Synthesis, Characterization and Density Functional Study of LiMn1.5Ni 0.5O4 Electrode for Lithium ion Battery by M. Aruna Bharathi, K. Venkateswara Rao, M. Sushama

“…This paper explains the synthesis of most interesting cathode material Lithium Manganese Spinel and its derivatives like transition metal oxide (LiNi0.5Mn1.5O4) using Co-Precipitation chemical method; it is one of the eco-friendly ,effective, economic and easy preparation method. The structural features of LiNi0.5Mn1.5O4 was characterized by XRD – analysis indicated that prepared sample mainly belong to cubic crystal form with Fd3m space group ,with lattice parameter a  8.265 and average crystal size of 31.59 nm and compared the experimental results with computation details from first principle computation methods with Quantum wise Atomistix Tool Kit (ATK),Virtual Nano Lab. …”
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Improved Butterfly Optimizer-Configured Extreme Learning Machine for Fault Diagnosis by Helong Yu, Kang Yuan, Wenshu Li, Nannan Zhao, Weibin Chen, Changcheng Huang, Huiling Chen, Mingjing Wang

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GCS-YOLO: A Lightweight Detection Algorithm for Grape Leaf Diseases Based on Improved YOLOv8 by Qiang Hu, Yunhua Zhang

“…The number of parameters and computational load of the improved model have been reduced by 45.7% and 45.1%, respectively, compared to the baseline model, while the mAP has increased by 1.3%. …”
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LMD-YOLO: A lightweight algorithm for multi-defect detection of power distribution network insulators based on an improved YOLOv8. by Weiyu Han, Zixuan Cai, Xin Li, Anan Ding, Yuelin Zou, Tianjun Wang

“…The SimAM attention mechanism is integrated to suppress irrelevant features and enhance feature extraction capabilities without adding extra parameters. …”
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Intelligent assessment of damage and prediction of seismic damage spectrum under the effect of Near-Fault earthquakes in Iran by R. Fazli, M. Shamekhi Amiri, H. Pahlavan

“…Finally, a simplified equation has been suggested for assessing the potential seismic damage spectrum of the structures exposed to ground motions in Iran, capturing both structural and earthquake features. This study demonstrates the significant impact of structural and seismic parameters on the seismic damage spectrum, highlighting that an increase in the resistance reduction factor correlates with a rise in damage spectrum across structures of varying vibration periods. …”
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Development and evaluation of deep neural networks for the classification of subtypes of renal cell carcinoma from kidney histopathology images by Amit Kumar Chanchal, Shyam Lal, Shilpa Suresh

“…Additionally, the proposed method significantly reduces the number of parameters and FLOPs, demonstrating computationally efficient with 2.71 × $$10^9$$ FLOPs & 0.2131 × $$10^6$$ parameters.…”
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DLE-YOLO: An efficient object detection algorithm with dual-branch lightweight excitation network by Peitao Cheng, Xuanjiao Lei, Haoran Chen, Xiumei Wang

“…However, efficient algorithms often come with a large number of parameters and high computational complexity. To meet the demand for high-performance object detection algorithms on mobile devices and embedded devices with limited computational resources, we propose a new lightweight object detection algorithm called DLE-YOLO. …”
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MACA-Net: Mamba-Driven Adaptive Cross-Layer Attention Network for Multi-Behavior Recognition in Group-Housed Pigs by Zhixiong Zeng, Zaoming Wu, Runtao Xie, Kai Lin, Shenwen Tan, Xinyuan He, Yizhi Luo

“…Furthermore, MACA-Net significantly reduces parameters by 48.4% and FLOPs by 39.5%. When evaluated in comparison to leading detectors such as RT-DETR, Faster R-CNN, and YOLOv11n, MACA-Net demonstrates a consistent level of both computational efficiency and accuracy. …”
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Fast forward modeling and response analysis of extra-deep azimuthal resistivity measurements in complex model by Pan Zhang, Shaogui Deng, Xiyong Yuan, Fen Liu, Weibiao Xie

“…During the geosteering process, fault and wedge models were simulated, and various feature parameters were extracted to assess their impact on the simulation outcomes of EDARM. …”
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RDCRNet: RGB-T Object Detection Network Based on Cross-Modal Representation Model by Yubin Li, Weida Zhan, Yichun Jiang, Jinxin Guo

“…The proposed network features a Cross-Modal Feature Remapping Module that aligns modality distributions through statistical normalization and learnable correction parameters, significantly reducing feature discrepancies between modalities. …”
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A New Fault Detection and Classification Scheme in MTDC Grids with Hybrid Cable and Overhead Transmission Line by Zahra Moravej, Amir Imani, Mohammad Pazoki

“…In this paper, a new single-end time domain-based protection scheme for fault detection and classification is presented with remarkable features such as easy implementation, low computation burden, low sampling frequency, no setting parameters requirement, and also appropriate performance in noisy conditions. …”
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Cross-Modal Data Fusion via Vision-Language Model for Crop Disease Recognition by Wenjie Liu, Guoqing Wu, Han Wang, Fuji Ren

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RP-DETR: end-to-end rice pests detection using a transformer by Jinsheng Wang, Tao Wang, Qin Xu, Lu Gao, Guosong Gu, Liangquan Jia, Chong Yao

“…In this regard, the paper introduces an effective rice pest detection framework utilizing the Transformer architecture, designed to capture long-range features. The paper enhances the original model by adding the self-developed RepPConv-block to reduce the problem of information redundancy in feature extraction in the model backbone and to a certain extent reduce the model parameters. …”
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Research on lightweight weed recognition algorithm based on improved YOLOv8 by Zhang Chao, Liu Bin, Li Kun

“…Aiming at the problems of low accuracy of current field weed identification models and the difficulty of deploying multiple parameters in mobile devices and embedded devices with limited computing resources, a lightweight field weed identification model based on YOLOv8 is proposed in this paper. …”
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A generative model-based coevolutionary training framework for noise-tolerant softsensors in wastewater treatment processes by Yu Peng, Erchao Li

“…Additionally, a dual population coding method inspired by evolutionary computation is proposed, enabling the coevolution of network parameters and structure. …”
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Method for automatic antenna matching with transmitter output stage by D. A. Kovalevich

“…Acomparative analysis of the features of both the known methods of automatic tuning and the newly proposed one ismade.…”
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MEIS-YOLO: Improving YOLOv11 for efficient aerial object detection with lightweight design by Yicheng Liu, Jinsong Wu, Li Chen

“…Additionally, the cross bi-level routing attention module, which incorporates the cross-stage partial structure, optimizes the attention mechanism, further enhancing the model’s detection ability and computational efficiency. To further optimize multi-scale feature fusion, this paper introduces the asymptotic feature pyramid network. …”
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Explainable Machine Learning and Predictive Statistics for Sustainable Photovoltaic Power Prediction on Areal Meteorological Variables by Sajjad Nematzadeh, Vedat Esen

“…The resulting subset, dominated by apparent temperature and diffuse, direct, global-tilted, and terrestrial irradiance, reduces dimensionality without significantly degrading accuracy. Feature importance is then quantified through two complementary aspects: (a) tree-based permutation scores extracted from a set of ensemble models and (b) information gain computed over random feature combinations. …”
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Deep Learning Model for Analyzing EEG Signal Analysis by Varun Gupta, Vivek Kumar, Prince, Saurabh Singh, Young-Seok Lee, In-Ho Ra

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GDFC-YOLO: An Efficient Perception Detection Model for Precise Wheat Disease Recognition by Jiawei Qian, Chenxu Dai, Zhanlin Ji, Jinyun Liu

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