Combined use of multi-source satellite imagery and deep learning for automated mapping of glacial lakes in the Bhutan Himalaya by Xingyu Xu, Lin Liu, Lingcao Huang, Yan Hu

“…DeepLabv3+, an advanced semantic segmentation algorithm, was trained to delineate glacial lakes with areas larger than 0.005 km2 from multi-source imagery and their derivatives, including PlanetScope red-green-blue (RGB), PlanetScope-derived Normalized Difference Water Index (NDWI), Sentinel-2 RGB, Sentinel-2-derived NDWI, Sentinel-1 Synthetic Aperture Radar (SAR), and Landsat-8 RGB images. …”
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Optimal Dual Control Strategy for Multi-Interconnected Microgrids Under Unintentional Islanding and Fault Scenarios by H. K. Shaker, Ines Mahmoud, Magdi A. Mosa, K. M. Abdel-Latif, A. A. Ali, H. E. Keshta

“…Additionally, the paper utilizes an advanced bioinspired metaheuristic algorithm, the Newton-Raphson-based optimizer (NRBO), to optimize the design of the proposed controllers via the ITAE as a performance measure.…”
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Estimating Chlorophyll-a Concentrations in Optically Shallow Waters Using Gaofen-1 Wide-Field-of-View (GF-1 WFV) Datasets from Lake Taihu, China by Fuli Yan, Yuzhuo Li, Xiangtao Fan, Hongdeng Jian, Yun Li

“…The results show the following: (1) The normalized difference vegetation index (NDVI) method can distinguish the bottom mud (NDVI < −0.46) and submerged aquatic plants (−0.46 ≤ NDVI < 0.52) from the emergent plants (NDVI ≥ 0.52) with 90% accuracy. (2) The downwelling and upwelling irradiance attenuation coefficients are highly correlated with the suspended sediments, and retrieval models for these coefficients in three visible bands with high accuracy are presented. (3) Compared to traditional algorithms without bottom effect removal, the proposed chlorophyll-a concentration estimation algorithm based on the water depth-optimized bottom effect removal method efficiently reduces the bottom effect of the submerged aquatic plants. …”
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A study on early diagnosis for fracture non-union prediction using deep learning and bone morphometric parameters by Hui Yu, Qiyue Mu, Zhi Wang, Yu Guo, Jing Zhao, Guangpu Wang, Qingsong Wang, Xianghong Meng, Xiaoman Dong, Shuo Wang, Jinglai Sun

“…Through ablation studies, comparative experiments, and result analysis, the algorithm's effectiveness and superiority were validated. …”
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Research on community characteristics of vegetation restoration in hilly power engineering based on multi temporal remote sensing technology by Chen Bin, Lei Dong, Huang Liangjun, Liu Qingdong, Zhao Xuan, Shi Yuanping

“…Combining the deep learning model with the multi model hierarchical classification algorithm, the remote sensing prediction map based on deep learning is used as the classification base map, and the normalized difference vegetation index threshold is used to classify the uncovered area. …”
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Wind speed and power forecasting using Bayesian optimized machine learning models in Gabal Al-Zayt, Egypt by Nehal Elshaboury, Haytham Elmousalami

“…For WPP, the LGBM and BDT algorithms demonstrate strong predictive performance across different time scales, with MAPE, MSE, EV, R, and CCC values ranging from 0.277 to 186.710%, 0.927 to 9444.576, 0.970 to 1.000, 0.985 to 1.000, and 0.985 to 1.000, respectively.…”
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Tribological Behavior of AA7075 Reinforced with Ag and ZrO2 Composites by C. R. Mahesha, Suprabha R, M. Mahaveer Sree Jayan, Shilpa Kulkarni, Aman Sharma, Essam A. Al-Ammar, S. M. A. K. Mohammed, Ram Subbiah, Agonafir Alemayehu

“…In order to identify the best genetic algorithm results, theoretical and experimental results were evaluated.…”
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Similarity Analysis of Upper Extremity’s Trajectories in Activities of Daily Living for Use in an Intelligent Control System of a Rehabilitation Exoskeleton by Piotr Falkowski, Maciej Pikuliński, Tomasz Osiak, Kajetan Jeznach, Krzysztof Zawalski, Piotr Kołodziejski, Andrzej Zakręcki, Jan Oleksiuk, Daniel Śliż, Natalia Osiak

“…Further analysis involved calculating mathematical measures to evaluate the similarity between the different movements. …”
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Predicting the Traffic Crashes of Taxi Drivers by Applying the Non-Linear Learning of ANFIS-PSO with M5 Model Tree by E. Abbasi, M. Hadji Hosseinlou

“…In order to improve the generalization ability of a single data driving algorithm, a cluster of ANFIS models with different nodes and hidden layers are implemented to extract the inherent relationship between traffic accident rates and human factors. …”
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Breast cancer risk assessment tool: Observations from an Indian cohort by Somesh Chandra, Shantanu Chandra, Veer Kanani

“…A risk assessment tool helps to evaluate an individual’s risk at a particular point in time. …”
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Prototype of the Near-Infrared Spectroscopy Expert System for Particleboard Identification by Anna Sandak, Jakub Sandak, Dominika Janiszewska, Salim Hiziroglu, Marta Petrillo, Paolo Grossi

“…The overall goal of this work was to develop a prototype expert system assisting quality control and traceability of particleboard panels on the production floor. Four different types of particleboards manufactured at the laboratory scale and in industrial plants were evaluated. …”
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A combined improved dung beetle optimization and extreme learning machine framework for precise SOC estimation by Kaihua Yao, Xinyu Yan, Xiling Mao, Mengwei Li, Xiao Li, Ziyu Lian, Yuxiang Han

“…In this work, we propose a combined Improved Dung Beetle Optimization (IDBO) and Extreme Learning Machine (ELM) framework for SOC estimation and evaluate the efficiency of the BMS. The novelty of the model stems from the application of the IDBO algorithm, which incorporating Circle chaotic mapping, the Golden sine strategy, and the Levy flight strategy, for hyper-parameter optimization. …”
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Cheating Detection in Online Exams Using Deep Learning and Machine Learning by Bahaddin Erdem, Murat Karabatak

“…For regression and classification, deep neural network (DNN) from deep learning algorithms and support vector machine (SVM), decision trees (DTs), k-nearest neighbor (KNN), random forest (RF), logistic regression (LR), and extreme gradient boosting (XGBoost) algorithms from machine learning algorithms were used. …”
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Integrated Time Series Analysis, Clustering, and Forecasting for Energy Efficiency Optimization and Tariff Management by Anderson Jhones Passos Nascimento, Menaouar Berrehil El Kattel, Jose Antonio Fernandes de Macedo, Fernando Luiz Marcelo Antunes

“…Additionally, the BIRCH algorithm was evaluated in combination with dimensionality reduction methods, such as Principal Component Analysis (PCA) and Autoencoders, to enhance clustering performance. …”
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Deep learning for smartphone-aided detection system of Helicobacter Pylori in gastric biopsy by Guanmeng Gao, Zihan Wei, Fei Pei, Yajie Du, Beiying Liu

“…All stained slides were scanned for analysis by the Faster-R-CNN with ResNet 50 or VGG16, then the model performance was evaluated. Furthermore, the real-time microscopic field, smartphone and AI algorithm were connected through 5G networks and the AI results were sent back to the smartphone for confirmation by the pathologists. …”
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A Stabilized Incompressible SPH Method by Relaxing the Density Invariance Condition by Mitsuteru Asai, Abdelraheem M. Aly, Yoshimi Sonoda, Yuzuru Sakai

“…In the ISPH, pressure is evaluated by solving pressure Poisson equation using a semi-implicit algorithm based on the projection method. …”
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Ranking nodes in bipartite systems with a non-linear iterative map by Andrea Mazzolini, Michele Caselle, Matteo Osella

“…This paper introduces a method based on a non-linear iterative map to evaluate node relevance in bipartite networks. By tuning a single parameter γ, the method captures different concepts of node importance, including established measures like degree centrality, eigenvector centrality and the fitness-complexity ranking. …”
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Blending physical and artificial intelligence models to improve satellite-derived bathymetry mapping by Daniel García-Díaz, Sandra Paola Viaña-Borja, Mar Roca, Gabriel Navarro, Isabel Caballero

“…Satellite-Derived Bathymetry (SDB) offers a promising alternative to address the lack of current bathymetric data in shallow areas, particularly when utilizing data from satellite platforms such as Sentinel-2, along with advanced Machine Learning and Deep Learning techniques capable of enhancing bathymetric estimation compared to conventional methods. In this study, we evaluated the performance of two different algorithms for estimating SDB in two areas of the Western Mediterranean: a physics-driven model and an Artificial Neural Network (ANN). …”
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Advances in Data Pre-Processing Methods for Distributed Fiber Optic Strain Sensing by Bertram Richter, Lisa Ulbrich, Max Herbers, Steffen Marx

“…An artificial but realistic benchmark data set simulating different measurement scenarios is used to discuss the features of these algorithms. …”
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Flow cytometry for screening and prioritisation of urine samples: a retrospective comparison with culture by Vicky Sender, John Kerr White, Ludvig Bolinder, Karin Amilon, Mirja Hägg, Karin Haij Bhattarai, Niklas K. Björkström, Baharak Saeedi

“…Receiver operating characteristic (ROC) curve analyses assessed method agreement across different patient subpopulations. Predictive values were calculated for the total population and the ten different subpopulations at different cut-offs. …”
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