Mixed Gas Detection and Temperature Compensation Based on Photoacoustic Spectroscopy by Sun Chao, Hu Runze, Liu Niansong, Ding Jianjun

“…It determines the weight ratio of each algorithm through experiments to improve the accuracy of gas category discrimination. …”
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Bioregionalization analyses with the bioregion R package by Pierre Denelle, Boris Leroy, Maxime Lenormand

“…The recent emergence of global databases, improvements in computational power and the development of clustering algorithms coming from the network theory have led to several major updates of the bioregionalizations of many taxa. …”
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Vegetation growth monitoring based on ground-based visible light images from different views by Yanli Chen, Lu Huang, Cheng Chen, Ying Xie

“…The machine learning algorithm combined with NLM filtering optimization had great advantages in multi-view image segmentation. …”
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Current approaches to diagnosis, treatment, and monitoring in patients with cryopyrin-associated periodic syndromes (CAPS) by S. O. Salugina, E. S. Fedorov, N. N. Kuzmina

“…Interleukin-1 inhibitors are target agents, by which one can monitor activity and prevent complications. The given algorithm will be able to improve the timely diagnosis of CAPS and to optimize treat-to-target treatment and management in patients.…”
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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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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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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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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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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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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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Development of a machine learning-based surrogate model for friction prediction in textured journal bearings by Yujun Wang, Georg Jacobs, Shuo Zhang, Benjamin Klinghart, Florian König

“…This enhancement is achieved through an architecture design based on cross-validation and further optimization utilizing the genetic algorithm. Eventually, the average prediction accuracy is improved to 98.81% from 95.89%, with the maximum error reduced to 3.25% from 13.17%. …”
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Joint source–channel rate allocation with unequal error protection for space image transmission by Dan Dong, Shaohua Wu, Dongqing Li, Jian Jiao, Chanjuan Ding, Qinyu Zhang

“…This separate design, although simple to be implemented, cannot explore the transmission performance to the most. In this article, we propose a joint source–channel rate allocation framework to improve the space image transmission performance. …”
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Rethinking Exploration and Experience Exploitation in Value-Based Multi-Agent Reinforcement Learning by Anatolii Borzilov, Alexey Skrynnik, Aleksandr Panov

“…We aim to optimize a deep MARL algorithm with minimal modifications to the well-known QMIX approach. …”
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A multitask framework based on CA-EfficientNetV2 for the prediction of glioma molecular biomarkers by Qian Xu, Feng Ning Liang, Ya Ru Cao, Jin Duan, Teng Cui, Teng Zhao, Hong Zhu

“…Initially, unlabeled MR images were annotated using K-means clustering to generate pseudolabels, which were subsequently refined using a Vision Transformer (ViT) network to improve labeling accuracy. Then, the Fruit Fly Optimization Algorithm (FOA) was employed to assign optimal weights to the pseudolabeled data. …”
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Automating an Encoder–Decoder Incorporated Ensemble Model: Semantic Segmentation Workflow on Low-Contrast Underwater Images by Jale Bektaş

“…Using a weight-optimization algorithm, the ensemble model with recreated IoU results improves the accuracy for both the Res34+Unet and the VGG19+FPN models, by 0.652% mIoU on average which is 6%. …”
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A Systematic Review and Comparative Analysis Approach to Boom Gate Access Using Plate Number Recognition by Asaju Christine Bukola, Pius Adewale Owolawi, Chuling Du, Etienne Van Wyk

“…By optimizing the capabilities of advanced YOLO algorithms, the proposed method seeks to improve the reliability and effectiveness of access control through precise and rapid plate number recognition. …”
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Finding Radial Network Configuration of Distribution System Based on Modified Symbiotic Organisms Search by Thuan Thanh Nguyen, Thanh-Quyen Ngo, Thanh Long Duong, Thang Trung Nguyen

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Features of single treasury account management in the context of budget funds liquidity management by N. S. Sergienko

“…Successful examples of integration of automated financial flow management systems, use of machine learning algorithms for forecasting and optimization of balances on single treasury account, as well as the interdepartmental interaction mechanisms to improve transparency and efficiency of budget management have been considered. …”
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Investigation on the Aerodynamic Parameters of the Triangle Shape of Tall Buildings by Using of CFD Method by Mehdi Noormohamadian, Eysa Salajegheh

“…Nowadays, the neural network algorithm is one of the most famous numerical methods for optimizing hull shapes. …”
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