Tootfinder

OmniNxt: A Fully Open-source and Compact Aerial Robot with Omnidirectional Visual Perception
Peize Liu, Chen Feng, Yang Xu, Yan Ning, Hao Xu, Shaojie Shen
https://arxiv.org/abs/2403.20085

OmniNxt: A Fully Open-source and Compact Aerial Robot with Omnidirectional Visual Perception
Adopting omnidirectional Field of View (FoV) cameras in aerial robots vastly improves perception ability, significantly advancing aerial robotics's capabilities in inspection, reconstruction, and rescue tasks. However, such sensors also elevate system complexity, e.g., hardware design, and corresponding algorithm, which limits researchers from utilizing aerial robots with omnidirectional FoV in their research. To bridge this gap, we propose OmniNxt, a fully open-source aerial robotics platform …

This https://arxiv.org/abs/2402.14872 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCL_…

Semantic Mirror Jailbreak: Genetic Algorithm Based Jailbreak Prompts Against Open-source LLMs
Large Language Models (LLMs), used in creative writing, code generation, and translation, generate text based on input sequences but are vulnerable to jailbreak attacks, where crafted prompts induce harmful outputs. Most jailbreak prompt methods use a combination of jailbreak templates followed by questions to ask to create jailbreak prompts. However, existing jailbreak prompt designs generally suffer from excessive semantic differences, resulting in an inability to resist defenses that use sim…

On the Average Runtime of an Open Source Binomial Random Variate Generation Algorithm
Vincent A. Cicirello
https://arxiv.org/abs/2403.11018 https://…

On the Average Runtime of an Open Source Binomial Random Variate Generation Algorithm
The BTPE algorithm (Binomial, Triangle, Parallelogram, Exponential) of Kachitvichyanukul and Schmeiser is one of the faster and more widely utilized algorithms for generating binomial random variates. Cicirello's open source Java library, $ρμ$, includes an implementation of BTPE as well as a variety of other random number related utilities. In this report, I explore the average case runtime of the BTPE algorithm when generating random values from binomial distribution $B(n,p)$. Beginning with…

Introducing RSESS: An Open Source Enumerative Sphere Shaping Implementation Coded in Rust
Frederik Ritter, Andrej Rode, Laurent Schmalen
https://arxiv.org/abs/2402.08771

Introducing RSESS: An Open Source Enumerative Sphere Shaping Implementation Coded in Rust
In this work, we present an open-source implementation of the enumerative sphere shaping (ESS) algorithm used for probabilistic constellation shaping (PCS). PCS aims at closing the shaping gap caused by using uniformly distributed modulation symbols in channels for which information theory shows non-uniformly distributed signaling to be optimal. ESS is one such PCS algorithm that sets itself apart as it operates on a trellis representation of a subset of the possible symbol sequences. ESS leads…

An Effective Networks Intrusion Detection Approach Based on Hybrid Harris Hawks and Multi-Layer Perceptron
Moutaz Alazab, Ruba Abu Khurma, Pedro A. Castillo, Bilal Abu-Salih, Alejandro Martin, David Camacho
https://arxiv.org/abs/2402.14037 https://arxiv.org/pdf/2402.14037
arXiv:2402.14037v1 Announce Type: new
Abstract: This paper proposes an Intrusion Detection System (IDS) employing the Harris Hawks Optimization algorithm (HHO) to optimize Multilayer Perceptron learning by optimizing bias and weight parameters. HHO-MLP aims to select optimal parameters in its learning process to minimize intrusion detection errors in networks. HHO-MLP has been implemented using EvoloPy NN framework, an open-source Python tool specialized for training MLPs using evolutionary algorithms. For purposes of comparing the HHO model against other evolutionary methodologies currently available, specificity and sensitivity measures, accuracy measures, and mse and rmse measures have been calculated using KDD datasets. Experiments have demonstrated the HHO MLP method is effective at identifying malicious patterns. HHO-MLP has been tested against evolutionary algorithms like Butterfly Optimization Algorithm (BOA), Grasshopper Optimization Algorithms (GOA), and Black Widow Optimizations (BOW), with validation by Random Forest (RF), XG-Boost. HHO-MLP showed superior performance by attaining top scores with accuracy rate of 93.17%, sensitivity level of 89.25%, and specificity percentage of 95.41%.

This https://arxiv.org/abs/1808.01590 has been replaced.
link: https://scholar.google.com/scholar?q=a

$\texttt{Spglib}$: a software library for crystal symmetry search
A computer algorithm to search symmetries of crystal structures as implemented in the \texttt{spglib} code is described. An iterative algorithm is employed to robustly identify space group types tolerating a certain amount of distortion in the crystal structures. The source code is distributed under the 3-Clause BSD License, a permissive open-source software license. This paper focuses on the algorithm for identifying the space group symmetry of the crystal structures.

Verified Multi-Step Synthesis using Large Language Models and Monte Carlo Tree Search
David Brandfonbrener, Sibi Raja, Tarun Prasad, Chloe Loughridge, Jianang Yang, Simon Henniger, William E. Byrd, Robert Zinkov, Nada Amin
https://arxiv.org/abs/2402.08147

Verified Multi-Step Synthesis using Large Language Models and Monte Carlo Tree Search
We present an approach using Monte Carlo Tree Search (MCTS) to guide Large Language Models (LLMs) to generate verified programs in Dafny, Lean and Coq. Our method, which we call VMCTS, leverages the verifier inside the search algorithm by checking partial programs at each step. In combination with the LLM prior, the verifier feedback raises the synthesis capabilities of open source models. On a set of five verified programming problems, we find that in four problems where the base model cannot …

An Effective Networks Intrusion Detection Approach Based on Hybrid Harris Hawks and Multi-Layer Perceptron
Moutaz Alazab, Ruba Abu Khurma, Pedro A. Castillo, Bilal Abu-Salih, Alejandro Martin, David Camacho
https://arxiv.org/abs/2402.14037 https://arxiv.org/pdf/2402.14037
arXiv:2402.14037v1 Announce Type: new
Abstract: This paper proposes an Intrusion Detection System (IDS) employing the Harris Hawks Optimization algorithm (HHO) to optimize Multilayer Perceptron learning by optimizing bias and weight parameters. HHO-MLP aims to select optimal parameters in its learning process to minimize intrusion detection errors in networks. HHO-MLP has been implemented using EvoloPy NN framework, an open-source Python tool specialized for training MLPs using evolutionary algorithms. For purposes of comparing the HHO model against other evolutionary methodologies currently available, specificity and sensitivity measures, accuracy measures, and mse and rmse measures have been calculated using KDD datasets. Experiments have demonstrated the HHO MLP method is effective at identifying malicious patterns. HHO-MLP has been tested against evolutionary algorithms like Butterfly Optimization Algorithm (BOA), Grasshopper Optimization Algorithms (GOA), and Black Widow Optimizations (BOW), with validation by Random Forest (RF), XG-Boost. HHO-MLP showed superior performance by attaining top scores with accuracy rate of 93.17%, sensitivity level of 89.25%, and specificity percentage of 95.41%.

This https://arxiv.org/abs/2108.13754 has been replaced.
link: https://scholar.google.com/scholar?q=a

MRI lung lobe segmentation in pediatric cystic fibrosis patients using a recurrent neural network trained with publicly accessible CT datasets
Purpose: To introduce a widely applicable workflow for pulmonary lobe segmentation of MR images using a recurrent neural network (RNN) trained with chest computed tomography (CT) datasets. The feasibility is demonstrated for 2D coronal ultra-fast balanced steady-state free precession (ufSSFP) MRI. Methods: Lung lobes of 250 publicly accessible CT datasets of adults were segmented with an open-source CT-specific algorithm. To match 2D ufSSFP MRI data of pediatric patients, both CT data and seg…

This https://arxiv.org/abs/2401.08772 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCL_…

HuixiangDou: Overcoming Group Chat Scenarios with LLM-based Technical Assistance
In this work, we present HuixiangDou, a technical assistant powered by Large Language Models (LLM). This system is designed to assist algorithm developers by providing insightful responses to questions related to open-source algorithm projects, such as computer vision and deep learning projects from OpenMMLab. We further explore the integration of this assistant into the group chats of instant messaging (IM) tools such as WeChat and Lark. Through several iterative improvements and trials, we ha…

This https://arxiv.org/abs/2304.06935 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csMS_…

Groebner.jl: A package for Gröbner bases computations in Julia
We present Groebner.jl, a Julia package for computing Groebner bases with the F4 algorithm. Groebner.jl is an efficient, portable, and open-source software. Groebner.jl works over integers modulo a prime and over the rationals, supports basic multi-threading, and specializes in computation in the degree reverse lexicographical monomial ordering. The implementation incorporates various symbolic computation techniques and leverages the Julia type system and tooling, which allows Groebner.jl to co…

This https://arxiv.org/abs/2307.05816 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Implicit Adaptive Mesh Refinement for Dispersive Tsunami Propagation
We present an algorithm to solve the dispersive depth-averaged Serre-Green-Naghdi (SGN) equations using patch-based adaptive mesh refinement. These equations require adding additional higher derivative terms to the nonlinear shallow water equations. This has been implemented as a new component of the open source GeoClaw software that is widely used for modeling tsunamis, storm surge, and related hazards, improving its accuracy on shorter wavelength phenomena. We use a formulation that requires …

MLatom software ecosystem for surface hopping dynamics in Python with quantum mechanical and machine learning methods
Lina Zhang, Sebastian V. Pios, Miko{\l}aj Martyka, Fuchun Ge, Yi-Fan Hou, Yuxinxin Chen, Lipeng Chen, Joanna Jankowska, Mario Barbatti, Pavlo O. Dral
https://arxiv.org/abs/2404.06189

MLatom software ecosystem for surface hopping dynamics in Python with quantum mechanical and machine learning methods
We present an open-source MLatom@XACS software ecosystem for on-the-fly surface hopping nonadiabatic dynamics based on the Landau-Zener-Belyaev-Lebedev (LZBL) algorithm. The dynamics can be performed via Python API with a wide range of quantum mechanical (QM) and machine learning (ML) methods, including ab initio QM (CASSCF and ADC(2)), semi-empirical QM methods (e.g., AM1, PM3, OMx, and ODMx), and many types of machine learning potentials (e.g., KREG, ANI, and MACE). Combinations of QM and ML …