandemic periods. By analyzing existing patches and security measures and considering emerging cybersecurity technologies and trends, comprehensive recommendations are formulated to enhance the security and sustainability of LMSs against evolving cyber threats, offering valuable insights to educational institutions for proactive risk mitigation. Therefore, …

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Web 2 Vs. Web 3 Paths To The Metaverse: Who Is Leading? Who Should Lead?, Le Kuai, Mary Lacity, Jeffrey K. Mullins Nov 2023

Web 2 Vs. Web 3 Paths To The Metaverse: Who Is Leading? Who Should Lead?, Le Kuai, Mary Lacity, Jeffrey K. Mullins

Information Systems Faculty Publications and Presentations

Our research investigates two questions: Who is leading the metaverse? Who should lead? The questions are important because metaverse will have significant consequences for individuals, businesses, and society. We examined the current leaders of metaverse on two evolutionary paths, namely Web 2 and Web 3. Based on regulatory reports, corporate press releases, and patents, we found that only a handful of Web 2 companies are “all-in” on metaverse, and at least one of these enterprises, Meta, is on track to end up as a dominant platform provider. Based on market capitalization, user activity, and patents, only a handful of Web …

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Lightweight Multi-Class Support Vector Machine-Based Medical Diagnosis System With Privacy Preservation, Sherif Abdelfattah, Mohamed Baza, Mohamed Mahmoud, Mostafa M. Fouda, Khalid Abualsaud, Elias Yaacoub, Maazen Alsabaan, Mohsen Guizani Nov 2023

Lightweight Multi-Class Support Vector Machine-Based Medical Diagnosis System With Privacy Preservation, Sherif Abdelfattah, Mohamed Baza, Mohamed Mahmoud, Mostafa M. Fouda, Khalid Abualsaud, Elias Yaacoub, Maazen Alsabaan, Mohsen Guizani

Machine Learning Faculty Publications

Machine learning, powered by cloud servers, has found application in medical diagnosis, enhancing the capabilities of smart healthcare services. Research literature demonstrates that the support vector machine (SVM) consistently demonstrates remarkable accuracy in medical diagnosis. Nonetheless, safeguarding patients’ health data privacy and preserving the intellectual property of diagnosis models is of paramount importance. This concern arises from the common practice of outsourcing these models to third-party cloud servers that may not be entirely trustworthy. Few studies in the literature have delved into addressing these issues within SVM-based diagnosis systems. These studies, however, typically demand substantial communication and computational resources and …

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From Type-2 Fuzzy To Type-2 Intervals And Type-2 Probabilities, Vladik Kreinovich, Olga Kosheleva, Luc Longpré Nov 2023

From Type-2 Fuzzy To Type-2 Intervals And Type-2 Probabilities, Vladik Kreinovich, Olga Kosheleva, Luc Longpré

Departmental Technical Reports (CS)

Our knowledge comes from observations, measurements, and expert opinions. Measurements and observations are never 100% accurate, there is always a difference between the measurement result and the actual value of the corresponding quantity. We gauge the resulting uncertainty either by an interval of possible values, or by a probability distribution on the set of possible values, or by a membership function that describes to what extent different values are possible. The information about uncertainty also comes either from measurements or from expert estimates and is, therefore, also uncertain. It is important to take such "type-2" uncertainty into account. This is …

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Giant Footprints Of Buddha And Generalized Limits, Julio C. Urenda, Vladik Kreinovich Nov 2023

Giant Footprints Of Buddha And Generalized Limits, Julio C. Urenda, Vladik Kreinovich

Departmental Technical Reports (CS)

In many places in Asia, there are footprints claimed to be left by Buddha. Many of them are much larger than the usual size of human feet, up to 150 cm and more in length. In this paper, we provide a possible mathematical explanation for such unusual sizes.

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How To Efficiently Propagate P-Box Uncertainty, Olga Kosheleva, Vladik Kreinovich Nov 2023

How To Efficiently Propagate P-Box Uncertainty, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

In many practical situations, to get the desired estimate or prediction, we need to process existing data. This data usually comes from measurements, and measurements are never 100% accurate. Because we only know the input values with uncertainty, the results of processing this data also comes with uncertainty. To make an appropriate decision, we need to know how accurate is the resulting estimate, i.e., how the input uncertainty "propagates" through the data processing algorithm. In the ideal case, when we know the probability distribution of each measurement error, we can, in principle, use Monte-Carlo simulations to describe the uncertainty of …

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Pushing The Boundaries Of Learning: Smu School Of Computing And Information Systems Celebrates Its 20th Birthday, Singapore Management University Nov 2023

Pushing The Boundaries Of Learning: Smu School Of Computing And Information Systems Celebrates Its 20th Birthday, Singapore Management University

SMU Press Releases and News

Over 400 people – namely alumni, faculty members and students – gathered to celebrate the 20th anniversary of the School of Computing and Information Systems (SCIS) of the Singapore Management University (SMU) on 20 Oct 2023. Over the past two decades, the school has grown from strength to strength. Its alumni stand at over 6,000, its undergraduate population at over 2,300 and its postgraduate at close to 700, including about 130 doctoral students. SCIS is ranked #4 globally for Software Engineering based on output in year 2022 on CSRankings, an influential metric on research publication in computing areas. SCIS’ postgraduate …

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Enhancing Search Engine Results: A Comparative Study Of Graph And Timeline Visualizations For Semantic And Temporal Relationship Discovery, Muhammad Shahiq Qureshi Nov 2023

Enhancing Search Engine Results: A Comparative Study Of Graph And Timeline Visualizations For Semantic And Temporal Relationship Discovery, Muhammad Shahiq Qureshi

Electronic Theses and Dissertations

In today’s digital age, search engines have become indispensable tools for finding information among the corpus of billions of webpages. The standard that most search engines follow is to display search results in a list-based format arranged according to a ranking algorithm. Although this format is good for presenting the most relevant results to users, it fails to represent the underlying relations between different results. These relations, among others, can generally be of either a temporal or semantic nature. A user who wants to explore the results that are connected by those relations would have to make a manual effort …

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Uncertainty Quantification For Results Of Ai-Based Data Processing: Towards More Feasible Algorithms, Christoph Q. Lauter, Martine Ceberio, Vladik Kreinovich, Olga Kosheleva Nov 2023

Uncertainty Quantification For Results Of Ai-Based Data Processing: Towards More Feasible Algorithms, Christoph Q. Lauter, Martine Ceberio, Vladik Kreinovich, Olga Kosheleva

Departmental Technical Reports (CS)

AI techniques have been actively and successfully used in data processing. This tendency started with fuzzy techniques, now neural network techniques are actively used. With each new technique comes the need for the corresponding uncertainty quantification (UQ). In principle, for both fuzzy and neural techniques, we can use the usual UQ methods -- however, these techniques often require an unrealistic amount of computation time. In this paper, we show that in both cases, we can use specific features of the corresponding techniques to drastically speed up the corresponding computations.

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Usually, Either Left And Right Brains Are Equally Active Or Only One Of Them Is Active: First-Principles Explanation, Julio C. Urenda, Vladik Kreinovich Nov 2023

Usually, Either Left And Right Brains Are Equally Active Or Only One Of Them Is Active: First-Principles Explanation, Julio C. Urenda, Vladik Kreinovich

Departmental Technical Reports (CS)

It is known that in most practical situations, either both left and right brains are equally active, or only one of them is active. A recent paper showed that this empirical phenomenon can be explained by a realistic model of the brain effectiveness. In this paper, we show that this conclusion can be made without any specific assumptions about the brain, based on first principles.

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Which Random-Set Representation Of A Fuzzy Set Is The Simplest?, Vladik Kreinovich, Olga Kosheleva, Hung T. Nguyen Nov 2023

Which Random-Set Representation Of A Fuzzy Set Is The Simplest?, Vladik Kreinovich, Olga Kosheleva, Hung T. Nguyen

Departmental Technical Reports (CS)

One of the ways to elicit membership degrees is by polling. For example, we ask a group of people how many believe that 30 C is hot. If 8 out of ten say that it is hot, we assign the degree 8/10 to the statement "30 C is hot". In precise mathematical terms, polling can be described via so-called random sets. It is known that every fuzzy set can be obtained this way, i.e., that every fuzzy set can be represented by an appropriate random set. Moreover, it is known that for many fuzzy sets, there are several different random-set …

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Limitations And Possibilities Of Digital Restoration Techniques Using Generative Ai Tools: Reconstituting Antoine François Callet’S Achilles Dragging Hector’S Body Past The Walls Of Troy, Charles O'Brien, James Hutson, Trent Olsen, Jay Ratican Nov 2023

Limitations And Possibilities Of Digital Restoration Techniques Using Generative Ai Tools: Reconstituting Antoine François Callet’S Achilles Dragging Hector’S Body Past The Walls Of Troy, Charles O'Brien, James Hutson, Trent Olsen, Jay Ratican

Faculty Scholarship

Digital restoration offers new avenues for conserving historical artworks, yet presents unique challenges. This research delves into the balance between traditional restoration methods and the use of generative artificial intelligence (AI) tools, using Antoine François Callet’s portrayal of Achilles Dragging Hector’s Body Past the Walls of Troy as a case study. The application of Easy Diffusion and Stable Diffusion 2.1 technologies provides insights into AI-driven restoration methods such as inpainting and colorization. Results indicate that while AI can streamline the restoration process, repeated inpainting can compromise the painting’s color quality and detailed features. Furthermore, the AI approach occasionally introduces unintended …

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Effective And Efficient Semantic Representations And Their Applications, Chong Cher Chia Nov 2023

Effective And Efficient Semantic Representations And Their Applications, Chong Cher Chia

Dissertations and Theses Collection (Open Access)

The proliferation of affordable and compact digital storage has also led to the creation of enormous databases of information, and much attention has been focused on the problem of processing unorganized and unstructured information into some form from which additional value can be extracted. Contemporary approaches to this problem virtually necessitate the use of complex models running on computational systems due to the sheer volume of information to be processed. While it is possible for the model to be fed the actual data as input, typically a representation of the data is used instead. These representations are therefore of interest, …

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Novus Ex Machina: Realise Your Organisation’S Creative Potential With Ai, Adam Tatarynowicz, Utz Claassen Nov 2023

Novus Ex Machina: Realise Your Organisation’S Creative Potential With Ai, Adam Tatarynowicz, Utz Claassen

Asian Management Insights

Innovation managers must learn how to harness AI’s transformative potential.

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Healthaichain: Improving Security And Safety Using Blockchain Technology Applications In Ai-Based Healthcare Systems, Naresh Kshetri, James Hutson, Revathy G Nov 2023

Healthaichain: Improving Security And Safety Using Blockchain Technology Applications In Ai-Based Healthcare Systems, Naresh Kshetri, James Hutson, Revathy G

Faculty Scholarship

Blockchain as a digital ledger for keeping records of digital transactions and other information, it is secure and decentralized technology. The globally growing number of digital population every day possesses a significant threat to online data including the medical and patients’ data. After bitcoin, blockchain technology has emerged into a general-purpose technology with applications in medical industries and healthcare. Blockchain can promote highly configurable openness while retaining the highest security standards for critical data of medical patients. Referred to as distributed record keeping for healthcare systems which makes digital assets unalterable and transparent via a cryptographic hash and decentralized network. …

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Spectrum-Enhanced Trca (Se-Trca): A Novel Approach For Direction Detection In Ssvep-Based Bci, Amirmohammad Mijani, Mohammad Norizadeh Cherloo, Haoteng Tang, Liang Zhan Nov 2023

Spectrum-Enhanced Trca (Se-Trca): A Novel Approach For Direction Detection In Ssvep-Based Bci, Amirmohammad Mijani, Mohammad Norizadeh Cherloo, Haoteng Tang, Liang Zhan

Computer Science Faculty Publications

The Steady State Visual Evoked Potential (SSVEP) is a widely used component in BCIs due to its high noise resistance and low equipment requirements. Recently, a novel SSVEP-based paradigm has been introduced for direction detection, in which, unlike the common SSVEP paradigms that use several frequency stimuli, only one flickering stimulus is used and it makes direction detection very challenging. So far, only the CCA method has been used for direction detection using SSVEP component analysis. Since Canonical Correlation Analysis (CCA) has some limitations, a Task-Related Component Analysis (TRCA) based method has been introduced for feature extraction to improve the …

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Digitizing The Cultural Capital: Harnessing Digital Humanities For Heritage Preservation In Bujumbura, Burundi, James Hutson, Pace Ellsworth, Matt Ellsworth, Jean Bosco Ntungirimana Nov 2023

Digitizing The Cultural Capital: Harnessing Digital Humanities For Heritage Preservation In Bujumbura, Burundi, James Hutson, Pace Ellsworth, Matt Ellsworth, Jean Bosco Ntungirimana

Faculty Scholarship

In an era where the erosion of cultural heritage is increasingly prevalent, there exists a critical imperative to explore and implement innovative methods for the preservation and revitalization of cultural identities, as exemplified by the urgent situation in Bujumbura, Burundi. Central to this study is the exploration of innovative digital methodologies for archiving a wide spectrum of cultural artifacts, including both notable and everyday heritage elements, in Bujumbura. Traditional approaches to biographical and historical profiling have predominantly focused on official records and significant events, often neglecting the richness of personal experiences and everyday interactions that substantially shape cultural identities. To …

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Constructing Holistic Spatio-Temporal Scene Graph For Video Semantic Role Labeling, Yu Zhao, Hao Fei, Yixin Cao, Bobo Li, Meishan Zhang, Jianguo Wei, Min Zhang, Tat-Seng Chua Nov 2023

Constructing Holistic Spatio-Temporal Scene Graph For Video Semantic Role Labeling, Yu Zhao, Hao Fei, Yixin Cao, Bobo Li, Meishan Zhang, Jianguo Wei, Min Zhang, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

As one of the core video semantic understanding tasks, Video Semantic Role Labeling (VidSRL) aims to detect the salient events from given videos, by recognizing the predict-argument event structures and the interrelationships between events. While recent endeavors have put forth methods for VidSRL, they can be mostly subject to two key drawbacks, including the lack of fine-grained spatial scene perception and the insufficiently modeling of video temporality. Towards this end, this work explores a novel holistic spatio-temporal scene graph (namely HostSG) representation based on the existing dynamic scene graph structures, which well model both the fine-grained spatial semantics and temporal …

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Understanding The Impact Of Trade Policy Effect Uncertainty On Firm-Level Innovation Investment: A Deep Learning Approach, Daniel. Chen, Nan Hu, Peng. Liang, Morgan. Swink Nov 2023

Understanding The Impact Of Trade Policy Effect Uncertainty On Firm-Level Innovation Investment: A Deep Learning Approach, Daniel. Chen, Nan Hu, Peng. Liang, Morgan. Swink

Research Collection School Of Computing and Information Systems

Integrating the real options perspective and resource dependence theory, this study examines how firms adjust their innovation investments to trade policy effect uncertainty (TPEU), a less studied type of firm specific, perceived environmental uncertainty in which managers have difficulty predicting how potential policy changes will affect business operations. To develop a text-based, context-dependent, time-varying measure of firm-level perceived TPEU, we apply Bidirectional Encoder Representations from Transformers (BERT), a state-of-the-art deep learning approach. We apply BERT to analyze the texts of mandatory Management Discussion and Analysis (MD&A) sections of annual reports for a sample of 22,669 firm-year observations from 3,181 unique …

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Npf-200: A Multi-Modal Eye Fixation Dataset And Method For Non-Photorealistic Videos, Ziyu Yang, Sucheng Ren, Zongwei Wu, Nanxuan Zhao, Junle Wang, Jing Qin, Shengfeng He Nov 2023

Npf-200: A Multi-Modal Eye Fixation Dataset And Method For Non-Photorealistic Videos, Ziyu Yang, Sucheng Ren, Zongwei Wu, Nanxuan Zhao, Junle Wang, Jing Qin, Shengfeng He

Research Collection School Of Computing and Information Systems

Non-photorealistic videos are in demand with the wave of the metaverse, but lack of sufficient research studies. This work aims to take a step forward to understand how humans perceive nonphotorealistic videos with eye fixation (i.e., saliency detection), which is critical for enhancing media production, artistic design, and game user experience. To fill in the gap of missing a suitable dataset for this research line, we present NPF-200, the first largescale multi-modal dataset of purely non-photorealistic videos with eye fixations. Our dataset has three characteristics: 1) it contains soundtracks that are essential according to vision and psychological studies; 2) it …

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An Empirical Study On The Use Of Secure Predictive Analytics For Improving Trade Forecasting In The Uae, Asma Salem Alneyadi Nov 2023

An Empirical Study On The Use Of Secure Predictive Analytics For Improving Trade Forecasting In The Uae, Asma Salem Alneyadi

Theses

Trade contributes to the United Arab Emirates' economic growth. This thesis focuses on trade dynamics in the UAE using Long Short-Term Memory (LSTM) neural networks. The study focuses on both import and export activities, providing understandings into the complex patterns and impacts of international trade on the UAE's economic growth. The research begins by constructing an LSTM model to forecast the UAE's Gross Domestic Product (GDP) through the utilization of historical trade data. We use time series data for imports and exports as key input features. This innovative approach highlights the relevance of trade statistics as a leading indicator of …

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Cyberattacks And Security Of Cloud Computing: A Complete Guideline, Muhammad Dawood, Shanshan Tu, Chuangbai Xiao, Hisham Alasmary, Muhammad Waqas, Sadaqat Ur Rehman Nov 2023

Cyberattacks And Security Of Cloud Computing: A Complete Guideline, Muhammad Dawood, Shanshan Tu, Chuangbai Xiao, Hisham Alasmary, Muhammad Waqas, Sadaqat Ur Rehman

Research outputs 2022 to 2026

Cloud computing is an innovative technique that offers shared resources for stock cache and server management. Cloud computing saves time and monitoring costs for any organization and turns technological solutions for large-scale systems into server-to-service frameworks. However, just like any other technology, cloud computing opens up many forms of security threats and problems. In this work, we focus on discussing different cloud models and cloud services, respectively. Next, we discuss the security trends in the cloud models. Taking these security trends into account, we move to security problems, including data breaches, data confidentiality, data access controllability, authentication, inadequate diligence, phishing, …

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Dress-Code Violation Detection In Arabic Regions Using Object Detection Machine Learning Model, Maha Sadat Aghaei Nov 2023

Dress-Code Violation Detection In Arabic Regions Using Object Detection Machine Learning Model, Maha Sadat Aghaei

Theses

The dress code violation detection system is crucial for assessing clothing appropriateness in public areas. This study aims to improve this system using advanced computer vision and machine learning techniques to more effectively categorize people's attire in images and videos. To enhance adaptability and create a user-friendly graphical interface for system management and deployment, we have generated a unique dataset from various contexts mix of Western and Arabic clothing. This allows users to interact with graphical components, including the ability to upload images or use live video for clothing detection. Moreover, we have taken privacy concerns into account and implemented …

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Individuality And The Collective In Ai Agents: Explorations Of Shared Consciousness And Digital Homunculi In The Metaverse For Cultural Heritage, James Hutson, Jay Ratican Nov 2023

Individuality And The Collective In Ai Agents: Explorations Of Shared Consciousness And Digital Homunculi In The Metaverse For Cultural Heritage, James Hutson, Jay Ratican

Faculty Scholarship

The confluence of extended reality (XR) technologies, including augmented and virtual reality, with large language models (LLM) marks a significant advancement in the field of digital humanities, opening uncharted avenues for the representation of cultural heritage within the burgeoning metaverse. This paper undertakes an examination of the potentialities and intricacies of such a convergence, focusing particularly on the creation of digital homunculi or changelings. These virtual beings, remarkable for their sentience and individuality, are also part of a collective consciousness, a notion explored through a thematic comparison in science fiction with the Borg and the Changelings in the Star Trek …

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Designing Secure Mental Healthcare Chatbots For Older Adults, Aishwarya Surani Nov 2023

Designing Secure Mental Healthcare Chatbots For Older Adults, Aishwarya Surani

Electronic Theses and Dissertations

The landscape of mental health support has evolved as a result of the rising demand for digital mental healthcare services. Users now have an opportunity to seek mental health support online due to the growth of digital platforms. For those looking for mental health treatments, chatbots have evolved as user-friendly, accessible platforms that provide remote access and convenience. However, for chatbots to be effective, users must divulge personal and sensitive information, such as demographics, insurance information, and a history of mental illness. While chatbots offer services to a variety of demographic users, older adults face unique challenges related to usability, …

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Optimizing E-Payment Applications For Older Adults: User-Centered Solutions To Improve Security, Privacy, Usability, And Accessibility, Urvashi Kishnani Nov 2023

Optimizing E-Payment Applications For Older Adults: User-Centered Solutions To Improve Security, Privacy, Usability, And Accessibility, Urvashi Kishnani

Electronic Theses and Dissertations

In an increasingly digital world, older adults are rapidly becoming a vital demographic in the realm of electronic financial transactions. It is imperative to address their unique needs and challenges to ensure their financial well-being. Older adults can be more vulnerable to various online threats, making security and privacy paramount. As they adapt to the digital age, understanding their specific privacy concerns and preferences is crucial for creating trustworthy e-payment systems. Moreover, enhancing the usability of e-payment applications for older adults promotes financial independence and inclusion, contributing to their overall quality of life. By focusing on these critical dimensions, we …

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A Fast And Responsive Web-Based Framework For Visualizing Hpc Application Usage, Ved Arora, Nayeli Gurrola, Amiya K. Maji, Guangzhen Jin Nov 2023

A Fast And Responsive Web-Based Framework For Visualizing Hpc Application Usage, Ved Arora, Nayeli Gurrola, Amiya K. Maji, Guangzhen Jin

Computer Science Faculty Publications

Insights about applications and user environments can help HPC center staff make data-driven decisions about cluster operations. In this paper, we present a fast and responsive web-based visualization framework for analyzing HPC application usage. By leveraging XALT, a powerful tool for tracking application and library usage, we collected tens of millions of data points on a national supercomputer. The portable visualization framework created with Plotly Dash can be easily launched as a container and accessed from a web browser. The presented visualizations take a deep dive into the XALT data, analyzing application use, compiler usage, library usage, and even user-specific …

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