A Constrained Multi-Objective Optimization Algorithm with a Population State Discrimination Model by Shaoyu Zhao, Heming Jia, Yongchao Li, Qian Shi

“…Tailored environmental selection models are then designed for the auxiliary population according to different states, enabling them to guide the evolution of the main population more effectively. …”
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Exploring IRGs as a Biomarker of Pulmonary Hypertension Using Multiple Machine Learning Algorithms by Jiashu Yang, Siyu Chen, Ke Chen, Junyi Wu, Hui Yuan

“…Results: Among the 113 machine learning algorithms, the Lasso + LDA model achieved the highest AUC of 0.741. …”
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Diagnostic Models for Differentiating COVID-19-Related Acute Ischemic Stroke Using Machine Learning Methods by Eylem Gul Ates, Gokcen Coban, Jale Karakaya

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Photograph-based machine learning approach for automated detection and differentiation of aerial blight disease in soybean crops by Mukta Nainwal, Anurag Satpathi, Saqib Shamsi, Ali Salem, Ajeet Singh Nain, Dinesh Kumar Vishwakarma, Ahmed Elbeltagi, Salah El-Hendawy, Mohamed A. Mattar

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PSLDV-Hop: a robust localization algorithm for WSN using PSO and refinement process by Bhupinder Kaur, Deepak Prashar, Arfat Ahmad Khan, Seifedine Kadry, Jungeun Kim

“…By utilizing an improved iterative evolution algorithm, the PSLDV-Hop algorithm reduces localization errors by achieving a higher degree of accuracy in node localization. …”
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Differentiating Pulmonary Nodule Malignancy Using Exhaled Volatile Organic Compounds: A Prospective Observational Study by Guangyu Lu, Zhixia Su, Xiaoping Yu, Yuhang He, Taining Sha, Kai Yan, Hong Guo, Yujian Tao, Liting Liao, Yanyan Zhang, Guotao Lu, Weijuan Gong

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Enhancing PV feed-in power forecasting through federated learning with differential privacy using LSTM and GRU by Pascal Riedel, Kaouther Belkilani, Manfred Reichert, Gerd Heilscher, Reinhold von Schwerin

“…Consequently, federated LSTM and GRU models are compared with centralized and local baseline models using rolling 5-fold cross-validation to evaluate their respective performances. By leveraging advanced FL algorithms such as FedYogi and FedAdam, we propose a method that not only predicts sequential energy data with high accuracy, achieving an R2 of 97.68%, but also adheres to stringent privacy standards, offering a scalable solution for the challenges of smart grids analytics, thus clearly showing that the proposed approach is promising and worth being pursued further.…”
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Differential chemoproteomic analysis of RRS-1 candidate molecule and molecules of several nonsteroidal anti-inflammatory drugs by P. A. Galenko-Yaroshevsky, I. Yu. Torshin, A. N. Gromov, O. A. Gromova, K. F. Suzdalev, R. A. Murashko, A. V. Zelenskaya, A. V. Zadorozhniy, T. R. Glechyan, G. V. Simavonyan, E.M. I. Muhammad

“…To plan effective and safe pharmacotherapy for inflammation and pain, it is important to evaluate the mechanisms and spectrum of action of nonsteroidal anti-inflammatory drugs (NSAIDs), including their effects on human proteome.Objective: to identify and evaluate the most significant specific differences of candidate molecule RRS-1 (N-{(Z)-2-(1-methyl-1H-indol-3-yl)1-[(propylamino)carbonyl]vinyl}benzamide) from other NSAIDs through differential chemoreactome analysis.Material and methods. …”
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A similarity-based multi-objective test optimization technique using search algorithm by Amir Sohail Habib, Saif Ur Rehman Khan, Shahid Hussain, Naseem Ibrahim, Habib un Nisa, Abdullah Yousafzai

“…Inspired by this, we propose a Similarity-based Multi-Objective Optimization Technique (SMOOT) for test suite reduction using a Grey Wolf Optimizer (GWO) algorithm. The proposed technique employs different similarity metrics, including Cosine Similarity, Euclidean Distance, Jaccard Similarity, Manhattan Distance, and Minkowski Distance, to evaluate the similarity score of the tests. …”
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Augmented secretary bird optimization algorithm for wireless sensor network deployment and engineering problem. by Qingwen Meng, Xi Kuang, Zihan Yu, Minghui He, Hanzhi Cui

“…Firstly, a differential collaborative search mechanism is introduced in the exploration phase to reduce the risk of the algorithm falling into local optima. …”
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An Enhanced Human Evolutionary Optimization Algorithm for Global Optimization and Multi-Threshold Image Segmentation by Liang Xiang, Xiajie Zhao, Jianfeng Wang, Bin Wang

“…Secondly, an adaptive learning strategy is proposed which combines differential learning and adaptive factors to improve the ability of the algorithm to jump out of the locally optimum threshold. …”
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How can Multi-Agents AI Systems help Reduce Biases in Trading Algorithms? by Florin GROSU

“…However, algorithmic trading is still accompanied by cognitive and algorithmic biases such as overconfidence, confirmation bias, and anchoring effects that can result in suboptimal decisions and higher levels of risk. …”
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Clinical TNM Lung Cancer Staging: A Diagnostic Algorithm with a Pictorial Review by Ivana Kuhtić, Tinamarel Mandić Paulić, Lucija Kovačević, Sonja Badovinac, Marko Jakopović, Margareta Dobrenić, Maja Hrabak-Paar

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Research on Optimized Algorithm for Deep Learning Based Recognition of Sediment Particles in Turbulent Flow by WANG Hao, YANG Feiqi, ZHANG Lei, WU Wei, XIE Haonan, ZHAO Lin

“…ObjectiveThe movement of sediment particles significantly affects riverbed evolution, establishing it as a central concern and ongoing challenge in fluvial dynamics research. …”
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Iterative Adaptive Multi-State Constrained Localization Algorithm Based on Vision/inertial Fusion by JIE Xiaohan, LIU Ning, SHEN Kai, QI Wenhao, LIU Xueqin

“…[Methods] First, the tracking efficiency and real-time requirements of the rescue personnel's violent and complex movements in occluded space analyzed, an iterative adaptive algorithm was designed, and window data iteration was used to judge the excitation and trigger the initialisation condition to construct the measurement update; Second, the way of evaluating and screening the number of map points and pixel differentiation was studied, and a map point optimisation mechanism was introduced to improve the real-time performance of evaluating and screening map points; Finally, a simulation and test platform is built to validate the algorithm. …”
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Automated Detection of Aberrant Episodes in Epileptic Conditions: Leveraging EEG and Machine Learning Algorithms by Uddipan Hazarika, Bidyut Bikash Borah, Soumik Roy, Manob Jyoti Saikia

“…The intent of this study is to precisely detect epileptic episodes by leveraging machine learning and deep learning algorithms on EEG inputs. The proposed approach aims to evaluate the feasibility of developing a novel technique that utilizes the Hurst exponent to identify EEG signal properties that could be crucial for classification. …”
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Distributed denial-of-service (DDOS) attack detection using supervised machine learning algorithms by S. Abiramasundari, V. Ramaswamy

“…Support Vector Machine (SVM), Logistic Regression (LR), Random Forest (RF), K-Nearest Neighbours (KNN), Decision Tree (DT) supervised models, and Principle Component Analysis (PCA) feature selection method are used to differentiate between attack and regular traffic. The CICIDS2018, CICIDS2017, and CICDDoS-2019 datasets are used to evaluate the performances of ML algorithms. …”
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Dengue algorithms integrated into the IMCI guidelines: An updated assessment in five Southeast-Asian countries. by Stephanie Petzold, Kerstin D Rosenberger, Bridget Wills, Jacqueline Deen, Martin W Weber, Thomas Jaenisch, IDAMS IMCI study group

“…We aimed to evaluate the dengue algorithms incorporated into IMCI guidelines and discuss the need for harmonization, including an extension of the age range for IMCI.…”
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The Efficiency of Complex Differential Treatment of the Patients with Systemic Lupus Erythematous Considering the Features of Bone Tissue Structure Remodeling by Abrahamovych U., Tsyhanyk L., Abrahamovych O., Farmaha M., Romaniuk O.

“…Considering the peculiarities of bone remodeling, we have developed an algorithm of a complex differential treatment of patients out of each subgroups: І group – calcium carbonate /calcium citrate 1000.0 mg/a day + vit D 600.0 IU/a day (Vitamin D deficiency (>20.0 ng/l)/ vit D1000.0 IU/a day (vitamin D deficiency (10.0-20.0 ng/l)/ vit D 2000.0 vitamin D deficiency (<10.0 ng/l); ІІ subgroup – calcium carbonate/calcium citrate 1000.0 mg/a day + vit D 600.0 IU/ a day (vitamin D deficiency(>20.0 ng/l)/ vit D1000.0 IU/ a day (vitamin D deficiency (10.0-20.0 ng/l)/ vit D2000.0 vitamin D deficiency (<10.0 ng/l) + alendronate 70.0 mg/a week; ІІІ subgroup – the diet enriched with calcium + alfacalcidol 1.0 mcg/24 hrs + alendronate 70.0 mg/ a week; FV subgroup – the diet enriched with calcium+ alfacalcidol 1.0 mcg/24 hrs. …”
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Computational scheme for the numerical solution of fractional order pantograph delay-integro-differential equations via the Bernstein approach by E. Aourir, H. Laeli Dastjerdi, Kamal Shah, Thabet Abdeljawad

“…The main objective of this research is to provide an efficient computational algorithm for solving a class of fractional order pantograph delay-integro-differential equations. …”
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