Differential evolution-optimized gold nanorods for enhanced photothermal conversion by Aimad Koulali, Piotr Radomski, Paweł Ziółkowski, Francesca Petronella, Luciano De Sio, Dariusz Mikielewicz

“…Utilizing the Differential Evolution (DE) algorithm, a robust metaheuristic optimization approach, we calculated the optimal size and shape of AuNRs for selected wavelengths. …”
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Daily reference evapotranspiration prediction in Iran: A machine learning approach with ERA5-land data by Ali Asghar Zolfaghari, Maryam Raeesi, Giuseppe Longo-Minnolo, Simona Consoli, Miles Dyck

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Association between different insulin resistance surrogates and erectile dysfunction in non-diabetic men: a large population-based study by Shenghao Wu, Weiting Xia

“…When segmenting effects were detected, recursive algorithms were used to determine potential inflection points. …”
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Evaluation of Preferred Automated Driving Patterns Based on a Driving Propensity Using Fuzzy Inference System by Sooncheon Hwang, Dongmin Lee

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<strong>Hybrid neural network with genetic algorithms for predicting distribution pattern of <em>Tetranychus urticae</em> (Acari: Tetranychidae) in cucumbers field of Ramhormoz, Ir... by Alireza Shabaninejad, Bahram Tafaghodinia, Nooshin Zandi Sohani

“…Results showed that in training and test phases of neural network combined genetic algorithm, there was no significant difference between variance and statistical distribution of actual values and predicted values, but distribution was no significant. …”
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Feasibility of thin-slice abdominal CT in overweight patients using a vendor neutral image-based denoising algorithm: Assessment of image noise, contrast, and quality. by Akio Tamura, Manabu Nakayama, Yoshitaka Ota, Masayoshi Kamata, Yasuyuki Hirota, Misato Sone, Makoto Hamano, Ryoichi Tanaka, Kunihiro Yoshioka

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End-to-End Architecture for English Reading and Writing Content Assessment Based on Prompt Learning by Su-Qin Wu, Ming-Yong Pang, Xue-Mei Sun, Xin-Jian Wang, Yun-Peng Ji

“…The algorithm preprocesses the input English texts through the prompt learning framework and uses multi-scale attention mechanisms to improve the model&#x2019;s ability to capture features at different linguistic levels. …”
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Computer Vision-Based Concrete Crack Identification Using MobileNetV2 Neural Network and Adaptive Thresholding by Li Hui, Ahmed Ibrahim, Riyadh Hindi

“…In addition, an advanced algorithm was developed to detect cracks and evaluate crack widths in high-resolution images. …”
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Potential Adverse Drug Events Identified with Decision Support Algorithms from Janusmed Risk Profile—A Retrospective Population-Based Study in a Swedish Region by Tora Hammar, Emma Jonsén, Olof Björneld, Ylva Askfors, Marine L. Andersson, Alisa Lincke

“…Janusmed Risk Profile is a CDSS evaluating the risk for nine common or serious ADEs resulting from combined pharmacodynamic effects. …”
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Analysis and evaluation of healthcare delivery to patients with coronary artery disease using PC-based medical data by A. M. Nazarov, S. N. Tolpygina, I. P. Bolodurina

“…Using PC-based medical information technologies, analyze and evaluate inpatient and outpatient care for patients with coronary artery disease (CAD) with the development and testing of machine learning algorithms.Material and methods. …”
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Method of calculating the pressure on the soil of wheeled tractors by V. Yu. Revenko, A. N. Nazarov, V. I. Skorlyakov

“…Insignificant differences in the assessment of the maximum pressure on the soil, obtained as a result of measurements and calculations (the difference is 1.9-3.3 %) indicate a high degree of reliability of the developed methodology, as well as the possibility of its application in engineering practice to evaluate the functional indicators of tractors, including taking into account changes in their size and mass parameters when equipped with ballast weights, agricultural machines, implements, dual tires, etc. …”
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Clinical evaluation of Rega 8: an updated genotypic interpretation system that significantly predicts HIV-therapy response. by Jurgen Vercauteren, Gertjan Beheydt, Mattia Prosperi, Pieter Libin, Stijn Imbrechts, Ricardo Camacho, Bonaventura Clotet, Andrea De Luca, Zehava Grossman, Rolf Kaiser, Anders Sönnerborg, Carlo Torti, Eric Van Wijngaerden, Jean-Claude Schmit, Maurizio Zazzi, Anna-Maria Geretti, Anne-Mieke Vandamme, Kristel Van Laethem

“…The predictive ability of Rega version 8 was analysed in comparison with that of previous evaluated version Rega 5 and two other algorithms (ANRS v2011.05 and Stanford HIVdb v6.0.11). …”
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Evaluating a discretized data acquisition method for couch modeling to streamline the commissioning process of radiological instruments by Syouta Tomimoto, Yusuke Saeki, Okihiro Motoda, Masato Tanaka, Syouki Tsumoto, Hana Nishikawa, Yuki Miyashima, Makiko Higuchi, Tadashi Tani, Kuniaki Katsui, Yoshinori Tanabe

“…Conclusions The optimal couch surface ED dose difference trend was identified, and the effectiveness indicated using the dose difference score from discrete-angle couch modeling. …”
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Quality evaluation of synthetic CT using a gamma analysis for prostate cancer MR-only radiotherapy by Viktor Babka, Lubos Rehounek, Iva Jakubcová, Igor Sirak, Petr Paluska, Linda Kašaová, Milan Vosmik, Jakub Grepl

“…GA was performed with thresholds of 100 HU and 70 HU for HU differences and 3 mm for DTA to evaluate image quality. …”
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The effects of nursing care package implementation on pressure injuries prevention in the intensive care unit by Sevda Önen, Özlem Doğu

“…Abstract Aim The study was aimed to evaluate the effect of the care package prepared in accordance with the algorithm in the intensive care unit on the prevention of pressure injuries. …”
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Comparison and general law research of multiple machine-learning models for proton exchange membrane electrolytic cell parameters prediction by Yukun Wang, Hai-Wen Li, Wenhan An, Yudong Mao, Kaimin Yang, Jiying Liu

“…Correlation analysis of the evaluation index is carried out and eight different machine learning techniques are adopted for prediction, including Elman neural network, back propagation neural network, long short-term memory, random forest (RF), support vector machine, bidirectional long short-term memory, Firefly algorithm optimized Elman neural network, and genetic algorithm optimized back propagation neural network (GA-BP). …”
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Machine Learning-Based Objective Evaluation Model of CTPA Image Quality: A Multi-Center Study by Sun Q, Liu Z, Ding T, Shi C, Hou N, Sun C

“…Model performance was evaluated using mean square error (MSE), coefficient of determination (R²), Pearson linear correlation coefficient (PLCC), Spearman rank correlation coefficient (SRCC), and Kendall rank correlation coefficient (KRCC).Results: After feature selection, three key features were retained: main pulmonary artery CT value, ascending aorta CT value, and the difference in noise values between the left and right main pulmonary arteries. …”
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The Volume-Based Pollution-Routing Problem with Time Windows: A Case Study by Bilal Bencharif, Mohamed Amine Beghoura, Emrah Demir

“…Computational experiments reveal a significant difference of over 20% between fixed and variable speed assumptions. …”
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Carrier-independent screen-shooting resistant watermarking based on information overlay superimposition by Xiaomeng LI, Daidou GUO, Xunfang ZHUO, Heng YAO, Chuan QIN

“…Financial security, an important part of national security, is critical for the stable and healthy development of the economy.Digital image watermarking technology plays a crucial role in the field of financial information security, and the anti-screen watermarking algorithm has become a new research focus of digital image watermarking technology.The common way to achieve an invisible watermark in existing watermarking schemes is to modify the carrier image, which is not suitable for all types of images.To solve this problem, an end-to-end robust watermarking scheme based on deep learning was proposed.The algorithm achieved both visual quality and robustness of the watermark image.A random binary string served as the input of the encoder network in the proposed end-to-end network architecture.The encoder can generate the watermark information overlay, which can be attached to any carrier image after training.The ability to resist screen shooting noise was learned by the model through mathematical methods incorporated in the network to simulate the distortion generated during screen shooting.The visual quality of the watermark image was further improved by adding the image JND loss based on just perceptible difference.Moreover, an embedding hyperparameter was introduced in the training phase to balance the visual quality and robustness of the watermarked image adaptively.A watermark model suitable for different scenarios can be obtained by changing the size of the embedding hyperparameter.The visual quality and robustness performance of the proposed scheme and the current state-of-the-art algorithms were evaluated to verify the effectiveness of the proposed scheme.The results show that the watermark image generated by the proposed scheme has better visual quality and can accurately restore the embedded watermark information in robustness experiments under different distances, angles, lighting conditions, display devices, and shooting devices.…”
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Model Updating and Global Eigenvalue Analysis of a Tie-Bolt Rotor Using Zero-Length Contact Elements under Different Preloads by Pu Li, Qi Yuan

“…Experimental modal testing is performed under different preloads of tie bolts. Model updating is carried out to tune the contact parameters using the Particle Swarm Optimization algorithm. …”
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