Modelling Itasy Lake Water Quality by Long Short Term Memory (LSTM) using Landsat8 Data by Randrianiaina Jerry Jean Christien Frederick, Rakotonirina Rija Itokiana, Jean Robertin Rasoloariniaina, Fils Lahatra Razafindramisa

“…Modeling lake water quality is very important to preserve and protect this resource. Several algorithms can be used to model lake water quality using in-situ measurement data. …”
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Addressing water scarcity challenges through rainwater harvesting: A comprehensive analysis of potential zones and model performance in arid and semi-arid regions–A case study on P... by Subhra Halder, Suddhasil Bose

“…Approximately 2% of the area is unsuitable, 8% is poorly suitable, 33% is moderately suitable, 45% is highly suitable, and the remaining 12% is extremely suitable in Purulia. Two predictive models were developed, with the RF algorithm demonstrating nearly 99% accuracy. …”
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Machine Learning Forecasting of Commercial Buildings’ Energy Consumption Using Euclidian Distance Matrices by Connor Scott, Alhussein Albarbar

“…A Euclidian distance matrix, akin to a K-nearest neighbour algorithm, determines the appropriate neural network(s) to utilise. …”
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Machine Learning Advancements in Urban Traffic Simulation: A Comprehensive Survey by Harshit Maheshwari, Li Yang, Richard W. Pazzi

“…Urban traffic simulation is useful in many ways to understand, manage, and predict the growing complexities of traffic dynamics within a city. …”
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Rotor Dynamic Behaviour of Electro-Rheological Lubricant Operated Multi-Lobe Journal Bearings by Kuldeep Narwat, Vivek Kumar, Simran Jeet Singh, Abhishek Kumar

“…The solution of the Reynolds equation is obtained employing the Newton-Raphson method, with numerical addressing of gaseous cavitation in the fluid film through a mass-conserving algorithm. The effects of lobe geometry and the applied electric field are scrutinized on bearing performance metrics. …”
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Two-Phase Globally Coupled Low-Density Parity Check Decoding Aided with Early Termination and Forced Convergence by Kun Zhu, Hongwen Yang

“…The initial variant, ET-1, predicts whether local decoding can be successful according to data characteristics and stop the local decoding iteration that is not expected to be successful in time. …”
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Design and development of advanced Al-Ti-V alloys for beampipe applications in particle accelerators by Kamaljeet Singh, Kangkan Goswami, Raghunath Sahoo, Sumanta Samal

“…The present investigation reports the design and development of an advanced material with a high figure of merit (FoM) for beampipe applications in particle accelerators by bringing synergy between computational and experimental approaches. Machine-learning algorithms have been used to predict the phase(s), low density, and high radiation length of the designed Al-Ti-V alloys. …”
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Bandage Therapeutic-Optical Keratoplasty in Keratoconus Patients after Intrastromal Corneal Segments Implantation by G. A. Osipyan, V. M. Sheludchenko, N. Y. Youssef, Kh. Khraystin

“…The first group consisted of 7 patients (7 eyes) of 27 ± 3 years old with had past history of CRS implantation followed by the absence of predicted improvement of visual acuity during the observation period of up to 18 months. …”
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Sequence-to-Sequence Text Generation with Discrete Diffusion Models by JIANG Hang, CAI Guoyong, LI Sihui

“…To this end, this paper simplifies the training process of the discrete diffusion model by deriving an upper bound on the training objective, and subsequently introduces and modifies the mask-and-predict decoding strategy from the conditional mask language model as the inference algorithm of the diffusion model. …”
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Cutting guides in mandibular tumor ablation: Are we as accurate as we think? by Omar Suhaym, Loren Moles, Nicholas Callahan

“…Conclusion: The finding of this study suggests that virtual surgical planning is an unambiguous paradigm shift in the predictability of the surgical plan and achievement of the reconstruction goals. …”
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Forced motion control of a mobile robot by T. Yu. Kim, R. A. Prakapovich, A. A. Lobatiy

“…The method of the theory of optimal control according to the criterion of maximum speed, the wave algorithm for finding the shortest path, the method of finite automata for relay control of the acceleration of movement are used.Results. …”
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Numerical modeling and experimental estimates of structural member fatigue characteristics by Yu. P. Man’shin, E. Yu. Man’shina

“…Introduction. In the algorithm for predicting the resource of machine parts, models of external actions, fracture resistance, and temporal development of a particular type of damage to these units interact. …”
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Classification of Moral Decision Making in Autonomous Driving: Efficacy of Boosting Procedures by Amandeep Singh, Yovela Murzello, Sushil Pokhrel, Siby Samuel

“…In contrast, the AdaBoost algorithm demonstrated superior accuracy and discriminatory power. …”
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Dynamic topology adaptability of adaptive multimodal transmission strategy based on environment perception in multi-hop routing of 5G vehicle network by Shengxia Tan, Xianshuang Zong, Feng Xiao

“…The features are input into gated recurrent unit (GRU) for time series modeling to predict the link node movement pattern. Then, ad hoc on-demand distance vector routing (AODV), greedy perimeter stateless routing (GPSR) and dynamic source routing (DSR) are integrated, and the best protocol is automatically selected through the classification and regression trees (CART) algorithm. …”
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A novel method for simulating dynamic facades to analysing, and optimizing daylight and visual comfort in office buildings by Mehran Shahmoradi, Mansour Yeganeh

“…Finally, it gives 12 two-variable functions (surface function) based on the sun's position parameters (x: azimuth, y: altitude) to shading device indices; then, these can predict the entire year's ideal position for the shading device. …”
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Advancing invasive species monitoring: A free tool for detecting invasive cane toads using continental-scale data by Franco Ka Wah Leung, Lin Schwarzkopf, Slade Allen-Ankins

“…Here, we present the development and assessment of a user-friendly and transferable monitoring tool for the invasive cane toad (Rhinella marina) using passive acoustic monitoring (PAM) and machine learning algorithms. Leveraging a continental-scale PAM dataset (Australian Acoustic Observatory), we trained a cane toad classifier using the BirdNET algorithm, a convolutional neural network architecture capable of identifying acoustic events. …”
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Single-Step Sampling Approach for Unsupervised Anomaly Detection of Brain MRI Using Denoising Diffusion Models by Mohammed Z. Damudi, Anita S. Kini

“…The output is a binary image showing the predicted anomalous regions, which is then compared to the ground truth to evaluate its segmentation performance. …”
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Forecast of hydrocarbon losses in deposits during the development of gas condensate fields by R. K. Dobrolyubova, E. I. Inyakina, I. I. Krasnov, V. V. Inyakin, A. F. Semenenko

“…To create such a model, a technique based on equations of state and an algorithm for modeling vapor-liquid transitions of hydrocarbon mixtures is used. …”
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Downscaling of ERA5 reanalysis land surface temperature based on attention mechanism and Google Earth Engine by Shiyu Li, Hong Wan, Qun Yu, Xinyuan Wang

“…In addition, the Bayesian global optimization algorithm is used to select the optimal hyperparameters of the network in order to enhance the predictive performance of the model. …”
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Prognostic and therapeutic potential of disulfidptosis-related genes in colon adenocarcinoma: a comprehensive multi-omics study by Ye Song, Haoran Zhu, Junyang Wei, Shanxue Yin

“…Conclusion The DRG-based prognostic model demonstrated strong predictive power in COAD, highlighting the potential of DRGs as therapeutic targets. …”
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