Enhanced BDS four-frequency cycle slip detection and repair using fuzzy clustering analysis by Jinfeng Yuan, Xiaoning Su, Yuzhao Li

“…It is worth noting that during the repair process, the coefficients of the combined observation values are integers, preserving the integer cycle characteristic of the observation values, which allows cycle slips to be fixed directly, eliminating the need for complex searching procedures. …”
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Intrusion detection system based on machine learning using least square support vector machine by Pratik Waghmode, Manideep Kanumuri, Hosam El-Ocla, Tanner Boyle

“…Unauthorized access or attack can be avoided in critical systems using a comprehensive approach via an effective intrusion detection system (IDS). Traditional intrusion detection techniques are no longer accurate and effective enough to handle the demands of the big data age. …”
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A comparative analysis of fault detection and process diagnosis methods based on a signal processing paradigm by Dorel Aiordăchioaie

“…The results of the computer-based experiments show acceptable performance for all methods for the test case of bearings but the potential to detect more complex faults and change detection in the behavior of the machines, in general. …”
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Smart Fault Detection, Classification, and Localization in Distribution Networks: AI-Driven Approaches and Emerging Technologies by Jianxian Wang, Hazlie Mokhlis, Nurulafiqah Nadzirah Mansor, Hazlee Azil Illias, Agileswari K. Ramasamy, Xingyu Wu, Siqi Wang

“…However, with nations worldwide actively pursuing carbon neutrality and emission peak goals, sustainable energy sources such as solar and wind are increasingly penetrating distribution networks, posing significant challenges to conventional fault detection, classification, and localization techniques due to bidirectional power flows, dynamic fault currents, and rising network complexity. …”
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Detection of Bipolar Disorder and Schizophrenia Employing Bayesian-Optimized Grad-CAM-Driven Deep Learning by Osman Tayfun Bişkin, Cemre Candemir, Mustafa Alper Selver

“…Building on its success in other domains, including autism spectrum disorder and Alzheimer’s disease, DL models have demonstrated the potential to detect subtle structural changes in BD and SCH. Recent advancements suggest that DL can outperform traditional statistical methods, offering higher classification accuracy and enabling the differentiation of complex psychiatric disorders. …”
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New Methods for Waterfowl and Habitat Survey Using AI and Drone Imagery by Zhenduo Zhai, Zhiguang Liu, Yang Zhang, Andrew Zhao, Yi Shang

“…Existing methods for waterfowl monitoring face critical challenges such as low accuracy in identifying overlapping image regions and limited segmentation accuracy in complex habitats. To address these issues, this paper presents an end-to-end system and several new methods for efficiently and accurately identifying waterfowl populations in their natural habitats using AI and drone imagery. …”
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A Multi-Task Based Deep Learning Framework With Landmark Detection for MRI Couinaud Segmentation by Dong Miao, Ying Zhao, Xue Ren, Meng Dou, Yu Yao, Yiran Xu, Yingchao Cui, Ailian Liu

“…By correlating landmark detection with segmentation, we enhance surgical planning precision. …”
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A Hybrid Approach for Reachability Analysis of Complex Software Systems Using Fuzzy Adaptive Particle Swarm Optimization Algorithm and Rule Composition by Nahid Salimi, Seyfollah Soleimani, Vahid Rafe, Davood Khodadad

“…Experimental results demonstrate that proposed hybrid algorithm reduced verification time by up to 49.86% compared to Particle Swarm Optimization and 65.17% compared to Genetic Algorithms in reachability analysis of complex models. Furthermore, it explored 32.7% fewer states on average than the hybrid method based on Particle Swarm Optimization and Gravitational Search Algorithms, and 57.4% fewer states compared to Genetic Algorithms, indicating improved search efficiency. …”
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Real-Time Object Detection and Distance Measurement Enhanced with Semantic 3D Depth Sensing Using Camera–LiDAR Fusion by Ahmet Serhat Yildiz, Hongying Meng, Mohammad Rafiq Swash

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Multi-frequency EEG and multi-functional connectivity graph convolutional network based detection method of patients with Alzheimer’s disease by Yujian Liu, Libing An, Haiqiang Yang, Shuzhi Sam Ge

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P4CN-YOLOv5s: a passion fruit pests detection method based on lightweight-improved YOLOv5s by Zhiping Tan, Zhiping Tan, Dapeng Ye, Jiancong Wang, Wenxiang Wang

“…Traditional algorithms often face challenges in achieving high detection accuracy and efficiency when addressing the complex task of detecting densely distributed small objects. …”
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Performance Analysis of Maximum Likelihood Detection in Cooperative DF MIMO Systems with One-Bit ADCs by Tae-Kyoung Kim

“…Although joint maximum likelihood detection can efficiently mitigate error propagation by leveraging probabilistic information from a source-to-relay link, its computational complexity is impractical. …”
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Lightweight multidimensional feature enhancement algorithm LPS-YOLO for UAV remote sensing target detection by Yong Lu, Minghao Sun

“…LPS-YOLO introduces the SKAPP module for better feature fusion and incorporates the E-BiFPN and OFTP structures to efficiently preserve and transfer backbone information. …”
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Prioritizing image processing and big data analytics factors for software development using DEMATEL-choquet method in bipolar complex fuzzy context by Ruimin Ma

“…The causal effects indicate that feature extraction, automation and efficiency, as well as object detection, are critical causal factors, whereas image enhancement, security, and segmentation are dependent effects. …”
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Robust Target Detection and Estimation for Airborne STAP Radar With Arbitrary Array Errors and Target Uncertainty by Jianxin Wu, Yang Zhao, Changxian Li, Peng Shen

“…Finally, target angle estimation using subspace coefficients, which implements the ML estimator in a reduced-dimensional version, is presented to reduce the computational complexity of the ML estimator. …”
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YOLOv7scb: A Small-Target Object Detection Method for Fire Smoke Inspection by Dan Shao, Yu Liu, Guoxing Liu, Ning Wang, Pu Chen, Jiaxun Yu, Guangmin Liang

“…Additionally, a weighted bidirectional feature pyramid network (BiFPN) is integrated into the feature-extraction network to merge features across scales efficiently without increasing the model’s complexity. …”
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Ionic Liquid-Based Centrifuge-Less Cloud Point Extraction of a Copper(II)–4-Nitrocatechol Complex and Its Analytical Application by Denitsa Kiradzhiyska, Nikolina Milcheva, Miglena Ruzmanova, Fatma Genç, Petya Racheva, Kiril Gavazov

“…The method demonstrates a linear response in the copper(II) concentration range of 32–763 ng mL⁻¹ and a limit of detection of 9.7 ng mL⁻¹. The logarithmic extraction constant (log <i>K</i>_ex) was determined to be 7.9, indicating efficient extraction. …”
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Transforming Retinal Photographs to Entropy Images in Deep Learning to Improve Automated Detection for Diabetic Retinopathy by Gen-Min Lin, Mei-Juan Chen, Chia-Hung Yeh, Yu-Yang Lin, Heng-Yu Kuo, Min-Hui Lin, Ming-Chin Chen, Shinfeng D. Lin, Ying Gao, Anran Ran, Carol Y. Cheung

“…Entropy images, representing the complexity of original fundus photographs, may strengthen the contrast between diabetic retinopathy (DR) lesions and unaffected areas. …”
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An IoT intrusion detection framework based on feature selection and large language models fine-tuning by Huan Ma, Wan Zhang, Dalong Zhang, Baozhan Chen

“…Therefore, we propose a Feature Selection and Large Language Models (LLMs)-based IoT intrusion detection framework (FSLLM). At its core is a multi-stage feature selection algorithm combining Minimum Redundancy Maximum Relevance algorithm (mRMR) and a Pearson Correlation Coefficient (PCC)-improved Covariance Matrix Adaptation Evolution Strategy algorithm (CMA-ES). …”
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The VGG16 Method Is a Powerful Tool for Detecting Brain Tumors Using Deep Learning Techniques by Sarthak Raghuvanshi, Sumit Dhariwal

“…A brain tumor diagnosis is a complex and difficult task that requires accurate and efficient data analysis. …”
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