Forecasting Wind Power Generation Using Artificial Neural Network: “Pawan Danawi”—A Case Study from Sri Lanka by Amila T. Peiris, Jeevani Jayasinghe, Upaka Rathnayake

“…This paper develops artificial neural network (ANN) models to forecast wind power generation in “Pawan Danawi”, a functioning wind farm in Sri Lanka. Wind speed, wind direction, and ambient temperature of the area were used as the independent variable matrices of the developed ANN models, while the generated wind power was used as the dependent variable. …”
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Manufacturing of Rotational Toroidal Shells in Coin Minting by Luís M. Alves, Paulo Alexandrino, Sónia Pereira

“…Through finite element modeling and experimentation, key process variables were identified, ensuring sound hollow toroidal shells with efficient rotation.…”
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Road Permeability Index as a tool for mitigation planning of road impacts on wildlife in Colombia: a case study using mammals by Fabio Leonardo Meza-Joya

“…The influence of 12 landscape variables on the permeability of each functional group was assessed at 30 locations along the road. …”
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An algorithm for independent component analysis using a general class of copula-based dependence criteria by Fatemeh Asadi, Hamzeh Torabi, Hossein Nadeb

“…The efficiency of Independent Component Analysis ($\rm ICA$) algorithms relies heavily on the choice of objective function and optimization algorithms. …”
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On optimization of substrate removal in a bioreactor with wall attached and suspended bacteria by Alma Mašić, Hermann J. Eberl

“…These control functions start with an initial no-flow period and then switch to a constant flow rate until the buffer vessel is empty. …”
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rcprd: An R package to simplify the extraction and processing of Clinical Practice Research Datalink (CPRD) data, and create analysis-ready datasets. by Alexander Pate, Rosa Parisi, Evangelos Kontopantelis, Matthew Sperrin

“…Functions are available to extract common variable types (e.g., history of a condition, or time until an event occurs, relative to an index date), and more general functions for database queries, allowing users to define their own variables for extraction. …”
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Robust IoT Activity Recognition via Stochastic and Deep Learning by Xuewei Wang, Shihao Wang, Xiaoxi Zhang, Chunsheng Li

“…Our approach begins with a rigorous preprocessing pipeline—encompassing filtering and normalization—to enhance data quality, followed by the application of probability density functions and key statistical measures to capture intrinsic sensor characteristics. …”
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Factors Determining Trade Credit Dynamics During Crisis: Panel Data Analysis for Macedonian Firms by F. Deari, V. V. Lakshina

“…The study includes a review of the literature on commercial credit factors; elaborately analyzed descriptive statistics of the collected data and dependent variable variance; tests for unobservable effects and their functional form; evaluation of panel regression and interpretation of the results. …”
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定中心距齿轮参数优化设计 by 李云鹏, 张科, 邓晓丽

“…Under the constant center distance conditions,according to the use of the transmission system requirements,selection of the appropriate design variables,constraint conditions and the objective function and using the complex method,the tooth parameters optimization design is carried out.Through the program,the optimized tooth parameter is calculated,the design efficiency is improved.…”
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Deep learning algorithm on H&E whole slide images to characterize TP53 alterations frequency and spatial distribution in breast cancer by Chiara Frascarelli, Konstantinos Venetis, Antonio Marra, Eltjona Mane, Mariia Ivanova, Giulia Cursano, Francesca Maria Porta, Alberto Concardi, Arnaud Gerard Michel Ceol, Annarosa Farina, Carmen Criscitiello, Giuseppe Curigliano, Elena Guerini-Rocco, Nicola Fusco

“…The DL model exhibited high accuracy in tissue quantification and TP53 status prediction, outperforming traditional methods in terms of precision and efficiency. DL-based approaches offer significant promise for enhancing biomarker testing and precision oncology by reducing intra- and inter-observer variability, but further validation is required to optimize their integration into real-world clinical workflows. …”
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Rehabilitation impact indices and their independent predictors: a systematic review by Amardeep Thind, Gerald Choon-Huat Koh, Robert Petrella, Cynthia Huijun Chen

“…Then, various names of the same formula were used to identify studies, limited to articles in English and up to 31 December 2011, including case–control and cohort studies, and controlled interventional trials where RIIs were outcome variable and matching or multivariate analysis was performed.Results The five RIIs identified were (1) absolute functional gain (AFG)/absolute efficacy/total gain, (2) rehabilitation effectiveness (REs)/Montebello Rehabilitation Factor Score (MRFS)/relative functional gain (RFG), (3) rehabilitation efficiency (REy)/length of stay-efficiency (LOS-EFF)/efficiency, (4) relative functional efficiency (RFE)/MRFS efficiency and (5) revised MRFS (MRFS-R). …”
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Vanadium remediation from polluted wastewater using a novel non-conventional adsorbent by Manar Banwan Hasan, Suha Anwer Ibrahim, Nisreen Mizher Rahmah, Thekra Atta Ibrahim, Alaa Hani Alminshid, Mohammed Nsaif Abbas

“…The obtained results indicated that the vanadium recovery efficiency reached 81 % and was in direct proportion to the pH, agitation speed, and contact time, and inversely with other variables, while adsorption capacity reaching 0.1 mg/g. …”
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Optimum Design of RC Beams Strengthened with Externally Bonded FRP Using Pattern Search by Noor Mohammed Sheet, Baraa J. M. AL-Eliwi, Rabi M. Najem

“…The design process involved an objective function that represents the cost function of the optimum solution and design variables that define the optimum dimensions of the beam and FRP material, such as beam width, effective beam depth, FRP strip thickness, FRP strips spacing, and FRP strip width, according to the design constraints of the ACI 440-2R-17 code. …”
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Preventive-Corrective Control for Static Voltage Stability Under Multiple <tex>$N-1$</tex> Contingencies Considering Wind Power Uncertainty by Yuerong Yang, Shunjiang Lin, Qiong Wang, Mingbo Liu, Qifeng Li

“…The chance constraints of the static voltage stability margins (SVSMs) in the normal operation state and after each <tex>$N-1$</tex> contingency are included. The approximate functions between the probability density functions (PDFs) of SVSMs and load shedding quantity with respect to preventive control variables are obtained to transform the expectation of load shedding quantity and the SVSM chance constraints into deterministic expressions. …”
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cagA gene EPIYA motif genetic characterization from Colombian Helicobacter pylori isolates: Standardization of a molecular test for rapid clinical laboratory detection. by Eliana Rocío Rodríguez Gómez, William Otero Regino, Pedro A Monterrey, Alba Alicia Trespalacios Rangel

“…Strains were obtained from patients diagnosed with functional dyspepsia at Clínica Fundadores in Bogotá. …”
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A comparative study evaluating three line immunoassays available for serodiagnosis of equine Lyme borreliosis: Detection of Borrelia burgdorferi sensu lato-specific antibodies in s... by Cornelia V Broeckl, Stephanie Hiereth, Reinhard K Straubinger

“…They are presented as inter-rater agreement and statistic reliability, represented by the Fleiss' kappa coefficient. Agreement scores ranged from poor to moderate depending on group and time-point of blood sample collection. …”
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Non-Destructive Detection of Fillet Fish Quality Using MQ135 Gas Sensor and Neutrosophic Logic-Enhanced System by M. Y. Shams, M. R. Darwesh, Roheet Bhatnagar, N. S. A. Al-Sattary, A. A. Salama, M. S. Ghoname

“…Artificial intelligence algorithms were employed to predict quality and calculate regression coefficients. Using the reference neural network algorithm based on chemical and physical compounds, regression coefficients (R values) achieved were 0.99, 0.98, and 0.97, respectively. …”
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Color image hybrid noise filtering algorithm based on deep convolution neural network by Yongfei Yu, Yuanjian Yan

“…Then, the probability density function and noise probability density function of Gaussian noise are calculated to determine the hybrid noise feature points of color image. …”
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Predicting the Permeability of Pervious Concrete Based on the Beetle Antennae Search Algorithm and Random Forest Model by Jiandong Huang, Tianhong Duan, Yi Zhang, Jiandong Liu, Jia Zhang, Yawei Lei

“…The results showed that the hyperparameters of RF can be tuned by the BAS efficiently; the BAS can combine the conventional RF algorithm to construct the evolved model to predict the permeability of pervious concrete; the cement/aggregate ratio was the most significant variable to determine the permeability, followed by the coarse aggregate proportions.…”
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An improved statistical bias correction method for Global Climate Model (GCM) precipitation projection: A case study on the CMCC-CM2-SR5 model projection in China’s Huaihe River Ba... by Yuning Luo, Ke Zhang, Wen Wang, Xinyu Chen, Jin Feng, Haijun Wang, Wei Liu, Cheng Guo, Cuiying Chen, Xiaozhong Wang

“…We applied this and three other methods—EquiDistant Cumulative Distribution Function matching method (EDCDF), combined Linear Scaling and Cumulative Distribution Function matching method (LS-CDF) and Quantile-quantile mapping method (QUANT)—to correct biases in the CMCC-CM2-SR5 model. …”
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