Mrinank Sharma

Bipolar fuzzy rough aggregation operator hybrid with TOPSIS and their application in group decision-making

Bipolar fuzzy rough aggregation operator hybrid with TOPSIS and their application in group decision-making — Citations: 0.

LLM-Driven Design Space Exploration of FPGA-based Accelerators

TREA: Low-precision Time-Multiplexed, Resource-Efficient Edge Accelerator for Object Detection and Classification

$C\!P$ violation analysis of local and nonlocal amplitudes in the $\overline{B}^0 \to \overline{K}^{*0}μ^+μ^-$ decay

Evidence for the decay $B^0_s\toφη'$

Active Control of Topological Exceptional Points in Non-Hermitian Metasurfaces

Towards Safeguarding LLM Fine-tuning APIs against Cipher Attacks

Chain-of-Thought Hijacking

Eliciting Harmful Capabilities by Fine-Tuning On Safeguarded Outputs

Who's in Charge? Disempowerment Patterns in Real-World LLM Usage

An Efficient Deep Learning Framework for Real-Time Gender Classification from Facial Images

An Efficient Deep Learning Framework for Real-Time Gender Classification from Facial Images — This paper presents an efficient deep learning framework for real-time gender classification from facial images. The proposed system uses the MobileNetV3-Small architecture, selected for its favorable accuracy–latency trade-off and optimized to minimize computational cost while maintaining high predictive performance. Implemented within the PyTorch/torchvision ecosystem, the framework incorporates a deterministic preprocessing pipeline and consistent transformations across training, validation, — Citations: 0.

Advanced multi-virus genome sequence classification using artificial intelligence techniques

Advanced multi-virus genome sequence classification using artificial intelligence techniques — The rapid transmission and mutation rates of viruses necessitate efficient and precise classification methods to aid public health responses. Often constrained by culturing requirements and narrow taxonomic scopes, traditional diagnostic techniques struggle to keep pace with the rapidly expanding genomic landscape. This study introduces an advanced multi-virus genome sequence classification approach utilizing a k-mer-based dictionary for rapid genomic pattern extraction, enhanced by sophisticate — Citations: 0.

Mocoa-fs: a multi-objective feature selection approach for genetic cancer classification using microarray data

Mocoa-fs: a multi-objective feature selection approach for genetic cancer classification using microarray data — Citations: 0.

Improving Feature Selection for Infant Mortality Risk Assessment via Binary Multi-Objective Cheetah Optimization

Improving Feature Selection for Infant Mortality Risk Assessment via Binary Multi-Objective Cheetah Optimization — Infant mortality is a pivotal indicator of community health and socioeconomic conditions. Despite global advancements in healthcare and significant reductions in infant mortality rates, substantial disparities persist, particularly in underserved populations. This research aims to tackle these disparities by enhancing the predictive accuracy of public health interventions. We utilize advanced feature selection techniques to identify critical predictors of infant survival, thereby supporting — Citations: 0.

ALIGN: An AI-Driven IoT Framework for Real-Time Sitting Posture Detection

ALIGN: An AI-Driven IoT Framework for Real-Time Sitting Posture Detection — Posture, defined as the body’s alignment relative to gravity, plays a vital role in musculoskeletal health by influencing muscle efficiency, joint integrity, and overall balance. The global shift to remote and sedentary work environments during the COVID-19 pandemic has amplified concerns regarding posture-related disorders and long-term ergonomic risks. This study introduces ALIGN, an IoT-enabled intelligent system for real-time sitting posture detection that integrates both machine learning an — Citations: 0.