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Articles 1 - 6 of 6
Full-Text Articles in Data Storage Systems
Evaluating Regularized Logistic Regression And K-Nn On Mnist Under Increasing Random Missingness, Daniel Markwei
Evaluating Regularized Logistic Regression And K-Nn On Mnist Under Increasing Random Missingness, Daniel Markwei
Data Science and Data Mining
This paper investigates the effect of random missingness on the performance of regularized multinomial logistic regression and the k-nearest neighbors (k-NN) classifier for handwritten digit recognition on the MNIST dataset. In particular, we study L1-regularized (LASSO) logistic regression and L2-regularized (Ridge) logistic regression alongside k-NN. Varying percentages of random missingness were introduced into the original dataset, and each model was evaluated in terms of its classification performance. The results show that random missingness degrades the performance of all three classifiers. Overall, k-NN consistently achieves higher accuracy than both L1- and L2-regularized logistic regression across all missingness levels; however, its performance …
Restoring Digital Trust: Decentralized Frameworks For Identity, Consent, And Media Provenance, Raghu N. Avula
Restoring Digital Trust: Decentralized Frameworks For Identity, Consent, And Media Provenance, Raghu N. Avula
Graduate Studies Theses and Dissertations 2026
Digital platforms are deeply embedded in modern society through centralized network architectures. As online interactions transition to the physical world handling sensitive data, user privacy and cryptographic security require enhancement beyond traditional limits. This dissertation presents a decentralized “Tri-Layer Trust Architecture” that leverages Verifiable Trust Registries, Cryptographic Binding, and Edge Verification to prioritize data sovereignty and local authentication. To demonstrate the architecture’s applicability across distinct operational environments, we implement three solutions: (1) Verifiable Presence for peer-to-peer ride-sharing via D-RideX, which encrypts biometric data on physical hardware (TEEs) and Soulbound Tokens (SBTs) to prevent impersonation without cloud database exposure; (2) Verifiable …
Minimizing Performance Overheads For Crash-Consistency In Disaggregated Persistent Memory, Khan Shaikhul Hadi
Minimizing Performance Overheads For Crash-Consistency In Disaggregated Persistent Memory, Khan Shaikhul Hadi
Graduate Studies Theses and Dissertations 2026
Compute express link (CXL) enables persistent memory disaggregation with memory pooling and hardware managed multi-host memory sharing capability, resulting in better resource utilization, increased scalability. Persistency-aware applications need to manage crash consistency across the system which results in significant performance overhead. This dissertation systematically investigates performance overhead to achieve crash consistency in disaggregated persistent memory and proposes solutions to enable persistency-aware application scaling for distributed system. First, we study persistent parallel programming to scale computation capability beyond single processor and determine the underlying hardware limitation to adopt lock-free data structure. We propose hardware support to design durable atomic instruction (DAI) …
Micro-Credentialing With Fuzzy Content Matching: An Educational Data-Mining Approach, Paul Amoruso
Micro-Credentialing With Fuzzy Content Matching: An Educational Data-Mining Approach, Paul Amoruso
Electronic Theses and Dissertations, 2020-2023
There is a growing need to assess and issue micro-credentials within STEM curricula. Although one approach is to insert a free-standing academic activity into the students learning and degree path, herein the development and mechanism of an alternative approach rooted in leveraging responses on digitized quiz-based assessments is developed. An online assessment and remediation protocol with accompanying Python-based toolset was developed to engage undergraduate tutors who identify and fill knowledge gaps of at-risk learners. Digitized assessments, personalized tutoring, and automated micro-credentialing scripts for Canvas LMS are used to issue skill-specific badges which motivate the learner incrementally, while increasing self-efficacy. This …
Improving Performance And Flexibility Of Fabric-Attached Memory Systems, Vamsee Reddy Kommareddy
Improving Performance And Flexibility Of Fabric-Attached Memory Systems, Vamsee Reddy Kommareddy
Electronic Theses and Dissertations, 2020-2023
As demands for memory-intensive applications continue to grow, the memory capacity of each computing node is expected to grow at a similar pace. In high-performance computing (HPC) systems, the memory capacity per compute node is decided upon the most demanding application that would likely run on such a system, and hence the average capacity per node in future HPC systems is expected to grow significantly. However, diverse applications run on HPC systems with different memory requirements and memory utilization can fluctuate widely from one application to another. Since memory modules are private for a corresponding computing node, a large percentage …
Robust Acceleration Of Data-Centric Applications Using Resistive Computing Systems, Baogang Zhang
Robust Acceleration Of Data-Centric Applications Using Resistive Computing Systems, Baogang Zhang
Electronic Theses and Dissertations, 2020-2023
With the accessible data reaching zettabyte level, CMOS technology is reaching its limit for the data hungry applications. Moore's law has been reaching its depletion in recent studies. On the other hand, von Neumann architecture is approaching the bottleneck due to the data movement between the computing and memory units. With data movement and power budgets becoming the limiting factors of today's computing systems, in-memory computing using emerging non-volatile resistive devices has attracted an increasing amount of attention. A non-volatile resistive device may be realized using memristor, resistive random access memory (ReRAM), phase change memory (PCM), or spin-transfer torque magnetic …