Advancing Frontiers of Path Integral Theory for Stochastic Optimal Control
Stochastic Optimal Control (SOC) problems arise in systems influenced by uncertainty, such as autonomous robots or financial models. Traditional methods like dynamic programming are often intractable for high-dimensional, nonlinear systems due to the curse of dimensionality. This dissertation explores the path integral...
A Comprehensive Review on RNA Subcellular Localization Prediction
The subcellular localization of RNAs, including long non-coding RNAs (lncRNAs), messenger RNAs (mRNAs), microRNAs (miRNAs) and other smaller RNAs, plays a critical role in determining their biological functions. For instance, lncRNAs are predominantly associated with chromatin and act as regulators of gene...
PhysioSync: Temporal and Cross-Modal Contrastive Learning Inspired by Physiological Synchronization for EEG-Based Emotion Recognition
Electroencephalography (EEG) signals provide a promising and involuntary reflection of brain activity related to emotional states, offering significant advantages over behavioral cues like facial expressions. Tuttavia, EEG signals are often noisy, affected by artifacts, and vary across individuals, complicating emotion recognition. While...
The critical power of short pulse initial data on the global existence or blowup of smooth solutions to 3-D semilinear Klein-Gordon equations
It is well-known that there are global small data smooth solutions for the 3-D semilinear Klein-Gordon equations $\square u + u = F(u,{\partial u})$ with cubic nonlinearities. Tuttavia, for the short pulse initial data $(u, \partial_tu)(0, x)=({\delta^{\nu+1}}{u_0}({\frac{x}{\delta}}),{\delta^\nu }{u_1}({\frac{x}{\delta}}))$ with $\nu\in\Bbb R$ and...
Augmenting Captions with Emotional Cues: An AR Interface for Real-Time Accessible Communication
This paper introduces an augmented reality (AR) captioning framework designed to support Deaf and Hard of Hearing (DHH) learners in STEM classrooms by integrating non-verbal emotional cues into live transcriptions. Unlike conventional captioning systems that offer only plain text, our system fuses...
Asymptotics of Yule’s nonsense correlation for Ornstein-Uhlenbeck paths: The correlated case
We study the continuous-time version of the empirical correlation coefficient between the paths of two possibly correlated Ornstein-Uhlenbeck processes, known as Yule’s nonsense correlation for these paths. Using sharp tools from the analysis on Wiener chaos, we establish the asymptotic normality of...
Approximating fluid queues with quasi birth-and-death processes with rational arrival process components
A fluid queue is a stochastic process which moves linearly with a rate that is determined by the state of a continuous-time Markov chain (CTMC). In this paper we construct an approximation to a fluid queue using a quasi birth-and-death process with...
How to Grow an LSM-tree? Towards Bridging the Gap Between Theory and Practice
LSM-tree based key-value stores are widely adopted as the data storage backend in modern big data applications. The LSM-tree grows with data ingestion, by either adding levels with fixed level capacities (dubbed as vertical scheme) or increasing level capacities with fixed number...
Evaluating Learned Query Performance Prediction Models at LinkedIn: Challenges, Opportunities, and Findings
Recent advancements in learning-based query performance prediction models have demonstrated remarkable efficacy. Tuttavia, these models are predominantly validated using synthetic datasets focused on cardinality or latency estimations. This paper explores the application of these models to LinkedIn’s complex real-world OLAP queries executed...
DualAttWaveNet: Multiscale Attention Networks for Satellite Interference Detection
The escalating overlap between non-geostationary orbit (NGSO) and geostationary orbit (GSO) satellite frequency allocations necessitates accurate interference detection methods that address two pivotal technical gaps: computationally efficient signal analysis for real-time operation, and robust anomaly discrimination under varying interference patterns. Existing deep...