Combining chromosome conformation capture and exome sequencing for simultaneous detection of structural and single-nucleotide variants by Maria Gridina, Timofey Lagunov, Polina Belokopytova, Nikita Torgunakov, Miroslav Nuriddinov, Artem Nurislamov, Lyudmila P. Nazarenko, Anna A. Kashevarova, Maria E. Lopatkina, Stanislav Vasilyev, Andrey Zuev, Elena O. Belyaeva, Olga A. Salyukova, Aleksandr D. Cheremnykh, Natalia N. Sukhanova, Marina E. Minzhenkova, Zhanna G. Markova, Nina A. Demina, Yana Stepanchuk, Anna Khabarova, Alexandra Yan, Emil Valeev, Galina Koksharova, Elena V. Grigor’eva, Natalia Kokh, Tatiana Lukjanova, Yulia Maximova, Elizaveta Musatova, Elena Shabanova, Andrey Kechin, Evgeniy Khrapov, Uliana Boyarskih, Oxana Ryzhkova, Maria Suntsova, Alina Matrosova, Mikhail Karoli, Andrey Manakhov, Maxim Filipenko, Evgeny Rogaev, Nadezhda V. Shilova, Igor N. Lebedev, Veniamin Fishman

“…Enhanced with targeted long-read sequencing, Exo-C evolves into a cost-efficient solution capable of resolving complex SVs at base-pair accuracy. …”
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Machine learning-based model for acute asthma exacerbation detection using routine blood parameters by Youpeng Chen, Junquan Sun, Yabang Chen, Enzhong Li, Jiancai Lu, Huanhua Tang, Yifei Xie, Jiana Zhang, Lesi Peng, Haojie Wu, Zhangkai J. Cheng, Baoqing Sun

“…Conclusions: This machine learning model provides an efficient and practical tool for detecting AAE using routine blood parameters, offering potential value in clinical practice, especially in resource-limited settings. …”
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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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Enhancing Harmony Search Metaheuristic Algorithm for Coverage Efficiency, Test Suite Reduction, and Running Time in Combinatorial Interaction Testing by Aminu Aminu Muazu, Ahmad Sobri Hashim

“…Optimization has developed powerful algorithms for solving complex problems efficiently. The effectiveness of these algorithms, also called metaheuristics, largely depends on the capabilities of their search techniques. …”
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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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Lightweight deep learning system for automated bone age assessment in Chinese children: enhancing clinical efficiency and diagnostic accuracy by Pang Hai, Zhang Bin, Liu Kesheng, Li Cong, Xu Fei

“…In the first stage, the YOLOv8 algorithm precisely localizes 13 key epiphyses in hand radiographs, achieving a mean Average Precision (mAP) of 99.5% at Intersection over Union (IoU) = 0.5 and 94.0% within IoU 0.5–0.95, demonstrating robust detection performance. The second stage employs a modified EfficientNetB3 architecture for fine-grained epiphyseal grade classification, enhanced by the Rectified Adam (RAdam) optimizer and a composite loss function combining center loss and weighted cross-entropy to mitigate class imbalance. …”
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A comparative study of ultra-massive MIMO intelligent receivers with adversarial robustness and energy efficiency for 6G applications by Pushkar Nidagundi, Advesh Darvekar, Malik Amber, Ramesh R

“…Ultra-Massive Multiple Input Multiple Output (UM-MIMO) systems are pivotal for 6G wireless networks, enabling unprecedented data rates and spectral efficiency. However, optimizing these systems requires a careful balance between energy efficiency, spectral efficiency, and Bit Error Rate (BER) performance. …”
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MT-CMVAD: A Multi-Modal Transformer Framework for Cross-Modal Video Anomaly Detection by Hantao Ding, Shengfeng Lou, Hairong Ye, Yanbing Chen

“…Our optimized window-shift attention mechanism also reduces computational complexity, making MT-CMVAD a robust and efficient solution for safety-critical video understanding tasks.…”
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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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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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Visual Detection on Aircraft Wing Icing Process Using a Lightweight Deep Learning Model by Yang Yan, Chao Tang, Jirong Huang, Zhixiong Cen, Zonghong Xie

“…High transparency and blurred edges of icing areas in wing images pose challenges to wing icing detection by machine vision. To address these challenges, this study proposes a detection model, Wing Icing Detection DeeplabV3+ (WID-DeeplabV3+), for efficient and precise aircraft wing leading edge icing detection under natural lighting conditions. …”
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Surface Damage Detection in Hydraulic Structures from UAV Images Using Lightweight Neural Networks by Feng Han, Chongshi Gu

“…However, existing deep learning (DL) models often lack architectural adaptations for the visual complexities of UAV imagery, including low-texture contrast, noise interference, and irregular crack patterns. …”
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Lightweight multidimensional feature enhancement algorithm LPS-YOLO for UAV remote sensing target detection by Yong Lu, Minghao Sun

“…LPS-YOLO offers an effective solution for multi-target detection in UAVs.…”
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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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Advancing Software Vulnerability Detection with Reasoning LLMs: DeepSeek-R1′s Performance and Insights by Wenting Qin, Lijie Suo, Liangchen Li, Fan Yang

“…The increasing complexity of software systems has heightened the need for efficient and accurate vulnerability detection. …”
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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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Optimizing concrete crack detection an echo state network approach with improved fish migration optimization by Zhichun Fang, Xiuhong Wang, Jiaojiao Gao, Behrooz Eskandarpour

“…However, there are many models available for concrete crack detection, an efficient approach is needed because the existing methods often have flaws like overfitting, high computational complexity, and noise sensitivity, which can lead to accurate crack detection and classification. …”
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The application of deep learning technology in smart agriculture: Lightweight apple leaf disease detection model by Luo Man

“…These advancements make it robust, efficient, and practical for real-time disease detection in intelligent agricultural environments.…”
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DECISION TREE WITH HILL CLIMBING ALGORITHM BASED SPECTRUM HOLE DETECTION IN COGNITIVE RADIO NETWORK by N Suganthi, R Meenakshi, A Sairam, M Parvathi

“…Simulation results confirm that the DTHC method achieves a spectrum hole detection accuracy of 99%, with a miss-detection probability below 0.9%, demonstrating its effectiveness in enhancing CRN performance while maintaining low complexity.…”
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Fast real-time detection and counting of thrips in greenhouses with multi-level feature attention and fusion by Zhangzhang He, Xinyue Chen, Ying Gao, Yu Zhang, Yuheng Guo, Tong Zhai, Xiaochen Wei, Huan Li, Haipeng Zhu, Yongkun Fu, Zhiliang Zhang, Zhiliang Zhang

“…Compared to existing methods, TCD-Net achieves higher thrips counting and detection accuracy with lower computational complexity. …”
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