AI-Driven Innovation in Skin Kinetics for Transdermal Drug Delivery: Overcoming Barriers and Enhancing Precision by Nubul Albayati, Sesha Rajeswari Talluri, Nirali Dholaria, Bozena Michniak-Kohn

“…AI-driven algorithms optimize formulations, including penetration enhancers and advanced delivery technologies like microneedles and liposomes, while ensuring safety and efficacy. …”
Get full text

AC-YOLO: A lightweight ship detection model for SAR images based on YOLO11. by Rui He, Dezhi Han, Xiang Shen, Bing Han, Zhongdai Wu, Xiaohu Huang

“…However, existing SAR ship detection algorithms encounter two major challenges: limited detection accuracy and high computational cost, primarily due to the wide range of target scales, indistinct contour features, and complex background interference. …”
Get full text

METHOD FOR MODIFYING PROFILE OF CYCLOIDAL WHEEL CONSIDERING COMPENSATION FOR ELASTIC DEFORMATION by QIN ZhengZheng, WANG Quan, ZHAO DaXing, WANG Jun, ZENG LiLei

Get full text

Comparative analysis and selection of the geometry of the microphone array based on MEMS microphones for sound localisation by Andrii Riabko, Tetiana Vakaliuk, Oksana Zaika, Roman Kukharchuk, Yuriy Smorzhevsky

“…The subject of this article is the design and optimization of the geometric configuration of omnidirectional MEMS microphone arrays for sound localization tasks. …”
Get full text

The analysis of sculpture image classification in utilization of 3D reconstruction under K-means++ by Xuhui Wang

“…To overcome this challenge, this study proposes an innovative image classification method that combines the ResNet50 model from the Deep Convolutional Neural Network (DCNN) with the K-means++ clustering algorithm. …”
Get full text

Prediction model of middle school student performance based on MBSO and MDBO-BP-Adaboost method by Rencheng Fang, Tao Zhou, Baohua Yu, Zhigang Li, Long Ma, Tao Luo, Yongcai Zhang, Xinqi Liu

“…In addition, we propose the MDBO-BP-Adaboost model to predict students' performance. Firstly, the model incorporates the good point set initialization, triangle wandering strategy and adaptive t-distribution strategy to obtain the Modified Dung Beetle Optimization Algorithm (MDBO), secondly, it uses MDBO to optimize the weights and thresholds of the BP neural network, and lastly, the optimized BP neural network is used as a weak learner for Adaboost. …”
Get full text

Winter Wheat Yield Prediction Using Satellite Remote Sensing Data and Deep Learning Models by Hongkun Fu, Jian Lu, Jian Li, Wenlong Zou, Xuhui Tang, Xiangyu Ning, Yue Sun

“…Accurate crop yield prediction is crucial for formulating agricultural policies, guiding agricultural management, and optimizing resource allocation. This study proposes a method for predicting yields in China’s major winter wheat-producing regions using MOD13A1 data and a deep learning model which incorporates an Improved Gray Wolf Optimization (IGWO) algorithm. …”
Get full text

Degradation modeling and remaining useful life prediction for electronic device under multiple stress influences by Changjun Li, Jinjun Cheng, Haizhen Zhu, Bincheng Wen, Xin Zhao, Weijie Kang

“…Finally, the MLE-SA optimization algorithm is used to obtain the unknown parameter values of the model. …”
Get full text

Protecting digital assets using an ontology based cyber situational awareness system by Tariq Ammar Almoabady, Yasser Mohammad Alblawi, Ahmad Emad Albalawi, Majed M. Aborokbah, S. Manimurugan, Ahmed Aljuhani, Hussain Aldawood, P. Karthikeyan

“…The dual-algorithm approach provided improved detection capabilities compared to traditional methods, underscoring its potential for scalable and effective cybersecurity applications. …”
Get full text

A novel and efficient personalized stress detection technique using a deep learning model by Ulligaddala Srinivasarao, Gopisetty Rathnamma, M. Satish Kumar, Lakshmipathi Anantha, Rakesh Kumar Donthi, T. Jhansi Rani

“…The Chaotic Fennec Fox Optimization Algorithm (CFFO) tunes the hyperparameter. …”
Get full text

Smart indoor monitoring for disabled individuals using an ensemble of deep learning models in an IoT environment by Faisal S. Alsubaei, Abdulrahman A. Alshdadi, Mohammed Rizwanullah

“…Initially, the SIMDP-EDLIoT approach uses linear scaling normalization (LSN) to ensure that the input data is scaled appropriately. Besides, the Improved Osprey Optimization Algorithm (IOOA)-based feature selection is employed to classify the most relevant features, enhancing the efficiency of the system by reducing dimensionality. …”
Get full text

Enhancing Extreme Learning Machine Robustness via Residual-Variance-Aware Dynamic Weighting and Broyden–Fletcher–Goldfarb–Shanno Optimization: Application to Metro Crowd Flow Predi... by Lihui Wang, Jianguang Xie

“…Aiming at the robustness problem of the extreme learning machine (ELM) in noisy and nonuniform data scenarios, this paper proposes an improved algorithm (BFGS-URWELM) that integrates uniform residual weighting and Broyden–Fletcher–Goldfarb–Shanno (BFGS) quasi-Newton optimization. …”
Get full text

Pure data correction enhancing remote sensing image classification with a lightweight ensemble model by Huaxiang Song, Hanglu Xie, Yingying Duan, Xinyi Xie, Fang Gan, Wei Wang, Jinling Liu

“…Existing advanced methods often require substantial modifications to model architectures to achieve optimal performance, resulting in complex frameworks that are difficult to adapt. …”
Get full text

Voltage regulation in distribution networks by electrical vehicles with online parameter estimation by Shukang Lyu, Huachun Han, Jingyan Li, Xiaodong Yuan, Wenyue Wang

“…Then we propose an algorithm with online resistance estimation to find the optimal solution without requiring complete information about distribution networks. …”
Get full text

Data-driven seismic mechanical performance evaluation of RC columns based on adaptive optimization ensemble learning method integrating random forest and back propagation neural ne... by Ayong Jiao, Ziqing Jiao, Bin Gao

“…An improved black-winged kite optimization algorithm (IBKA), based on Levy flight and adaptive t-distribution strategies, is used to optimize the hyperparameters of the base models. …”
Get full text

YOLO-HPSD: A high-precision ship target detection model based on YOLOv10. by Manlin Zhu, Dezhi Han, Bing Han, Xiaohu Huang

“…Meanwhile, the Mixed Local Channel Attention (MLCA) is introduced after the C2F module at the network neck, which improves the model's ability to integrate both local and global information. …”
Get full text

Physical Health Portrait and Intervention Strategy of College Students Based on Multivariate Cluster Analysis and Machine Learning by Rong Guo, Rou Dong, Ni Lu, Lin Yu, Chaoxian Chen, Yonglin Che, Jiajin Zhang, Jianke Yang

“…This study employs an improved K-means algorithm integrated with machine learning models to analyze university students’ fitness data and develop personalized health intervention strategies. …”
Get full text

Dark Side of the Web: Dark Web Classification Based on TextCNN and Topic Modeling Weight by Gun-Yoon Shin, Younghoan Jang, Dong-Wook Kim, Sungjin Park, A-Ran Park, Younghwan Kim, Myung-Mook Han

“…For validation, we employed two datasets and compared the performance of the model with other text classification algorithms, where the proposed model demonstrated superior effectiveness in Dark Web classification.…”
Get full text

Deep learning-based edge detection for random natural images by Kanija Muntarina, Rafid Mostafiz, Sumaita Binte Shorif, Mohammad Shorif Uddin

“…Deep learning approaches offer significant advantages in capturing high-level representations, thereby improving the accuracy and robustness of edge detection algorithms. …”
Get full text

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

“…First, we introduce the high-low frequency (HiLo) attention into the intra-scale feature interaction module to enhance the extraction of both high- and low-frequency features, reduce computational complexity, and improve detection performance. To strengthen the model&#x2019;s multi-scale fusion capability for ship features of different scales, we incorporate the bidirectional feature pyramid network (BiFPN) to optimize cross-scale feature fusion and add the <inline-formula> <tex-math notation="LaTeX">$S_{2}$ </tex-math></inline-formula> features to further enhance the representation of small-scale ship features. …”
Get full text