Can Knowledge Distillation Enable Seismic Interpolation, Super-Resolution, and Denoising Simultaneously? by Benwen Zhang, Linrong Wang

“…Consequently, SNet inherits TNet’s capabilities and further refines them during optimization. For comparison, we combine three interpolation algorithms with three super-resolution algorithms and select the one with the best performance. …”
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GRU-based multi-scenario gait authentication for smartphones by Qi JIANG, Ru FENG, Ruijie ZHANG, Jinhua WANG, Ting CHEN, Fushan WEI

“…At present, most of the gait-based smartphone authentication researches focus on a single controlled scenario without considering the impact of multi-scenario changes on the authentication accuracy.The movement direction of the smartphone and the user changes in different scenarios, and the user’s gait data collected by the orientation-sensitive sensor will be biased accordingly.Therefore, it has become an urgent problem to provide a multi-scenario high-accuracy gait authentication method for smartphones.In addition, the selection of the model training algorithm determines the accuracy and efficiency of gait authentication.The current popular authentication model based on long short-term memory (LSTM) network can achieve high authentication accuracy, but it has many training parameters, large memory footprint, and the training efficiency needs to be improved.In order to solve the above problems a multi-scenario gait authentication scheme for smartphones based on Gate Recurrent Unit (GRU) was proposed.The gait signals were preliminarily denoised by wavelet transform, and the looped gait signals were segmented by an adaptive gait cycle segmentation algorithm.In order to meet the authentication requirements of multi-scenario, the coordinate system transformation method was used to perform direction-independent processing on the gait signals, so as to eliminate the influence of the orientation of the smartphone and the movement of the user on the authentication result.Besides, in order to achieve high-accuracy authentication and efficient model training, GRUs with different architectures and various optimization methods were used to train the gait model.The proposed scheme was experimentally analyzed on publicly available datasets PSR and ZJU-GaitAcc.Compared with the related schemes, the proposed scheme improves the authentication accuracy.Compared with the LSTM-based gait authentication model, the training efficiency of the proposed model is improved by about 20%.…”
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Establishment of Hyperspectral Prediction Model of Water Content in Anshan-Type Magnetite by Xiaoxiao XIE, Yang BAI, Jiuling ZHANG, Yuna JIA

“…Using S-G smoothing filtering (S-G), multivariate scattering correction (MSC), standard normal transformation (SNV), second derivative (SD), reciprocal logarithm (LR) and continuum removal (CR) to preprocess the data, the spectral characteristics and their correlation with water content were analyzed. In order to further improve the prediction ability of the model, the competitive adaptive reweighting method (CARS) was used to optimize the characteristic band, and a prediction model was established by combining random forest regression (RFR), least squares support vector regression (LSSVR) and particle swarm optimization least squares support vector regression (PSO-LSSVR). …”
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The accuracy of image-based individual tree crown detection and delineation across vegetation types by N. Pucino, T. McVicar, S. Levick, A. van Dijk

“…Additionally, the DalPonte ITS algorithm provides the most accurate results, especially in sparsely vegetated areas such as rangelands, which are critical for mapping and monitoring. …”
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AGW-YOLO-Based UAV Remote Sensing Approach for Monitoring Levee Cracks by HU Weibo, ZHOU Shaoliang, ZHAO Erfeng, ZHAO Xueqiang

“…Comparative experiments indicated that AGW-YOLO outperformed several mainstream object detection algorithms, including Faster R-CNN, YOLOv8n, YOLOv9-tiny, YOLOv10n, RT-DETR-R50, and TPH-YOLO, across most evaluation metrics, offering high recognition accuracy with lower computational complexity. …”
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Stochastic economic placement and sizing of electric vehicles charging station with renewable units and battery bank in smart distribution network by Mehdi Veisi

“…Benders decomposition algorithm is used to extract the optimal solution. …”
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A Simheuristic Method for the Reversible Lanes Allocation and Scheduling Problem at Smart Container Terminal Gate by Wenyuan Wang, Ying Jiang, Yun Peng, Yong Zhou, Qi Tian

“…Together with a consideration of minimized total costs (both construction and operating) of terminal gate system, this paper first developed an optimization model to decide the number and scheduling rules of the reversible lanes at a terminal gate. …”
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A review of machine learning approaches for the discovery of thermoelectric materials by Övgü C. Yelgel, Celal Yelgel

“…This review explores the integration of ML into TE materials discovery, emphasizing its role in property prediction, descriptor engineering, and structural optimization. A systematic examination of ML-driven strategies promises to accelerate the discovery process and improve the efficiency of next-generation thermoelectric systems.…”
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Enhancing Tire Condition Monitoring through Weightless Neural Networks Using MEMS-Based Vibration Signals by Siddhant Arora, Sridharan Naveen Venkatesh, Vaithiyanathan Sugumaran, Anoop Prabhakaranpillai Sreelatha, Vetri Selvi Mahamuni

“…Hyperparameter optimization of the WNN leads to improved classification accuracy and shorter computation times. …”
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Boosting skin cancer diagnosis accuracy with ensemble approach by Priya Natha, Sivarama Prasad Tera, Ravikumar Chinthaginjala, Safia Obaidur Rab, C. Venkata Narasimhulu, Tae Hoon Kim

“…Moreover, feature vectors that were optimally produced from image data by a Genetic Algorithm (GA) were given to the ML models. …”
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High voltage direct current system-based generation and transmission expansion planning considering reactive power management of AC and DC stations by Ehsan Akbari, Ahad Faraji Naghibi, Mehdi Veisi, Sasan Pirouzi, Sheila Safaee

“…The scheme incorporates a non-linear model. The Red Panda Optimization (RPO) is utilized to solve the provided model in order to attain a dependable and optimal solution. …”
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Estimation of Wind Turbine Blade Icing Volume Based on Binocular Vision by Fangzheng Wei, Zhiyong Guo, Qiaoli Han, Wenkai Qi

“…Therefore, this paper proposes a non-contact ice volume estimation method based on binocular vision and improved image processing algorithms. The method employs a stereo matching algorithm that combines dynamic windows, multi-feature fusion, and reordering, integrating gradient, color, and other information to generate matching costs. …”
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Multi-user fine-grained task offloading scheduling strategy under cloud-edge-end collaboration by XIE Mande, HUANG Zhufang, SUN Hao

“…Then, a multi-user subtask scheduling scheme was proposed and an improved simulated annealing particle swarm algorithm was designed to minimize the total system cost to achieve the optimal offloading decision. …”
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RFID-embedded mattress for sleep disorder detection for athletes in sports psychology by Metin Pekgor, Aydolu Algin, Turhan Toros

“…This approach shows significant potential for sports psychology applications, enabling personalized recovery strategies and performance optimization. Future work will focus on expanding the dataset, integrating additional biometric sensors, and refining algorithms to improve diagnostic accuracy and real-time usability in clinical and home settings.…”
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Generalizability of machine learning models for diabetes detection a study with nordic islet transplant and PIMA datasets by Dinesh Chellappan, Harikumar Rajaguru

“…Researchers utilizing a hybrid feature extraction method such as Artificial Bee Colony (ABC) and Particle Swarm Optimization (PSO) followed by metaheuristic feature selection algorithms as Harmonic Search (HS), Dragonfly Algorithm (DFA), Elephant Herding Algorithm (EHA). …”
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Integrating personalized shape prediction, biomechanical modeling, and wearables for bone stress prediction in runners by Liangliang Xiang, Yaodong Gu, Kaili Deng, Zixiang Gao, Vickie Shim, Alan Wang, Justin Fernandez

“…The digital twin leverages a domain adaptation-based Long Short-Term Memory (LSTM) algorithm, informed by wearable sensor data, to dynamically simulate the structural behavior of foot bones under running conditions. …”
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Masks-to-Skeleton: Multi-View Mask-Based Tree Skeleton Extraction with 3D Gaussian Splatting by Xinpeng Liu, Kanyu Xu, Risa Shinoda, Hiroaki Santo, Fumio Okura

“…Furthermore, we use a minimum spanning tree (MST) algorithm during the optimization loop to regularize the graph to a tree structure. …”
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A single-snapshot inverse solver for two-species graph model of tau pathology spreading in human Alzheimer’s disease by Zheyu Wen, Ali Ghafouri, George Biros, the Alzheimer’s Disease Neuroimaging Initiative (ADNI)

“…This optimization problem is solved with a projection-based quasi-Newton algorithm. …”
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Massively parallel unsupervised single-particle cryo-EM data clustering via statistical manifold learning. by Jiayi Wu, Yong-Bei Ma, Charles Congdon, Bevin Brett, Shuobing Chen, Yaofang Xu, Qi Ouyang, Youdong Mao

“…However, traditional algorithms for unsupervised classification, such as K-means clustering and maximum likelihood optimization, may classify images into wrong classes with decreasing signal-to-noise-ratio (SNR) in the image data, yet demand increased computational costs. …”
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Deep reinforcement learning applications and prospects in industrial scenarios by JING TAN, Ligang YANG, Xiaorui LI, Zhaolin YUAN, Yunduan CUI, Chao YAO, Zongjie WANG, Xiaojuan BAN

“…Central to these systems are control algorithms, which enable the automation of operations, optimization of process parameters, and reduction of operational costs. …”
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