arXiv subjects

Rashi Sharma

Publications and source records attributed to Rashi Sharma.

6 recordsLinked to original sources

arXiv2026

The Sustainability Paradox of Biodegradable Packaging: A Life Cycle Perspective on Chitosan-Based Food Packaging

Chitosan-based nanomaterials are being increasingly explored as sustainable alternatives to petroleum-derived food packaging, yet their environmental performance across the full life cycle remains insufficiently understood. This review critically evaluates these systems from a life cycle perspective and examines how material origin, processing pathways, functional performance, and end-of-life behavior collectively influence sustainability outcomes. Beginning with chitin extraction from crustacean waste, key processing steps, including demineralization, deproteinization, and nanoparticle synthesis, are assessed in terms of chemical intensity, energy demand, and associated emissions. Manufacturing routes, including solvent-based and green synthesis approaches, are compared with those of conventional plastics to identify relative environmental burdens. The use phase is analyzed with respect to antimicrobial functionality, shelf life extension, and potential reductions in food waste. End-of-life pathways, including biodegradation and composting, are evaluated alongside uncertainties related to degradation behavior and nanoparticle fate. By synthesizing these stagewise interactions, this review highlights critical trade-offs that are often overlooked in sustainability narratives and examines whether chitosan-based nanomaterials provide net environmental benefits in food packaging applications.

physics.soc-ph↗

arXiv2026

Portable Active Learning for Object Detection

Annotating bounding boxes is costly and limits the scalability of object detection. This challenge is compounded by the need to preserve high accuracy while minimizing manual effort in real-world applications. Prior active learning methods often depend on model features or modify detector internals and training schedules, increasing integration overhead. Moreover, they rarely jointly exploit the benefits of image-level signals, class-imbalance cues, and instance-level uncertainty for comprehensive selection. We present Portable Active Learning (PAL), a detector-agnostic, easily portable framework that operates solely on inference outputs. PAL combines class-wise instance uncertainty with image-level diversity to guide data selection. At each round, PAL trains lightweight class-specific logistic classifiers to distinguish true from false positives, producing entropy-based uncertainty scores for proposals. Candidate images are then refined using global image entropy, class diversity, and image similarity, yielding batches that are both informative and diverse. PAL requires no changes to model internals or training pipelines, ensuring broad compatibility across detectors. Extensive experiments on COCO, PASCAL VOC, and BDD100K demonstrate that PAL consistently improves label efficiency and detection accuracy compared to existing active learning baselines, making it a practical solution for scalable and cost-effective deployment of object detection in real-world settings.

cs.CV↗

arXiv2025

2D Addressable Mid-infrared Metasurface Spatial Light Modulator

Active metasurfaces enable dynamic control of light for applications in beam steering, pixelated holography, and adaptive optics, but demonstrations of two-dimensional (2D) electrically addressable arrays have so far been limited. Here we introduce a scalable 2D architecture based on phase-change materials (PCMs) integrated metasurfaces and apply it to realize the first transmissive mid-infrared (mid-IR) spatial light modulator (SLM). The device is fabricated through standard silicon photonic foundry processing combined with backend-of-line (BEOL) integration and employs multilayer backend metal interconnects to implement a crossbar addressing scheme. Each pixel is integrated with a silicon diode selector to suppress sneak-path currents, a feature essential for scaling to large arrays. The result establishes a foundry-compatible route to high-density, large-area active metasurfaces with independently tunable pixels.

physics.optics↗

arXiv2024

Decoding BACnet Packets: A Large Language Model Approach for Packet Interpretation

The Industrial Control System (ICS) environment encompasses a wide range of intricate communication protocols, posing substantial challenges for Security Operations Center (SOC) analysts tasked with monitoring, interpreting, and addressing network activities and security incidents. Conventional monitoring tools and techniques often struggle to provide a clear understanding of the nature and intent of ICS-specific communications. To enhance comprehension, we propose a software solution powered by a Large Language Model (LLM). This solution currently focused on BACnet protocol, processes a packet file data and extracts context by using a mapping database, and contemporary context retrieval methods for Retrieval Augmented Generation (RAG). The processed packet information, combined with the extracted context, serves as input to the LLM, which generates a concise packet file summary for the user. The software delivers a clear, coherent, and easily understandable summary of network activities, enabling SOC analysts to better assess the current state of the control system.

cs.CR↗

arXiv2024

Robust electrothermal switching of optical phase change materials through computer-aided adaptive pulse optimization

Electrically tunable optical devices present diverse functionalities for manipulating electromagnetic waves by leveraging elements capable of reversibly switching between different optical states. This adaptability in adjusting their responses to electromagnetic waves after fabrication is crucial for developing more efficient and compact optical systems for a broad range of applications including sensing, imaging, telecommunications, and data storage. Chalcogenide-based phase change materials (PCMs) have shown great promise due to their stable, non-volatile phase transition between amorphous and crystalline states. Nonetheless, optimizing the switching parameters of PCM devices and maintaining their stable operation over thousands of cycles with minimal variation can be challenging. In this paper, we report on the critical role of PCM pattern as well as electrical pulse form in achieving reliable and stable switching, extending the operational lifetime of the device beyond 13,000 switching events. To achieve this, we have developed a computer-aided algorithm that monitors optical changes in the device and adjusts the applied voltage in accordance with the phase transformation process, thereby significantly enhancing the lifetime of these reconfigurable devices. Our findings reveal that patterned PCM structures show significantly higher endurance compared to blanket PCM thin films.

physics.optics↗

arXiv2023

Updated Trends in Neutrino-induced hadron production

With four different type of neutrino-induced interactions, we considered to investigate and reanalyse the KNO scaling in modified multiplicity distributions from a different perspective. In an attempt of first of its kind, we propose alternate fitting function to parameterise the distribution than the most widely adopted Slattery's function and compare it with yet another form. We propose the shifted Gompertz and Weibull functions as the fitting functions and compare their potency for the most conventional form of Slattery's function. In addition the analysis of the data by evaluating the central moments and factorial moments, we show the dependence of moments on the target size.

hep-ph↗