RSWD-YOLO: A Walnut Detection Method Based on UAV Remote Sensing Images by Yansong Wang, Xuanxi Yang, Haoyu Wang, Huihua Wang, Zaiqing Chen, Lijun Yun

“…Through model deployment and testing on small edge devices, we demonstrate the feasibility of our proposed method. The detection algorithm achieves 86.1% mean Average Precision on the walnut dataset while maintaining operational functionality on small edge devices. …”
Get full text

Herbify: an ensemble deep learning framework integrating convolutional neural networks and vision transformers for precise herb identification by Farhan Sheth, Ishika Chatter, Manvendra Jasra, Gireesh Kumar, Richa Sharma

“…Abstract Herbs have historically been central to medicinal practices, representing one of the earliest forms of therapeutic intervention. While synthetic drugs are often highly effective in treating acute conditions, their use is frequently accompanied by adverse side effects. …”
Get full text

Precision farming in aquaculture: non-invasive monitoring of Atlantic salmon (Salmo salar) behaviour in response to environmental conditions in commercial sea cages for health and... by Meredith Burke, Dragana Nikolic, Pieter Fabry, Hemang Rishi, Trevor Telfer, Sonia Rey Planellas

“…Understanding fish behavioural responses to environmental conditions can inform management practices, while using cameras with associated algorithms offers a powerful, non-invasive tool for continuously monitoring and safeguarding fish health and welfare.…”
Get full text

Benchmarking a Novel Particle Swarm Optimization Dynamic Model Versus HOMER in Optimally Sizing Grid-Integrated Hybrid PV–Hydrogen Energy Systems by Ayatte I. Atteya, Dallia Ali

“…In this paper, a novel Particle Swarm Optimization (PSO) dynamic system model is developed by integrating a PSO algorithm with a precise dynamic hybrid PV-H₂ energy system model that is developed to accurately simulate the hybrid system by considering the dynamic behaviour of its individual system components. …”
Get full text

Land use changes and restraining environmental risks via mitigation approach, the case of Darakeh-Velenjak watershed in Iran by Hassan Esmaeilzadeh, Mohsen Ehteshami

“…The results of this research exhibited that from 1987 to 2018, vegetation had dramatically decreased, while arid, roads and built-up areas had increased. …”
Get full text

Trade credit management in wholesale companies based on statistical methods by E. V. Ermakova

“…In this industry, the companies deal with a huge amount of customers, while trade credit is a common practice. As a result, fast and reasonable choice of trade credit terms becomes especially important for wholesale companies. …”
Get full text

Research on Automatic Alignment for Corn Harvesting Based on Euclidean Clustering and K-Means Clustering by Bin Zhang, Hao Xu, Kunpeng Tian, Jicheng Huang, Fanting Kong, Senlin Mu, Teng Wu, Zhongqiu Mu, Xingsong Wang, Deqiang Zhou

“…To validate the impact of Euclidean clustering on subsequent clustering, two separate treatments of the obtained point cloud data were conducted during experimental validation: the first used the K-means clustering algorithm directly, while the second involved performing Euclidean clustering followed by K-means clustering. …”
Get full text

Intelligent deep learning for human activity recognition in individuals with disabilities using sensor based IoT and edge cloud continuum by Mohammed Maray

“…For feature subset selection, the enhanced honey badger algorithm (EHBA) model is used to effectively reduce dimensionality while retaining critical activity-related features. …”
Get full text

Bridging ACO-Based Drone Logistics and Computing Continuum for Enhanced Smart City Applications by Salvatore Rosario Bassolillo, Egidio D’Amato, Immacolata Notaro, Luca D’Agati, Giovanni Merlino, Giuseppe Tricomi

“…The proposed system addresses the Capacitated Vehicle Routing Problem (CVRP) by considering both drone capacity constraints and autonomy, using the ACO-based algorithm to efficiently assign delivery destinations while minimizing travel distances. …”
Get full text

Ship-DETR: A Transformer-Based Model for EfficientShip Detection in Complex Maritime Environments by Yi Wang, Xiang Li

“…To address these issues, we propose an effective ship detection algorithm—Ship Detection Transformer (Ship-DETR). …”
Get full text

Drilling Condition Identification Method for Imbalanced Datasets by Yibing Yu, Huilin Yang, Fengjia Peng, Xi Wang

“…Secondly, a sliding-window-based Synthetic Minority Oversampling Technique (SMOTE) algorithm is developed, which generates new minority-class samples while preserving temporal dependencies, achieving balanced data distribution among classes. …”
Get full text

Designing a Sustainable Supply Chain Network for Perishable Products Integrating Internet of Things and Mixed Fleets by Lihong Pan, Xialian Li, Miyuan Shan

“…The model is solved using the Non-Dominated Sorting Genetic Algorithm II (NSGA-II). A case study based on real-world data demonstrates the model’s effectiveness. …”
Get full text

An improved YOLOv5s-based method for detecting rice leaves in the field by Cheng Zhou, Caohang Zhou, Lili Yao, Yagang Du, Xin Fang, Zhangbin Chen, Chengliang Yin

“…First, we added a high-resolution layer and removed the original low-resolution detection layer, using the K-Means++ clustering algorithm to reset the anchor box sizes, enhancing the model’s ability to identify small leaf tip targets while reducing the number of parameters. …”
Get full text

Integrating Learning-Driven Model Behavior and Data Representation for Enhanced Remaining Useful Life Prediction in Rotating Machinery by Tarek Berghout, Eric Bechhoefer, Faycal Djeffal, Wei Hong Lim

“…The first part focuses on comprehensive data preprocessing using only feature scaling and selection via random forest (RF) algorithm, streamlining the process by minimizing human intervention while managing data complexity. …”
Get full text

A skipping spectrum sensing scheme based on deep reinforcement learning for transform domain communication systems by Ce Li, Yanhua Wu, Rangang Zhu, Ruochen Wu, Zhengkun Zhang, Zunhui Wang

“…By assigning different weights to balance sensing overhead and spectrum utilization while reducing conflicts, the algorithm’s adaptability and performance are improved. …”
Get full text

Using Reinforcement Learning in a Dynamic Team Orienteering Problem with Electric Batteries by Majsa Ammouriova, Antoni Guerrero, Veronika Tsertsvadze, Christin Schumacher, Angel A. Juan

“…The study incorporates a novel approach for solving the dynamic TOP, comparing two solution methodologies: a merging heuristic and a reinforcement learning (RL) algorithm. The heuristic combines routes using calculated savings and a biased-randomized strategy, while the RL model leverages a transformer-based encoder–decoder architecture to sequentially construct solutions. …”
Get full text

CAFiKS: Communication-Aware Federated IDS With Knowledge Sharing for Secure IoT Connectivity by Ogobuchi Daniel Okey, Demostenes Zegarra Rodriguez, Frederico Gadelha Guimaraes, Joao Henrique Kleinschmidt

“…Federated learning has recently gained significant attention as a method for building machine learning models due to its ability to preserve data privacy while delivering improved performance. In many cases, deep neural networks (DNNs) serve as the backbone algorithm in federated processes. …”
Get full text

Towards Secure IoT Authentication System Based on Fog Computing and Blockchain Technologies to Resist 51% and Hijacking Cyber-Attacks by Muwafaq Jawad, Ali A. Yassin, Hamid Ali Abed Al-asadi, Zaid Ameen Abduljabbar, Vincent Omollo Nyangares, Zaid Alaa Hussien, Husam A. Neamah

“…The average latency for registration is 1.25 ms, while the authentication phase completes in just 1.50 ms, making it highly suitable for time-critical IoHT applications. …”
Get full text

Towards an automated protocol for wildlife density estimation using camera‐traps by Andrea Zampetti, Davide Mirante, Pablo Palencia, Luca Santini

“…Still, processing and analysis of camera‐trap data are extremely time‐consuming. While algorithms for automated species classification are becoming more common, they have only served as supporting tools, limiting their true potential in being implemented in ecological analyses without human supervision. …”
Get full text

Cascaded Machine Learning of Soil Moisture and Salinity Prediction in Estuarine Wetlands Based on In Situ Internet of Things Monitoring by Jie Song, Yujun Yi

“…The Gradient Boosting Decision Tree (GBDT) algorithm predicted moisture best (R2 = 0.846), while the GBDT‐RF model predicted salinity best (R2 = 0.875). …”
Get full text