All posts under category "Research"
Software developers share programming solutions in Q&A sites like Stack Overflow. The reuse of crowd-sourced code snippets can facilitate rapid prototyping. However, recent research shows that the shared code snippets may be of low quality and can ev
The observations of Mars by the CRISM and OMEGA hyperspectral imaging spectrometers require correction for photometric, atmospheric and thermal effects prior to the interpretation of possible mineralogical features in the spectra. Here, we report on
In this paper, a novel data hiding technique is proposed, as an improvement over the Fibonacci LSB data-hiding technique proposed by Battisti et al,based on decomposition of a number (pixel-value) in sum of natural numbers. This particular representa
The pulse profiles of the transient Be/X-ray binary EXO 2030+375 show strong dependence on energy, as well as on its luminosity state, and are asymmetric in shape. We want to identify the emission components of the two magnetic poles in the pulsed em
Enterprises are always on the lookout for tools that analyze end-users perspectives on their products. In particular, app reviews have been assessed as useful for guiding improvement efforts and software evolution, however, developers find reading ap
Several different measures for digraph width have appeared in the last few years. However, none of them shares all the 'nice' properties of treewidth: First, being emph{algorithmically useful} i.e. admitting polynomial-time algorithms for all MS1 -d
BRICKxAR is a novel Augmented Reality (AR) instruction method for construction toys such as LEGO. With BRICKxAR, physical LEGO construction is guided by virtual bricks. Compared with the state-of-the-art, accuracy of the virtual - physical model alig
We propose a method for automatically generating abstract transformers for static analysis by abstract interpretation. The method focuses on linear constraints on programs operating on rational, real or floating-point variables and containing linear
We introduce a robust, error-tolerant adaptive training algorithm for generalized learning paradigms in high-dimensional superposed quantum networks, or emph{adaptive quantum networks}. The formalized procedure applies standard backpropagation traini
Rigorous evaluation of large language models (LLMs) relies on comparing models by the prevalence of desirable or undesirable behaviors, such as task pass rates or policy violations. These prevalence estimates are produced by a classifier, either an L
Message passing type algorithms such as the so-called Belief Propagation algorithm have recently gained a lot of attention in the statistics, signal processing and machine learning communities as attractive algorithms for solving a variety of optimiz
Currently, over forty transiting planets have been discovered by ground-based photometric surveys, and space-based missions like Kepler and CoRoT are expected to detect hundreds more. Follow-up photometric observations from the ground will play an im
We propose a training-free, binary verification workflow for zero-shot vision with off-the-shelf VLMs. It comprises two steps: (i) quantization, which turns the open-ended query into a multiple-choice question (MCQ) with a small, explicit list of una
Multiple carrier-frequency offsets (CFO) arise in a distributed antenna system, where data are transmitted simultaneously from multiple antennas. In such systems the received signal contains multiple CFOs due to mismatch between the local oscillators
Social bots are now deeply embedded in online platforms for promotion, persuasion, and manipulation. Most bot-detection systems still treat behavioural features as static, implicitly assuming bots behave stationarily over time. We test that assumptio
The fully automated and relatively accurate method of brain tissues segmentation on T2-weighted magnetic resonance perfusion images is proposed. Segmentation with this method provides a possibility to obtain perfusion region of interest on images wit
Fig. 1. Top: B-rep models generated by BrepGPT. Bottom: Visualization of corresponding Voronoi Half-Patches, where distinct colors represent regions in the parametric space of each face that are geometrically closest to their respective boundary curv
As LLM-based judges become integral to industry applications, obtaining well-calibrated uncertainty estimates efficiently has become critical for production deployment. However, existing techniques, such as verbalized confidence and multi-generation
Chain-of-thought (CoT) prompting has become central to mathematical reasoning in large language models, yet models remain brittle to early errors: a single arithmetic slip or unjustified inference typically propagates uncorrected to an incorrect fina
Catastrophic forgetting is a longstanding challenge in continual learning, where models lose knowledge from earlier tasks when learning new ones. While various mitigation strategies have been proposed for Multi-Layer Perceptrons (MLPs), recent archit
We propose a communication-bound-aware cross-domain resource assignment framework for pipeline-parallel distributed training over multi-datacenter optical networks, which lowers iteration time by 31.25% and reduces 13.20% blocking requests compared t
Following a short report of our preliminary results [Phys. Rev. E 79, 055203(R) (2009)], we present a more detailed study of the effects of coupling delay in diffusively coupled phase oscillator populations. We find that coupling delay induces chimer
We present Classical BI (CBI), a new addition to the family of bunched logics which originates in O'Hearn and Pym's logic of bunched implications BI. CBI differs from existing bunched logics in that its multiplicative connectives behave classically r
Several overlay-based live multimedia streaming platforms have been proposed in the recent peer-to-peer streaming literature. In most of the cases, the overlay neighbors are chosen randomly for robustness of the overlay. However, this causes nodes th
Graphical User Interface (GUI) task automation constitutes a critical frontier in artificial intelligence research. While effective GUI agents synergistically integrate planning and grounding capabilities, current methodologies exhibit two fundamenta
Large language models show promise for embodying historical characters in dialogue systems, but existing approaches face a critical trade-off: simple retrieval-augmented generation produces shallow responses, while multi-stage reflection achieves dep
Lower limb amputees often suffer skin and tissue problems from using their prosthesis which is a challenging biomechanical problem. The finite element method (FEM) has previously been applied to analyse internal mechanical conditions of the leg at pr
We provide an empirical investigation aimed at uncovering the statistical properties of intricate stock trading networks based on the order flow data of a highly liquid stock (Shenzhen Development Bank) listed on Shenzhen Stock Exchange during the wh
Explainable Artificial Intelligence (XAI) has become an increasingly important area of research, particularly as machine learning models are deployed in high-stakes domains. Among various XAI approaches, SHAP (SHapley Additive exPlanations) has gaine
We examine the effective counterion-mediated electrostatic interaction between two like-charged dielectric cylinders immersed in a continuous dielectric medium containing neutralizing mobile counterions. We focus on the effects of image charges induc
Large Language Models and multi-agent systems have shown promise in decomposing complex tasks, yet they struggle with long-horizon reasoning tasks and escalating computation cost. This work introduces a hierarchical multi-agent architecture that dist
Several works in the last few years devoted to measure fundamental probes of contemporary cosmology have suggested the existence of a delocalized dominant component (the 'dark energy'), in addition to the several-decade-old evidence for 'dark matter'
Network weights can be reverse-engineered given enough informative samples of a network's input-output function. In a teacher-student setup, this translates into collecting a dataset of the teacher mapping -querying the teacher -and fitting a student
This chapter seeks to frame the elemental and invisible problems of AI and big data in the African context by examining digital sites and infrastructure through the lens of power and interests. It will present reflections on how these sites are using
Data governance ensures data quality, security, and compliance through policies and standards, a critical foundation for scaling modern AI development. Recently, large language models (LLMs) have emerged as a promising solution for automating data go
We present a unique system for large-scale, multi-performer, high resolution 4D volumetric capture providing realistic free-viewpoint video up to and including 4K resolution facial closeups. To achieve this, we employ a novel volumetric capture, reco
XTE J1818-245 is an X-ray nova that experienced an outburst in 2005, first seen by the RXTE satellite. The source was observed simultaneously at various wavelengths up to soft gamma-rays with the INTEGRAL satellite, from 2005 February to September. X
We analyzed the frequency domain of time series of simulated ZZ Ceti light-curves to investigate the detectability and period recovery performance of short period variables (periods < 2 hours) for the Gaia mission. In our analysis, first we used a no
Using an AI assistant, we developed a method for systematically constructing controlled natural language for requirements based on formal specification patterns containing logical attributes. The method involves three stages: 1) compiling a generaliz
This paper proposes a competitive and computationally efficient approach to probabilistic rainfall nowcasting. A video projector (V-JEPA Vision Transformer) associated to a lightweight probabilistic head is attached to a pre-trained satellite vision
Diffusion Language Models (dLLMs) have emerged as promising alternatives to Auto-Regressive (AR) models. While recent efforts have validated their pre-training potential and accelerated inference speeds, the post-training landscape for dLLMs remains
Black-box AI (BBAI) systems such as foundational models are increasingly being used for sequential decision making. To ensure that such systems are safe to operate and deploy, it is imperative to develop efficient methods that can provide a sound and
We study possible correlations between ultrahigh energy cosmic rays (UHECRs), observed by Auger, AGASA and Yakutsk, and nearby active galactic nuclei (AGNs) and Fermi sources. We consider the deflection effects by a Galactic magnetic field (GMF) mo
Here we show a photonic design for tunable dual-wavelength generation deploying optical nonlinear mode coupling of two coupled III-V semiconductor microring resonators (MRRs) connected to a pump and drop waveguide buses. Here one of the two rings con
Let G be a finite group and Y a G -gerbe over an orbifold B . A disconnected orbifold hat{Y} and a flat U(1)-gerbe c on hat{Y} is canonically constructed from Y . Motivated by a proposal in physics, we study a mathematical duality betwee
We investigate the slow time scales that arise from aging of the paths during the process of path aggregation. This is studied using Monte-Carlo simulations of a model aiming to describe the formation of fascicles of axons mediated by contact axon-ax
Molecular-dynamics algorithms for systems of particles interacting through discrete or 'hard' potentials are fundamentally different to the methods for continuous or 'soft' potential systems. Although many software packages have been developed for co
This paper investigates the inelastic response of a yielding structure coupled with a rocking wall which can be vertically restrained. The paper first derives the nonlinear equations of motion of a yielding oscillator coupled with a vertically restra
Hierarchical Matrix (H-matrix) is an approximation technique which splits a target dense matrix into multiple submatrices, and where a selected portion of submatrices are low-rank approximated. The technique substantially reduces both time and space
The pivot algorithm for self-avoiding walks has been implemented in a manner which is dramatically faster than previous implementations, enabling extremely long walks to be efficiently simulated. We explicitly describe the data structures and algorit
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