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High-Performance Computing In Next-Generation Sequencing Read Alignment, Minh H. Pham
High-Performance Computing In Next-Generation Sequencing Read Alignment, Minh H. Pham
USF Tampa Graduate Theses and Dissertations
Advancements in Next-Generation Sequencing (NGS) have dramatically reduced the cost and increased the speed of DNA sequencing. However, this rapid influx of data necessitates efficient and robust analysis tools, particularly for the complex task of aligning short NGS reads to reference genomes such as the human genome. We explore groundbreaking computational strategies and hardware acceleration to optimize this critical alignment process. This dissertation is structured around three innovative studies. First, we introduce a novel approach to dynamic memory allocation tailored for massively parallel systems, particularly Graphical Processing Units (GPUs), to support NGS alignment and other applications. Unlike traditional memory allocators …
Methionine Sulfoxide Speciation In Mouse Hippocampus Revealed By Global Proteomics Exhibits Age- And Alzheimer’S Disease-Dependent Changes Targeted To Mitochondrial And Glycolytic Pathways, Filipa Blasco Tavares Pereira Lopes, Daniela Schlatzer, Mengzhen Li, Serhan Yılmaz, Rihua Wang, Xin Qi, Marzieh Ayati, Mehmet Koyutürk, Mark R. Chance
Methionine Sulfoxide Speciation In Mouse Hippocampus Revealed By Global Proteomics Exhibits Age- And Alzheimer’S Disease-Dependent Changes Targeted To Mitochondrial And Glycolytic Pathways, Filipa Blasco Tavares Pereira Lopes, Daniela Schlatzer, Mengzhen Li, Serhan Yılmaz, Rihua Wang, Xin Qi, Marzieh Ayati, Mehmet Koyutürk, Mark R. Chance
Computer Science Faculty Publications
Methionine oxidation to the sulfoxide form (MSox) is a poorly understood post-translational modification of proteins associated with non-specific chemical oxidation from reactive oxygen species (ROS), whose chemistries are linked to various disease pathologies, including neurodegeneration. Emerging evidence shows MSox site occupancy is, in some cases, under enzymatic regulatory control, mediating cellular signaling, including phosphorylation and/or calcium signaling, and raising questions as to the speciation and functional nature of MSox across the proteome. The 5XFAD lineage of the C57BL/6 mouse has well-defined Alzheimer’s and aging states. Using this model, we analyzed age-, sex-, and disease-dependent MSox speciation in the mouse hippocampus. …
Methionine Sulfoxide Speciation In Mouse Hippocampus Revealed By Global Proteomics Exhibits Age- And Alzheimer’S Disease-Dependent Changes Targeted To Mitochondrial And Glycolytic Pathways, Filipa Blasco Tavares Pereira Lopes, Daniela Schlatzer, Mengzhen Li, Serhan Yılmaz, Rihua Wang, Xin Qi, Marzieh Ayati, Mehmet Koyutürk, Mark R. Chance
Methionine Sulfoxide Speciation In Mouse Hippocampus Revealed By Global Proteomics Exhibits Age- And Alzheimer’S Disease-Dependent Changes Targeted To Mitochondrial And Glycolytic Pathways, Filipa Blasco Tavares Pereira Lopes, Daniela Schlatzer, Mengzhen Li, Serhan Yılmaz, Rihua Wang, Xin Qi, Marzieh Ayati, Mehmet Koyutürk, Mark R. Chance
Computer Science Faculty Publications
Methionine oxidation to the sulfoxide form (MSox) is a poorly understood post-translational modification of proteins associated with non-specific chemical oxidation from reactive oxygen species (ROS), whose chemistries are linked to various disease pathologies, including neurodegeneration. Emerging evidence shows MSox site occupancy is, in some cases, under enzymatic regulatory control, mediating cellular signaling, including phosphorylation and/or calcium signaling, and raising questions as to the speciation and functional nature of MSox across the proteome. The 5XFAD lineage of the C57BL/6 mouse has well-defined Alzheimer’s and aging states. Using this model, we analyzed age-, sex-, and disease-dependent MSox speciation in the mouse hippocampus. …
Ensemble Learning-Powered Url Phishing Detection: A Performance Driven Approach, Shougfta Mushtaq, Tabassum Javed, Mazliham Mohd Su’Ud
Ensemble Learning-Powered Url Phishing Detection: A Performance Driven Approach, Shougfta Mushtaq, Tabassum Javed, Mazliham Mohd Su’Ud
Journal of Informatics and Web Engineering
With the rapid growth in the usage of the Internet, criminals have found new ways to engage in cyber-attacks. The most common and widespread attack is URL phishing. The proposed system focuses on improving phishing website detection using feature selection and ensemble learning. This model uses two datasets, DS-30 and DS-50, each with 30 and 50 features. Ensemble learning using a voting classifier was then applied to train the model, achieving more accuracy. The combination of HEFS with random forest distribution achieved 94.6% accuracy while minimizing the number of features used (20.8% of the base feature set). The classifier works …
Editorial Preview, Su-Cheng Haw
Editorial Preview, Su-Cheng Haw
Journal of Informatics and Web Engineering
This editorial highlights all 18 papers in the June issue that deal with the practical aspects of Machine Learning (ML), Artificial Intelligence (AI), Data Mining (DM), the Internet of Things (IoT), Computer Vision, e-learning, and other topics in Computer Science. This issue also includes suggestions for several worthwhile works that deserve further research. With effective from our third volume first issue, we will be publishing triannually in February, June and October.
Classroom Environment Analysis Via Internet Of Things, Kai-Yuan Tan, Kok-Why Ng, Kanesaraj Ramasamy
Classroom Environment Analysis Via Internet Of Things, Kai-Yuan Tan, Kok-Why Ng, Kanesaraj Ramasamy
Journal of Informatics and Web Engineering
In this era of rapid technological advancement, the potential of the digital age has opened up numerous possibilities for our society. However, despite these advancements, traditional classrooms still lack the necessary technology to create an optimal learning environment for students. Consequently, students may struggle to effectively acquire knowledge within classrooms. This paper aims to conduct a classroom environment analysis using Internet of Things technology to gather data and uncover valuable insights. The proposed solution involves an embedded system for controlling and monitoring the classroom environment, as well as exporting historical data for further research. By ensuring accurate data collection, this …
Knowledge-Based Word Tokenization System For Urdu, Asif Khan, Khairullah Khan, Wahab Khan, Sadiq Nawaz Khan, Rafiul Haq
Knowledge-Based Word Tokenization System For Urdu, Asif Khan, Khairullah Khan, Wahab Khan, Sadiq Nawaz Khan, Rafiul Haq
Journal of Informatics and Web Engineering
Word tokenization, a foundational step in natural language processing (NLP), is critical for tasks like part-of-speech tagging, named entity recognition, and parsing, as well as various independent NLP applications. In our tech-driven era, the exponential growth of textual data on the World Wide Web demands sophisticated tools for effective processing. Urdu, spoken widely across the globe, is experiencing a surge in, presents unique challenges due to its distinct writing style, the absence of capitalization features, and the prevalence of compound words. This study introduces a novel knowledge-based word tokenization system tailored for Urdu. Central to this system is a maximum …
Unveiling The Efficacy Of Ai-Based Algorithms In Phishing Attack Detection, Tajamul Shahzad, Kashif Aman
Unveiling The Efficacy Of Ai-Based Algorithms In Phishing Attack Detection, Tajamul Shahzad, Kashif Aman
Journal of Informatics and Web Engineering
Phishing poses a significant challenge in an ever-evolving world. The increased usage of the Internet has resulted in the emergence of a different kind of theft referred to as cybercrime. The term cybercrime describes the act of invading privacy and illegitimately obtaining personal information using digital platform. Primarily an approach named phishing is employed, which involves the use of spoof emails or bogus websites by the attackers to get the victim's personal information like their account credentials, debit, or credit card’s number, etc. To give the brief knowledge of phishing attacks and their types of the objective of this work …
Temporal Climatic Shifts In Henan Province: A 16-Decades Perspective Through Regression, Sarima, And Nar Modeling, Lin Qing, Ang Ling Weay, Shao Yiyang, Sellappan Palaniappan
Temporal Climatic Shifts In Henan Province: A 16-Decades Perspective Through Regression, Sarima, And Nar Modeling, Lin Qing, Ang Ling Weay, Shao Yiyang, Sellappan Palaniappan
Journal of Informatics and Web Engineering
Global warming is having a significant impact on all aspects of human production and life. This study employs a cross-sectional analysis to investigate the temporal dynamics of average temperature changes in Henan Province, China, from 1851 to 2012. Utilizing the Berkeley Earth Surface Temperature Data and the Daily Meteorological Dataset of China National Surface Weather Station v3.0, we applied regression analysis, Seasonal Autoregressive Integrated Moving Average (SARIMA), and Nonlinear Autoregressive Network (NAR) models to predict temperature trends. Results indicate a significant warming trend over the 160-year period, with the models demonstrating strong predictive performance, albeit with some variability. The study …
Social Messaging Application With Translation And Speech-To-Text Transformation, Kang Qin Yip, Pey Yun Goh, Lee Ying Chong
Social Messaging Application With Translation And Speech-To-Text Transformation, Kang Qin Yip, Pey Yun Goh, Lee Ying Chong
Journal of Informatics and Web Engineering
Unlike traditional SMS or MMS, messaging apps offer a broader range of data transmission capabilities. The application utilizes a WIFI or internet connection and enables users to exchange information through various means such as text, voice, and multimedia files. However, popular messaging applications such as WeChat, Telegram, and WhatsApp have limitations in language translation and file uploading size. Thus, this project aims to address these limitations by developing a social messaging application that serves as a comprehensive communication tool. The application will facilitate both written and verbal communication by providing translation services for various languages, including voice messages. The proposed …
Ensemble-Smote: Mitigating Class Imbalance In Graduate On Time Detection, Theng-Jia Law, Choo-Yee Ting, Hu Ng, Hui-Ngo Goh, Albert Quek
Ensemble-Smote: Mitigating Class Imbalance In Graduate On Time Detection, Theng-Jia Law, Choo-Yee Ting, Hu Ng, Hui-Ngo Goh, Albert Quek
Journal of Informatics and Web Engineering
In education, detecting students graduating on time is difficult due to high data complexity. Researchers have employed various approaches in identifying on-time graduation with Machine Learning, but it remains a challenging task due to the class imbalance in the dataset. This study has aimed to (i) compare various class imbalance treatment methods with different sampling ratios, (ii) propose an ensemble class imbalance treatment method in mitigating the problem of class imbalance, and (iii) develop and evaluate predictive models in identifying the likelihood of students graduating on time during their studies in university. The dataset is collected from 4007 graduates of …
Empirical Analysis Of Ci/Cd Tools Usage In Github Actions Workflows, Adam Rafif Faqih, Alif Taufiqurrahman, Jati H. Husen, Mira Kania Sabariah
Empirical Analysis Of Ci/Cd Tools Usage In Github Actions Workflows, Adam Rafif Faqih, Alif Taufiqurrahman, Jati H. Husen, Mira Kania Sabariah
Journal of Informatics and Web Engineering
As software systems grow larger and more complex, with rapidly changing requirements, manually managing code integration, testing, and deployment becomes extremely challenging. Continuous Integration and Continuous Deployment (CI/CD) practices and tools have emerged to help automate these processes. This research explores the usage of different categories of CI/CD tools within GitHub Actions workflow configurations across GitHub repositories. The five-tool categories analyzed are Version Control Management, Static Code Analysis, Build Automation, Test Automation, and CI/CD Servers. The data used in this research is from a dataset of GitHub Actions workflow configuration files. From the data, the usage is extracted and the …
Securing The Inbox: Advancing Cyber Resilience With Fine-Tuned Bert, Fatima Rashed Al Saedi
Securing The Inbox: Advancing Cyber Resilience With Fine-Tuned Bert, Fatima Rashed Al Saedi
Thesis/ Dissertation Defenses
In recent years, phishing attacks have persisted as a widespread threat in the contemporary digital environment, presenting substantial risks to individuals and organizations. Cybercriminals are devising increasingly sophisticated strategies to deceive users through malicious emails. In response to this challenge, this research focuses on developing a new tool for detecting phishing emails utilizing the BERT algorithm. The tool aims to enhance email security by accurately identifying deceptive emails and protecting users from potential cyber threats. The primary objective of this study is to investigate how leveraging the BERT algorithm can improve the detection of phishing emails compared to traditional methods. …
Machine Learning Multimodal Framework For Fake News Detection And Mitigation, Nada A. Gaballah
Machine Learning Multimodal Framework For Fake News Detection And Mitigation, Nada A. Gaballah
Theses and Dissertations
Social media has become our new reality, people wake up every morning and the first thing they do before getting out of bed, is check their social media. Nowadays, people rarely read newspapers, they even rarely watch TV news or listen to radio broadcasts. In recent years, we have witnessed lots of fake news roaming social media every second, with people simply believing it and spreading it even more without checking the credibility of this news. This fake news affected several domains like what happened in the US election in 2016 and again in 2020, the false information about Covid-19 …
Case Studies For Energy Efficient Machine Learning Inference Acceleration, Recep Erol
Case Studies For Energy Efficient Machine Learning Inference Acceleration, Recep Erol
Theses and Dissertations
The advancements in machine learning, deep learning and AI have yielded remarkable tools and innovations, but certain groups face barriers preventing their utilization of these technologies. This research identifies and categorizes these barriers, focusing on three distinct groups: those lacking computational power, seeking to deploy models across multiple devices, and struggling with optimization challenges in high-performance computing centers. The study highlights the disconnect between academia's proposed solutions and their practical integration within industries and research centers, emphasizing the lack of convenience and integration among existing tools. To bridge this gap, this research offers a multifaceted approach. Firstly, it introduces publicly …
The Robot On The Hill, James Ryan
The Robot On The Hill, James Ryan
College of Computing and Digital Media Dissertations
“The Robot on the Hill” is a rogue-like autobattler that procedurally models the state of the individual in the information age. The game abruptly transitions between diverse framings - a hill, a bedroom, a pond, a chessboard, the void - in order to highlight the disjointedness that is present in the informationalizing of self and reality. It dialogues with Byung Chul Han and Heidegger to portray what Han describes as a ‘narrative crisis’ in modernity and the devaluation of experience. When the value of experience diminishes and disintegrates, “all that is left is bare life, a kind of survival.” …
Achieving Domain-Independent Certified Robustness Via Knowledge Continuity, Alan Wenyuan Sun
Achieving Domain-Independent Certified Robustness Via Knowledge Continuity, Alan Wenyuan Sun
Computer Science Senior Theses
We present knowledge continuity, a novel definition inspired by Lipschitz continuity which aims to certify the robustness of neural networks across input domains (such as continuous and discrete domains in vision and language, respectively). Most existing approaches that seek to certify robustness, especially Lipschitz continuity, lie within the continuous domain with norm and distribution-dependent guarantees. In contrast, our proposed definition yields certification guarantees that depend only on the loss function and the intermediate learned metric spaces of the neural network. These bounds are independent of domain modality, norms, and distribution. We further demonstrate that the expressiveness of a model …
Implementing Selective Signature Scanning To Optimize Malware Detection, Lucas Gray Wilbur
Implementing Selective Signature Scanning To Optimize Malware Detection, Lucas Gray Wilbur
Computer Science Senior Theses
Signature scanning is one of the oldest types of malware detection, and it remains an essential lightweight detection method for many antivirus programs. However, signature scanning has unavoidable limitations, including an inevitably increasing runtime as malware signature databases continually expand. In this paper, we discuss the current state of signature scanning, including usage of the open-source signature scanning tool YARA. We test Zemlyanaya et al’s assertion that scanning only the beginning and end of files can reduce the runtime cost of signature database expansion — while maintaining a high level of accuracy — and find it inaccurate in the case …
Evading Antivirus Detection By Abusing File Type Identification, Chavin Udomwongsa
Evading Antivirus Detection By Abusing File Type Identification, Chavin Udomwongsa
Computer Science Senior Theses
File type identification is a vital step in automated file processing, especially in the realm of malware detection. The challenges with file type identification and evasion techniques that take advantage of them were pointed out over a decade ago. We show that this remains the case: file type identification implementations are still fragile, especially for files with ambiguous file types. We present a novel antivirus bypass technique via crafted tar archives that evades all detection from VirusTotal and numerous antiviruses: BitDefender, F-Secure, Kaspersky, Panda Dome, Trend Micro, Quick Heal, IKARUS, Avira. These crafted files evade detection by tricking file type …
Curating Familiarity Within The Unfamiliar: Exploring Non-Native Mobile App Experiences To Create Cross-Cultural Design Frameworks, Hanna Hong
Computer Science Senior Theses
Global mobility and markets are expanding, and as a result, countries are becoming less and less monocultural. With multiple cultural affinity groups to cater towards, companies often will deploy different versions of a website or app based on the country a user is accessing it from. This strategy of catering to geographic location results in a lack of accommodation for people living within a culture that is different from their native one. In order to increase accessibility and equal ease-of-use for all audiences, designers should understand and work towards the needs of a multicultural user base. This study investigates how …
Designing Of Human Serum Albumin Nanoparticles For Drug Delivery: A Potential Use Of Anticancer Treatment, Ali Al-Ani, Rasha Alsahlanee
Designing Of Human Serum Albumin Nanoparticles For Drug Delivery: A Potential Use Of Anticancer Treatment, Ali Al-Ani, Rasha Alsahlanee
Karbala International Journal of Modern Science
Human serum albumin (HSA) nanoparticles have been widely used as versatile drug delivery systems for improving the efficiency and pharmaceutical properties of drugs. The present study aimed to design HSA nanoparticle encapsulated with the hydrophobic anticancer pyridine derivative (2-((2-([1,1'-biphenyl]-4-yl)imidazo[1,2-a]pyrimidin-3-yl)methylene)hydrazine-1-carbothioamide (BIPHC)). The synthesis of HSA-BIPHC nanoparticles was achieved using a desolvation process. Atomic force microscopy (AFM) analysis showed the average size of HSA-BIPHC nanoparticles was 80.21 nm. The percentages of entrapment efficacy, loading capacity and production yield were 98.11%, 9.77% and 91.29%, respectively. An In vitro release study revealed that HSA-BIPHC nanoparticles displayed fast dissolution at pH 7.4 compared to pH …
Modified Toulmin's Argumentation Model Based On Prior Experiences, Ali Hadi Hasan, Mohamad Ab. Saleh, Ahmed T. Sadiq
Modified Toulmin's Argumentation Model Based On Prior Experiences, Ali Hadi Hasan, Mohamad Ab. Saleh, Ahmed T. Sadiq
Karbala International Journal of Modern Science
Our work focuses on the usefulness of previously stored correct extracted results, which form a sort of stored knowledge got from previous experiences, from enhancing Toulmin's argument model that deals with drug conflict problems in therapeutic diagnostics. New patients are entered using friendly user interface to store in files and then they are matched with the records of previous results, patients’ symptoms and histories datasets which also contain the correct best drugs extracted results. If the new entered record of a patient is matching with any previous record then the correct result of drug will be found immediately and displayed. …
Flying Base Station Channel Capacity Limits: Dependent On Stationary Base Station And Independent Of Positioning, Sang-Yoon Chang, Kyungmin Park, Jonghyun Kim, Jinoh Kim
Flying Base Station Channel Capacity Limits: Dependent On Stationary Base Station And Independent Of Positioning, Sang-Yoon Chang, Kyungmin Park, Jonghyun Kim, Jinoh Kim
Faculty Publications
Flying base stations, also known as aerial base stations, provide wireless connectivity to the user and utilize their aerial mobility to improve communication performance. Flying base stations depend on traditional stationary terrestrial base stations for connectivity, as stationary base stations act as the gateway to the backhaul/cloud via a wired connection. We introduce the flying base station channel capacity to build on the Shannon channel capacity, which quantifies the upper-bound limit of the rate at which information can be reliably transmitted using the communication channel regardless of the modulation and coding techniques used. The flying base station’s channel capacity assumes …
Resource-Constrained 2d Scene Recovery With Single-Photon Cameras, Daphne Ariadne Kurzenhauser
Resource-Constrained 2d Scene Recovery With Single-Photon Cameras, Daphne Ariadne Kurzenhauser
Dissertations and Theses
The modern world is built of images. However, in our goal to photograph and replicate what the human eye is capable of seeing, we are throttled by the restrictions of conventional imaging sensors in high- and low-illumination environments. Single-photon cameras (SPCs) have recently emerged as a promising alternative to conventional camera sensors for capturing images in challenging conditions such as high-dynamic range and fast scene motion. Compared to traditional CMOS cameras, SPCs exploit the arrival of individual photons rather than using an aggregate photon count to compute the brightness of pixels. However, SPCs are extremely resource-intensive, making them inconvenient for …
Artificial Intelligence As The Next Front In The Class War, Christopher Hill
Artificial Intelligence As The Next Front In The Class War, Christopher Hill
Dissertations and Theses
For many years, artificial intelligence has been confined to the realm of science fiction, and while the technology has been in development, predicting the effects AI will have on our society has been a challenging endeavor. The release of ChatGPT in 2022, the subsequent mass adoption of the AI chatbot, and the response by other private firms in the field announced AI's permanent entrance into the public sphere. These recent strides made in the field of artificial intelligence reveal that the pace of technological development has outstripped the rate at which we are able to politically examine and understand these …
Cellmarkerpipe: Cell Marker Identification And Evaluation Pipeline In Single Cell Transcriptomes, Yinglu Jia, Pengchong Ma, Qiuming Yao
Cellmarkerpipe: Cell Marker Identification And Evaluation Pipeline In Single Cell Transcriptomes, Yinglu Jia, Pengchong Ma, Qiuming Yao
School of Computing: Faculty Publications
Assessing marker genes from all cell clusters can be time-consuming and lack systematic strategy. Streamlining this process through a unified computational platform that automates identification and benchmarking will greatly enhance efficiency and ensure a fair evaluation. We therefore developed a novel computational platform, cellMarkerPipe (https:// github. com/ yao- labor atory/ cellM arker Pipe), for automated cell-type specific marker gene identification from scRNA-seq data, coupled with comprehensive evaluation schema. CellMarkerPipe adaptively wraps around a collection of commonly used and state-of-the-art tools, including Seurat, COSG, SC3, SCMarker, COMET, and scGeneFit. From rigorously testing across diverse samples, we ascertain SCMarker’s overall reliable performance …
A Meta-Ensemble Predictive Model For The Risk Of Lung Cancer, Sideeqoh Oluwaseun Olawale-Shosanya, Olayinka Olufunmilayo Olusanya, Adeyemi Omotayo Joseph, Kabir Oluwatobi Idowu, Oyelade Babatunde Eriwa, Adedeji Oladimeji Adebare, Morufat Adebola Usman
A Meta-Ensemble Predictive Model For The Risk Of Lung Cancer, Sideeqoh Oluwaseun Olawale-Shosanya, Olayinka Olufunmilayo Olusanya, Adeyemi Omotayo Joseph, Kabir Oluwatobi Idowu, Oyelade Babatunde Eriwa, Adedeji Oladimeji Adebare, Morufat Adebola Usman
Al-Bahir
The lungs play a vital role in supplying oxygen to every cell, filtering air to prevent harmful substances, and supporting defense mechanisms. However, they remain susceptible to the risk of diseases such as infections, inflammation, and cancer that affect the lungs. Meta-ensemble techniques are prominent methods used in machine learning to enhance the accuracy of classifier learning systems in making predictions. This work proposes a robust predictive model using a meta-ensemble method to identify high-risk individuals with lung cancer, thereby taking early action to prevent long-term problems benchmarked upon the Kaggle Machine Learning practitioners' Lung Cancer Dataset. Three machine learning …
Ai's Ethical Frontier
DePaul Magazine
Artificial intelligence (AI) is affecting every aspect of the university and society. Experts from across DePaul share their insights on artificial intelligence's advantages and pitfalls. Learn about DePaul's new Artificial Intelligence Institute and research projects that use AI for societal benefit.
What's In A Social Computing Course: Analyzing Computer And Information Science Syllabi, C. G. Delcourt, Sukrit Venkatagiri, E. Chandrasekharan
What's In A Social Computing Course: Analyzing Computer And Information Science Syllabi, C. G. Delcourt, Sukrit Venkatagiri, E. Chandrasekharan
Computer Science Faculty Works
Social computing systems—such as social media and e-commerce platforms as well as search engines and collaboration software—not only drive vast economic value and societal impact, but are also becoming prominent topics in policy discourse. Although social technology companies heavily recruit students from Computer and Information Science (CS and IS) programs, and social computing is a well-established scholarly field within human-computer interaction (HCI) focused on the social interactions between people mediated through computational systems, little is known about social computing education. Consequently, in this paper we analyzed 25 undergraduate and graduate level courses titled “social computing.” First, as a fast-paced discipline …
Easy-Ai: Semantic And Composable Glyphs For Representing Ai Systems, Alexis Ellis, Brandon Dave, Hugh Salehi, Subhashini Ganapathy, Cogan Shimizu
Easy-Ai: Semantic And Composable Glyphs For Representing Ai Systems, Alexis Ellis, Brandon Dave, Hugh Salehi, Subhashini Ganapathy, Cogan Shimizu
Computer Science and Engineering Faculty Publications
Despite the rapid integration of artificial intelligence (AI) into various research domains and the lives of everyday people, challenges with communicating and understanding these AI systems arise. The lack of a consistent method of communication highlights the need for a transdisciplinary approach to explain the inner workings of AI systems in a cohesive and accessible manner. We thus propose an ontological visual framework using semantically-enhanced, symbols, providing a symbolic language for conveying the structure, purpose, and characteristics of AI systems. The framework encompasses a generalizable glyph set of various AI system components, ensuring both common and obscure architectures can be …