Enhanced YOLO and Scanning Portal System for Vehicle Component Detection by Feng Ye, Mingzhe Yuan, Chen Luo, Shuo Li, Duotao Pan, Wenhong Wang, Feidao Cao, Diwen Chen

“…In this paper, a novel online detection system is designed to enhance accuracy and operational efficiency in the outbound logistics of automotive components after production. …”
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Disc Diffusion Reader: an AI-powered potential solution to combat antibiotic resistance in developing countries by Hoang B Nguyen, Thanh L Phan, Thi T Ung, Thi KL Nguyen

“…Conclusions: The AI-powered “Disc Diffusion Reader” demonstrated high accuracy and efficiency, by reducing interpretation variability in the AST workflows. …”
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The Role of Digital Transformation in Manufacturing: Discrete Event Simulation to Reshape Industrial Landscapes by Fabio De Felice, Cristina De Luca, Antonella Petrillo, Antonio Forcina, Miguel Angel Ortiz Barrios, Ilaria Baffo

“…The implemented solutions led to a significant annual increase in productivity, the result of an overall improvement in process efficiency, which was also achieved through the identification and resolution of key process bottlenecks, confirming the method’s effectiveness. …”
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LGM-Net: Wheat Pest and Disease Detection Network Based on Local Global Information Interaction and Multi-Level Feature Fusion by Yimin Qu, Shaobo Yu, Jing Yang

“…Finally, this paper designs a decoupled task-adaptive detection head, including a task-aware layer dominated by channel attention and a feature learning layer dominated by deformable convolution. This model significantly improves the detection efficiency and accuracy of wheat diseases and insect pests, so as to take timely control measures and reduce the yield loss caused by diseases and insect pests, which is of great significance for ensuring global food security, and also provides strong technical support for the development of intelligent agriculture and precision agriculture. …”
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CLSTM-MT (a Combination of 2-Conv CNN and BiLSTM Under the Mean Teacher Collaborative Learning Framework): Encryption Traffic Classification Based on CLSTM (a Combination of 2-Conv... by Xiaozong Qiu, Guohua Yan, Lihua Yin

“…Therefore, there is an urgent need to develop an efficient and accurate encryption traffic identification method. …”
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Seedling Stage Corn Line Detection Method Based on Improved YOLOv8 by LI Hongbo, TIAN Xin, RUAN Zhiwen, LIU Shaowen, REN Weiqi, SU Zhongbin, GAO Rui, KONG Qingming

“…[Conclusions]The proposed crop line extraction method effectively addresses field challenges such as lighting and weed interference, enabling rapid and accurate crop identification. This approach supports the automatic navigation of agricultural machinery, offering significant improvements in the precision and efficiency of field operations.…”
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A Hybrid VGG16‐ViT Approach With Image Processing Techniques for Improved White Blood Cell Classification and Disease Diagnosis: A Retrospective Study by Md Shahin Ali, Md. Maruf Hossain, Md. Mahfuz Ahmed, Kazi Rubaya Nowrin, S. M. Mahim, Shakib Al Hasan, Moutushi Akter Kona, Md Shafiqul Islam, Kazi Mowdud Ahmed, Md Mahbubur Rahman, Md Khairul Islam

“…This study aims to enhance WBC detection and classification using a hybrid VGG16‐Vision Transformer (VGG16‐ViT) model. Methods To enhance the efficiency of the classification process, preprocessing techniques such as data normalization, categorical variable encoding, feature extraction, and data augmentation were employed in conjunction with the proposed model before the training phase. …”
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Deep learning-based fully automated detection and segmentation of pelvic lymph nodes on diffusion-weighted images for prostate cancer: a multicenter study by Zhaonan Sun, Pengsheng Wu, Tongtong Zhao, Ge Gao, Huihui Wang, Xiaodong Zhang, Xiaoying Wang

“…We utilized a 3D V-Net model to improve the efficiency and accuracy of LN detection and segmentation. …”
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An Auto-Annotation Approach for Object Detection and Depth-Based Distance Estimation in Security and Surveillance Systems by Misbah Bibi, Muhammad Faseeh, Anam Nawaz Khan, Atif Rizwan, Qazi Waqas Khan, Rashid Ahmad, Do-Hyeun Kim

“…A synthetic data is created by using the blender tool which emulates the real-world security and surveillance environments, is utilized to train a model for fast and accurate object recognition and identification. …”
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Federated Learning Based on an Internet of Medical Things Framework for a Secure Brain Tumor Diagnostic System: A Capsule Networks Application by Roman Rodriguez-Aguilar, Jose-Antonio Marmolejo-Saucedo, Utku Köse

“…This research introduces an analytical intelligence system based on an Internet of Medical Things (IoMT) framework that employs federated learning to provide a safe and effective diagnostic solution for brain tumor identification. By utilizing specific brain MRI datasets, the model enables multiple local capsule networks (CapsNet) to achieve improved classification results. …”
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Empowering voice assistants with TinyML for user-centric innovations and real-world applications by Sireesha Chittepu, Sheshikala Martha, Debajyoty Banik

“…A comparative review of current methods identifies areas of research gaps such as deployment difficulties, noise interference, and model efficiency on low-resource devices. From this study, researchers can directly identify the research gap with minimal effort, which may motivate them to focus more on solving the open problems due to optimize the problem identification time.…”
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Gearbox fault diagnosis method based on optimized VMD-NLM with 1DDRSN by WAN Zhiguo, ZHAO Wei, WANG Zhiguo, DOU Yihua

“…ObjectiveAiming at the problem of poor accuracy of gearbox fault diagnosis under noise interference, a new fault diagnosis method for gearboxes based on the denoising methods of optimized variational modal decomposition (VMD）and non-local means (NLM) was constructed, combined with a one-dimensional deep residual shrinkage network (1DDRSN).MethodsFirstly, the parameters in the VMD were automatically optimized using the subtractive average-based optimization (SABO); secondly, each intrinsic mode function (IMF） after the decomposition of the VMD was filtered using sample entropy, and the noise-containing components were subjected to the NLM denoising and reconstruction; then, a residual network that combines the attention mechanism with soft thresholding was introduced to model 1DDRSN; finally, the denoised and reconstructed signals were inputted into the 1DDRSN for fault diagnosis and identification. …”
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Research on Local Obstacle Avoidance Path Planning Algorithm for Autonomous Mining Trucks by HUANG Shuai, WANG Jia, HUANG Jiade, HUANG Peng, LYU Liang

“…Autonomous mining trucks currently face several challenges in local obstacle avoidance path planning within mining environments, including difficulties in close-range identification, delays in vehicle-to-ground communication, and the absence of real-time planning capabilities on the ground. …”
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PARADIGM FOR CONTEMPORARY SYMBOLIC REALITY by Elena Korableva

“…Conclusions: 1) Persons' immersion into the space of cultural and historical symbolic processes determines the content of their socialization which is a process of self-identification in the symbolic reality, the process of entering the subject-shaped field of human culture; 2) An adequate model of signs and symbols reflects the diversity of information flows, that is the synthesis of a specific objective and true knowledge, its interpretation and value. …”
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Using Modified Intelligent Experimental Design in Parameter Estimation of Chaotic Systems by Zahra Shourgashti, Hamid Keshvari, Shirin Panahi

“…Therefore, parameter estimation is known as an important part of the modeling and system identification. It usually refers to the process of using sampled data to estimate the optimum values of parameters. …”
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Space Precession Target Classification Based on Radar High-Resolution Range Profiles by Yizhe Wang, Cunqian Feng, Yongshun Zhang, Sisan He

“…We first establish the precession model of space targets and analyze the scattering characteristics and then compute electromagnetic data of the cone target, cone-cylinder target, and cone-cylinder-flare target. …”
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Artificial Intelligence and Machine Learning Approaches for Target-Based Drug Discovery: A Focus on GPCR-Ligand Interactions by M. O. Otun

“…The advent of artificial intelligence (AI) and machine learning (ML) has revolutionized target-based drug discovery, offering innovative approaches to predict GPCR-ligand interactions with enhanced accuracy and efficiency. This review explores the integration of AI and ML techniques in GPCR-targeted drug discovery, highlighting their potential to accelerate lead identification, optimize ligand binding predictions, and improve structure-activity relationship modeling. …”
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Intelligent Fault Detection and Self-Healing Mechanisms in Wireless Sensor Networks Using Machine Learning and Flying Fox Optimization by Almamoon Alauthman, Abeer Al-Hyari

“…This paper presents an intelligent framework based on Light Gradient Boosting Machine integration for fault detection and a Flying Fox Optimization Algorithm in dynamic self-healing. The LGBM model provides very accurate and scalable performance related to effective fault identification, whereas FFOA optimizes the recovery strategies to minimize downtown and maximize network resilience. …”
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Determinants of Stock Theft and Its Implication on Household Dietary Diversity in Semiarid Regions of Zimbabwe: Case of Gwanda District by Kainos Manyeruke, Lovemore Musemwa, Tavengwa Masamha

“…The linear regression model was used to analyze the factors that affected stock theft in rural areas. …”
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Are leaf chlorophyll fluorescence and Dark Green stressor-specific fingerprints in grapevine under drought or salt stress? A reanalysis study by Giuseppe Montanaro, Antonio Carlomagno, Pasquale Giorio, Angelo Petrozza, Francesco Cellini, Vitale Nuzzo

“…This study is motivated by the socio-economic relevance of vineyard and by the increasing need for stressor-specific fingerprint(s) to support the reliable identification of stress type (e.g., drought or salinity) within a high-throughput plant phenotyping domain.This paper presents a reanalysis of physiological and phenotyping data from drought and salt stress experiments in Vitis vinifera focussing the maximum photosynthetic efficiency (Fv/Fm) and leaf Dark Green color. …”
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