Related papers: Software infrastructure for the highly-distributed…

Traditional Digital Signal Processing ( DSP ) compilers work at low level ( C-level / assembly level ) and hence lose much of the optimization opportunities present at high-level ( domain-level ). The emerging multi-level compiler…

In this paper, the performance of high speed optical fiber based network is analysed by using dispersion compensating module (DCM). The optimal operating condition of the DCM is obtained by considering dispersion management configurations…

Machine Learning (ML) and Deep Learning (DL) innovations are being introduced at such a rapid pace that researchers are hard-pressed to analyze and study them. The complicated procedures for evaluating innovations, along with the lack of…

This paper studies a deep learning (DL) framework for the design of binary modulated visible light communication (VLC) transceiver with universal dimming support. The dimming control for the optical binary signal boils down to a…

Distributed tensor decomposition (DTD) is a fundamental data-analytics technique that extracts latent important properties from high-dimensional multi-attribute datasets distributed over edge devices. Conventionally its wireless…

The Physics and Data Quality Monitoring (DQM) framework aims at providing a homogeneous monitoring environment across various applications related to data taking at the CMS experiment. In this contribution, the DQM system for the Silicon…

We present the Distributed and Localized Model Predictive Control (DLMPC) algorithm for large-scale structured linear systems, wherein only local state and model information needs to be exchanged between subsystems for the computation and…

Light curves serve as a valuable source of information on stellar formation and evolution. With the rapid advancement of machine learning techniques, it can be effectively processed to extract astronomical patterns and information. In this…

Cooperative Simultaneous Localization and Mapping (C-SLAM) enables multiple agents to work together in mapping unknown environments while simultaneously estimating their own positions. This approach enhances robustness, scalability, and…

This paper presents Direct LiDAR-Inertial Odometry and Mapping (DLIOM), a robust SLAM algorithm with an explicit focus on computational efficiency, operational reliability, and real-world efficacy. DLIOM contains several key algorithmic…

We present DCOOL-NET, a scalable distributed in-network algorithm for sensor network localization based on noisy range measurements. DCOOL-NET operates by parallel, collaborative message passing between single-hop neighbor sensors, and…

In this paper, we propose a workflow that uses Terrestrial Laser Scanning(TLS) to semi-automatically monitor landslide and then test it in practice. Firstly, several groups of TLS stations are set on different time to collect the raw point…

The rapid escalation in the parameter count of large language models (LLMs) has transformed model training from a single-node endeavor into a highly intricate, cross-node activity. While frameworks such as Megatron-LM successfully integrate…

Security engineering, from security requirements engineering to the implementation of cryptographic protocols, is often supported by domain-specific languages (DSLs). Unfortunately, a lack of knowledge about these DSLs, such as which…

The Visual Simultaneous Localization and Mapping (V-SLAM) system has seen significant development in recent years, demonstrating high precision in environments with limited dynamic objects. However, their performance significantly…

The emerging Software Defined Networking (SDN) paradigm separates the data plane from the control plane and centralizes network control in an SDN controller. Applications interact with controllers to implement network services, such as…

Sentinel-5P (S5P) satellite provides atmospheric measurements for air quality and climate monitoring. While the S5P satellite offers rich spectral resolution, it inherits physical limitations that restricts its spatial resolution.…

Modern distributed data processing systems struggle to balance performance, maintainability, and developer productivity when integrating machine learning at scale. These challenges intensify in large collaborative environments due to high…

This paper gives an overview of Software Defined Optical Networks or SDONs and how they can be implemented. It traces the evolution of Optical networks upto GMPLS and traces the idea of SDN and builds upto OpenFlow. The paper explores the…

DBSP_DRP is a python package that provides fully automated data reduction of data taken by the Double Spectrograph (DBSP) at the 200-inch Hale Telescope at Palomar Observatory (Oke & Gunn, 1982). The underlying data reduction functionality…