A global object-oriented dynamic network for low-altitude remote sensing object detection by Daoze Tang, Shuyun Tang, Yalin Wang, Shaoyun Guan, Yining Jin

“…This study introduces the Global Object-Oriented Dynamic Network (GOOD-Net) algorithm, comprising three fundamental components: an object-oriented, dynamically adaptive backbone network; a neck network designed to optimize the utilization of global information; and a task-specific processing head augmented for detailed feature refinement. …”
Get full text

A seismic random noise suppression method based on CNN-Mamba by Xiujuan WEI, Xingye LIU, Huailai ZHOU

“…The hardware-aware parallel algorithm of Mamba was employed to reduce the computational resource consumption, thus ensuring the denoising performance while enhancing computational efficiency. …”
Get full text

IoT intrusion detection method for unbalanced samples by ANTONG P, Wen CHEN, Lifa WU

“…In recent years, network traffic increases exponentially with the iteration of devices, while more and more attacks are launched against various applications.It is significant to identify and classify attacks at the traffic level.At the same time, with the explosion of Internet of Things (IoT) devices in recent years, attacks on IoT devices are also increasing, causing more and more damages.IoT intrusion detection is able to distinguish attack traffic from such a large volume of traffic, secure IoT devices at the traffic level, and stop the attack activity.In view of low detection accuracy of various attacks and sample imbalance at present, a random forest based intrusion detection method (Resample-RF) was proposed, which consisted of three specific methods: optimal sample selection algorithm, feature merging algorithm based on information entropy, and multi-classification greedy transformation algorithm.Aiming at the problem of unbalanced samples in the IoT environment, an optimal sample selection algorithm was proposed to increase the weight of small samples.Aiming at the low efficiency problem of random forest feature splitting, a feature merging method based on information entropy was proposed to improve the running efficiency.Aiming at the low accuracy problem of random forest multi-classification, a multi-classification greedy transformation method was proposed to further improve the accuracy.The method was evaluated on two public datasets.F1 reaches 0.99 on IoT-23 dataset and 1.0 on Kaggle dataset, both of which have good performance.The experimental results show that the proposed model can effectively identify the attack traffic from the massive traffic, better prevent the attack of hackers on the application, protect the IoT devices, and thus protect the related users.…”
Get full text

Efficient multiplication for finite fields of p characteristic by LI Yin 1, CHEN Gong-liang1, LI Jian-hua1

“…Based on residue arithmetic,a new form of polynomial named PAPB in Fp[x] had been constructed.The amount and distribution of such irreducible polynomials had also been investigated.Then,an efficient algorithm for multiplication modulo PAPB had been proposed using residue arithmetic and Chinese remainder theorem.In the end,the result analysis was given.The theoretic analysis and simulation experiment show that for some finite field of medium prime characteristic,the given algorithm only costs O（k1.5） operations in Fp while the multiplication modulo irreducible binomial cost O（k2） operations,which shows a better performance.As a result,the work presents an interesting perspective for optimal extension field and elliptic curve cryptography.…”
Get full text

Analysis of Two-Grid Characteristic Finite Element Methods for Convection-Diffusion Equations by Keyan Wang, Boxia Hu

“…We present an optimal error estimate in Lp-norm for the characteristic finite element method unconditionally, while all previous works require certain time-step restrictions. …”
Get full text

Analysis of Blockchain-Technology by Danylo Dvorchuk, Iryna Shpinareva

“…The study explores the comparative advantages and limitations of different blockchain architectures and evaluates emerging optimization techniques such as hybrid consensus algorithms and artificial intelligence-based enhancements. …”
Get full text

Turning Energy-Aware Route Planning With an Extended TSP and Double-Layer State Graph: Experimental Evaluation With a Crawler Mobile Robot by Namihei Adachi, Hisashi Date

“…The routes that minimized energy consumption showed an average 17 % reduction in energy consumption, while the routes that minimized travel time achieved an average 5 % reduction in travel time compared to the standard TSP algorithm.…”
Get full text

Research on Unmanned Aerial Vehicle Path Planning for Carbon Emission Monitoring of Land-Side Heavy Vehicles in Ports by Xincong Wu, Zhanzhu Li, Xiaohua Cao

“…In the simulation experiment results, the proposed algorithm outperforms A*, ACO, and IEA algorithms in optimizing path length, reducing collision points to ensure path safety, and robustness. …”
Get full text

Differentiable architecture search-based automatic modulation recognition for multi-carrier signals by LI Jie, LI Jing, LYU Lu, GONG Fengkui

“…Simulation results demonstrate that the proposed algorithm improves accuracy in urban multipath channels, especially at low SNR, while simultaneously providing better robustness to modulation parameter variations and small-sample scenarios.…”
Get full text

Retrieval of water quality parameters based on IOA-ML models and their response to short-term hydrometeorological factors by Wentong Hu, Donghao Miao, Chi Zhang, Zixian He, Wenquan Gu, Dongguo Shao

“…The best IOA-ML model for total phosphorus (TP), total nitrogen (TN), and permanganate index (CODMn) was extreme gradient boosting optimized by genetic algorithm (GA-XGB), while that for dissolved oxygen (DO) and turbidity was categorical boosting regression optimized by GA (GA-CBR). …”
Get full text

Artificial Intelligence-Based Techniques for Fouling Resistance Estimation of Shell and Tube Heat Exchanger: Cascaded Forward and Recurrent Models by Ikram Kouidri, Abdennasser Dahmani, Furizal Furizal, Alfian Ma’arif, Ahmed A. Mostfa, Abdeltif Amrane, Lotfi Mouni, Abdel-Nasser Sharkawy

“…The training process is optimized using the Levenberg–Marquardt (LM) algorithm, ensuring rapid convergence and high accuracy. …”
Get full text

A real-time 3D modeling method for buildings driven by IMU and RGB-D fusion by Yuhan Gao, Chao Dang, Jun Zhu, Yakun Xie, Ya Hu, Chunli Yan, Kun Yi, Chuan Yi, Xue Li

“…The method incorporates an adaptive sampling strategy for RGB-D cameras based on IMU data calibration, introduces a pose estimation optimization algorithm that combines dynamic feature point cluster centroid prediction with bias detection, establishes a progressive 3D modeling approach constrained by structural features, and develops a prototype system for in-depth case study analysis. …”
Get full text

Machine learning enables legal risk assessment in internet healthcare using HIPAA data by Shixian Liu, Hailing Liu, Siyu Fan, Leming Song, Zeyu Wang

“…Each algorithm has its strengths and limitations depending on the specific legal risk assessment task. …”
Get full text

Modify a dual ridge horn antenna for drone jamming applications by Alaa Hussein Hilal, Ahmed Hameed Reja, Mohammed J. Mohammed

“…This work presents a DRHA developed utilizing CST Studio and optimized by using genetic algorithm optimization (GA) that has been employed to improve parameters that enhance selected frequencies. …”
Get full text

A Robust Game Approach for On Spot Price Cloud Markets in Microservice-Based Applications by Hamta Sedghani, Mauro Passacantando, Riccardo Lancellotti, Mina Zolfy Lighvan, Danilo Ardagna

“…Furthermore, we propose a best-reply algorithm to identify a robust GNE, ensuring that the solution remains feasible even under the worst-case scenarios of uncertain parameters. …”
Get full text

Huffman coding-based data reduction and quadristego logic for secure image steganography by Irsyad Fikriansyah Ramadhan, Ntivuguruzwa Jean De La Croix, Tohari Ahmad, Andre Uzamurengera

“…To address these challenges, this study proposes a novel steganographic algorithm integrating two key innovations: (1) Enhancement of stego image quality via stego image’s segmentation into four images, reducing concentration-induced distortions, and (2) optimization of data embedding through Huffman coding through a lossless compression minimizing the embedding-induced distortions while maximizing payload capacity. …”
Get full text

Multiplicity and stability of solutions in transport phenomena of non-Newtonian Carreau nanofluid with nonlinear Rosseland thermal approximations and neural prediction by Puneet Rana, Xinyi Zhu, Ioan Pop

“…The optimal number of neurons in a single hidden layer is determined and compared using metrics R2 and RMSE for each algorithm. …”
Get full text

Experimental Study on Evaluation of Organization Collaboration in Prefabricated Building Construction by Dingjing Bao, Yuan Chen, Shuai Wan, Jinlai Lian, Ying Lei, Kaizhe Chen

“…The knowledge-driven part of this evaluation system used an evaluation model based on the analytic hierarchy process (AHP), while the data-driven part used a prediction model based on the BO-XGBoost algorithm to verify the validity of the AHP-based model. …”
Get full text

Analyzing the impact of non-Newtonian nanofluid flow on pollutant discharge concentration in wastewater management using an artificial computing approach by Sidra Jubair, Jie Yang, Bilal Ali, Bandar Bin-Mohsin, Hamiden Abd El-Wahed Khalifa

“…These equations (ODEs) are solved using the Levenberg Marquardt back-propagation optimization algorithm (LMBOA) of the artificial neural network (ANN). …”
Get full text

Predicting weather-related power outages in large scale distribution grids with deep learning ensembles by L. Prieto-Godino, C. Peláez-Rodríguez, J. Pérez-Aracil, J. Pastor-Soriano, S. Salcedo-Sanz

“…This paper focuses on predicting daily reported incidences in electrical grids within specific regions, leveraging weather conditions as specific predictive variables. An optimization-based feature selection approach has been considered for selecting the optimal Reanalysis node locations used as predictors. …”
Get full text