DVAEGMM: Dual Variational Autoencoder With Gaussian Mixture Model for Anomaly Detection on Attributed Networks by Wasim Khan, Mohammad Haroon, Ahmad Neyaz Khan, Mohammad Kamrul Hasan, Asif Khan, Umi Asma Mokhtar, Shayla Islam

“…Deep learning approaches like graph autoencoders are utilized to perform anomaly detection through obtaining node embeddings while dealing with the network nonlinearity and sparsity issues. …”
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I-YOLOv11n: A Lightweight and Efficient Small Target Detection Framework for UAV Aerial Images by Yukai Ma, Caiping Xi, Ting Ma, Han Sun, Huiyang Lu, Xiang Xu, Chen Xu

“…However, existing detection algorithms still have weak small target representation ability, extensive computational resource overhead, and poor deployment adaptability. …”
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Large-Language-Model-Enabled Text Semantic Communication Systems by Zhenyi Wang, Li Zou, Shengyun Wei, Kai Li, Feifan Liao, Haibo Mi, Rongxuan Lai

“…Based on this, we derive the optimal decoding criteria for the receiver and introduce beam search algorithm to further reduce complexity. …”
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A robust method for evaluating the potentials of 15-minute cities: Implications for sustainable urban futures by Jianying Wang, Mei-Po Kwan, Gezhi Xiu, Fangxu Deng

“…We employ the Location Set Covering Problem optimization model to analyze the resources required to achieve full coverage of 15-minute accessibility and the knee point detection algorithm to assess a city’s 15minC potential. …”
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Steatotic liver disease: radiological and ultrasound point of view by Alexey V. Borsukov, Daria Yu. Shestakova

“…All patients were examined with a single diagnostic algorithm consisting of 5 stages: clinical and laboratory stage, physical examination, ultrasound, dual-energy X-ray absorptiometry in the “Whole Body” mode, retrospective analysis of MDCT and/or MRI studies. …”
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Digital three-stage recursive-separable image processing filter with variable sizes of scanning multielement aperture by A. V. Kamenskiy, T. M. Akaeva, D. A. Grebenshchikova

“…The study established that the processing time of a test image using the developed filter is on average 5 times less than the time taken by the classical two-dimensional convolution algorithm. The optimal coefficients for magnifying the central element and raising the positive part of the aperture of a digital filter were determined, enabling the efficiency of its use to be enabled.Conclusions. …”
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Obstacle Avoidance Control of Autonomous Undersea Vehicle Based on DVFH+ in Ocean Current Environment by Zhongben ZHU, Jiahao ZHANG, Yifan XUE, Hongde QIN

“…Additionally, by considering the drift angle compensation in the real ocean current environment, the obstacle avoidance algorithm was optimized to improve its robustness and adaptability. …”
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Evaluation of Multi-Class Classification Performance Lung Cancer Through K-NN and SVM Approach by Muh. Indra Endriartono Saputra Troy, Sitti Rahmah Jabir, Siska Anraeni

“…Therefore, the results show that the SVM algorithm is superior to the KNN algorithm. The KNN and SVM methods were implemented for multi-class classification of lung cancer, allowing identification of various subtypes of lung cancer with optimal accuracy.…”
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Adaptive multi-agent reinforcement learning for dynamic pricing and distributed energy management in virtual power plant networks by Jian-Dong Yao, Wen-Bin Hao, Zhi-Gao Meng, Bo Xie, Jian-Hua Chen, Jia-Qi Wei

“…Our proposed MARL framework enables adaptive, decentralized decision-making for both the distribution system operator and individual VPPs, optimizing economic efficiency while maintaining grid stability. …”
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Cross-modal adaptive reconstruction of open education resources by Tang Shengju, Feng Li, Zhan Wang, Xie Zhaoyuan

“…., text, video, user behavior logs). (2) Maintaining the knowledge graph’s real-time relevance. (3) Reducing the cognitive demand of recommendations (optimizing cognitive efficiency). Our approach employs contrastive learning (a technique for similarity learning) with an enhanced algorithm. …”
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Secure Beamforming via Amplify-and-Forward Relays in Machine-to-Machine Communications by Zhongjian Liu, Xiaoning Zhang, Lin Bai, Chen Chen, Haige Xiang

“…The secrecy rate maximization problem can be formed into a two-level optimization problem and we solve it using semidefinite relaxation (SDR) techniques. …”
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Development of intelligent controller for high performance electric drives with hybrid CSA and RERNN technique by J. Prabhakaran, P. Thirumoorthi, M. Mathankumar, S. P. Mangaiyarkarasi

“…The primary objective is to control the speed of electric drives using complex mechanical configurations and variable parameters. The CSA optimizes the voltage source inverter’s control signal, while RERNN predicts the optimal control signal. …”
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Eliminating Effect of Moisture Content in Prediction of Lower Heating Value and Ash Content in Sugarcane Leaves Biomass by Kanvisit Maraphum, Kantisa Phoomwarin, Nirattisak Khongthon, Jetsada Posom

“…Additionally, variable selection methods such as a genetic algorithm (GA) and moisture-related wavelength exclusion were explored. …”
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Widefield ultra-high-density optical breast tomography system supplementing x-ray mammography by Miguel Mireles, Edward Xu, Morris Vanegas, Ailis Muldoon, Rahul Ragunathan, Shijie Yan, Bin Deng, Jayne Cormier, Mansi Saksena, Stefan A. Carp, Qianqian Fang

“…The OMCI system utilizes large field-of-view structured light illumination and single-pixel-camera based detection techniques to produce ultra-high spatial sampling density while ensuring that the inverse problem remains compact via the development of a unique target-adaptive pattern optimization technique to achieve compressive-sensing based measurements. …”
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Classification of Cervical Biopsy Images Based on LASSO and EL-SVM by Pan Huang, Shuailei Zhang, Min Li, Jing Wang, Cailing Ma, Bowei Wang, Xiaoyi Lv

“…This paper proposes a method of cervical biopsy tissue image classification based on least absolute shrinkage and selection operator (LASSO) and ensemble learning-support vector machine (EL-SVM). Using the LASSO algorithm for feature selection, the average optimization time was reduced by 35.87 seconds while ensuring the accuracy of the classification, and then serial fusion was performed. …”
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A Full-Profile Measurement Method for an Inner Wall with Narrow-Aperture and Large-Cavity Parts Based on Line-Structured Light Rotary Scanning by Zhengwen Li, Changshuai Fang, Xiaodong Zhang

“…Considering the structural constraints in the measurement of narrow-aperture and large-cavity parts, a structural optimization algorithm is designed to enable the sensor to achieve a high theoretical measurement resolution while satisfying the geometric constraints of the measured parts. …”
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Shoulder–Elbow Joint Angle Prediction Using COANN with Multi-Source Information Integration by Siyu Zong, Wei Li, Dawen Sun, Zhuoda Jia, Zhengwei Yue

“…To address the precision challenges in upper-limb joint motion prediction, this study proposes a novel artificial neural network (COANN) enhanced by the Cheetah Optimization Algorithm (COA). The model integrates surface electromyography (sEMG) signals with joint angle data through multi-source information fusion, effectively resolving the local optima issue in neural network training and improving the accuracy limitations of single sEMG predictions. …”
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Collaborative Federated Learning of Unmanned Aerial Vehicles in Space–Air–Ground Integrated Network by Huibo Li, Peng Gong, Siqi Li, Weidong Wang, Yu Liu, Xiang Gao, Dapeng Oliver Wu, Duk Kyung Kim, Guangwei Zhang, Jihao Zhang

“…In order to solve the mixed integer nonlinear problem (MINLP), a data offloading selection strategy based on proximity discovery and an iterative method-based resource allocation algorithm (IRA) are proposed. In addition, the closed-form solutions of the optimized variables are obtained. …”
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Flood resilience assessment of region based on TOPSIS-BOA-RF integrated model by Guofeng Wen, Fayan Ji

“…Training samples are then input into the Butterfly Optimization Algorithm(BOA) to optimize the key parameters in the Random Forest(RF). …”
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Enhancing and Generalizing Position-Velocity Tracking in Imperfect <italic>mm</italic>Wave Systems Using a Low-Complexity Neural Network by Deeb Assad Tubail, Mohammed Zourob, Salama Ikki

“…To manage the computational demands of the training phase, we employ a low-complexity algorithm, the Extreme Learning Machine (ELM), which calculates weights and biases through closed-form solution, avoiding complex optimization processes. …”
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