Optimizing Euclidean Distance Computation by Rustam Mussabayev

“…From spatial data structures and approximate nearest neighbor algorithms to dimensionality reduction, vectorization, and parallel computing, various approaches exist to accelerate Euclidean distance computation in different contexts. …”
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Distribution of University Admission Quotas: Problems of Competitive Selection Process by L. M. Nurieva, S. G. Kiselev

“…There will certainly be a deficiency of young specialists due to low mobility of graduates of the Russian higher school and reduction of the contingent of provincial higher education institutions-outsiders. …”
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Crystal structure generation with autoregressive large language modeling by Luis M. Antunes, Keith T. Butler, Ricardo Grau-Crespo

“…Seeding structure prediction algorithms with quality generated candidates can overcome a major bottleneck. …”
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Comparison of artificial intelligence approaches for estimating wind energy production: A real-world case study by Mohamed Bousla, Mohamed Belfkir, Ali Haddi, Youness El Mourabit, Badre Bossoufi

“…These results emphasise the need of accurate prediction for the efficient operation and maintenance of contemporary wind turbines and provide direction on choosing the most appropriate prediction techniques considering variables such as time frames, input properties, and processing needs.…”
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Neural Network Models for the Half-Cell Potential of Reinforced Slabs with Magnesium Sacrificial Anodes Subjected to Chloride Ingress by Yogesh Murthy

“…The network architecture [5-10-1] and 10 neurons in the hidden layer were used for all the prediction models. Out of all the training algorithms used, the overall performance was best with LM in all stages of modelling (>96%). …”
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Development of an AI‐based support system for controlled ovarian stimulation by Yoshimasa Asada, Tomoya Shinohara, Sho Yonezawa, Tomoki Kinugawa, Emiko Asano, Masae Kojima, Noritaka Fukunaga, Natsuka Hashizume, Yoshiki Hashiba, Daichi Inoue, Rie Mizuno, Masaya Saito, Yoshinori Kabeya

“…Four models, namely the hCG prediction model, the hMG prediction model, the Cetrorelix prediction model, and the Estradiol prediction model included in the prescription inference model, achieved AUC values of 0.914, 0.937, 0.966, and 0.976, respectively. …”
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Full Characterization of the Depth Overhead for Quantum Circuit Compilation with Arbitrary Qubit Connectivity Constraint by Pei Yuan, Shengyu Zhang

“…In this paper, we fully characterize the depth overhead by the routing number of the underlying constraint graph, a graph-theoretic measure which has been studied for 3 decades. We also give reduction algorithms between different graphs, which allow compilation for one graph to be transferred to one for another. …”
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Non-invasive detection of Parkinson’s disease based on speech analysis and interpretable machine learning by Huanqing Xu, Wei Xie, Mingzhen Pang, Ya Li, Luhua Jin, Fangliang Huang, Xian Shao

“…SHAp values highlighted the importance of fundamental frequency variation and harmonic-to-noise ratio in distinguishing PD patients from healthy individuals.ConclusionThe developed machine learning model accurately predicts Parkinson’s disease using speech recordings, with Random Forest and Gradient Boosting algorithms demonstrating superior performance. …”
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Multi-Model Demand Forecasting in Water Distribution Network Districts by Enrico Creaco, Carlo Giudicianni, Manuel Herrera

“…The first two modelling elements working in parallel are a pattern-based algorithm and a Random Forest model. By varying the algorithm setting and predictors, 42 algorithms are constructed and calibrated using demand and weather data in the previous weeks to the generic <i>n</i>-th week, when the objective is the prediction of the hourly demand pattern in the <i>n</i> + 1-th week. …”
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Smart Flow Steering Agent for End-to-End Delay Improvement in Software-Defined Networks by Omar F. Hussain, Bilal R. Al-Kaseem, Omar Z. Akif

“…By comparison, to these two routing algorithms, the suggested SFSA strategy determined a reduction of 2% in packets dropped ratio (PDR), a reduction of 15-45% in end-to-end delay according to the traffic produced, as well as a reduction of 23% in round trip time (RTT). …”
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Economical design strategies for reinforced concrete one-way slabs: a parametric approach considering material strength and rebar size by Rizwan Azam, Muhammad Rizwan Riaz, Mansoor Shakeel, Muhammad Umer Farooq, Muhammad Ammar Arshad

“…Abstract Despite the rapid advancements in optimization algorithms for economical reinforced concrete (RC) structures, their application to RC slabs has been significantly limited. …”
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An Empirical Evaluation of Supervised Learning Methods for Network Malware Identification Based on Feature Selection by C. Manzano, C. Meneses, P. Leger, H. Fukuda

“…This study presents an empirical evaluation of two statistical methods of reduction and selection of features in an Android network traffic dataset using six supervised algorithms: Naïve Bayes, support vector machine, multilayer perceptron neural network, decision tree, random forest, and K-nearest neighbors. …”
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Non-Gaussian Process Dynamical Models by Yaman Kindap, Simon Godsill

“…Probabilistic dynamical models used in applications in tracking and prediction are typically assumed to be Gaussian noise driven motions since well-known inference algorithms can be applied to these models. …”
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SURGNET: An Integrated Surgical Data Transmission System for Telesurgery by Sriram Natarajan, Aura Ganz

“…In this paper we propose SURGNET, a telesurgery system for which we developed the architecture, algorithms and implemented it on a testbed. The algorithms include adaptive packet prediction and buffer time adjustment techniques which reduce the negative effects caused by the lossy and time varying networks. …”
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A fact based analysis of decision trees for improving reliability in cloud computing. by Muhammad Asim Shahid, Muhammad Mansoor Alam, Mazliham Mohd Su'ud

“…J48 also has less fault prediction but with a good algorithm complexity of 0.11 seconds. …”
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Multi‐Model Assessment of PCA‐Informer Hybrid Model Against Empirical and Deep Learning Methods in TEC Forecasting by Yang Lin, Hanxian Fang, Die Duan, Ding Yang, Hongtao Huang, Chao Xiao, Ganming Ren

“…Consequently, there is a great interest in the prediction of TEC. In this study, we integrated the Informer deep learning algorithm and Principal Component Analysis (PCA), a dimensionality reduction technique, to achieve spatio‐temporal modeling for forecasting the global TEC maps. …”
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Sparse long short-term memory for information fusion in wireless sensor networks by Yangfan Zhou, Mingchuan Zhang, Ping Xie, Junlong Zhu, Ruijuan Zheng, Qingtao Wu

“…Furthermore, the prediction accuracy of the sparse long short-term memory algorithm is almost the same as the other comparison algorithms.…”
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Robust vs. Non-robust radiomic features: the quest for optimal machine learning models using phantom and clinical studies by Seyyed Ali Hosseini, Ghasem Hajianfar, Brandon Hall, Stijn Servaes, Pedro Rosa-Neto, Pardis Ghafarian, Habib Zaidi, Mohammad Reza Ay

“…Abstract Purpose This study aimed to select robust features against lung motion in a phantom study and use them as input to feature selection algorithms and machine learning classifiers in a clinical study to predict the lymphovascular invasion (LVI) of non-small cell lung cancer (NSCLC). …”
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Explainable Artificial Intelligence to Unveil Intrinsic Characteristics of Conditioning Factors Governing Forest Fire Susceptibility by A. Teke, T. Kavzoglu

“…The results showed that the NGBoost had the highest predictive performance with an overall accuracy of 81.42%, and outperformed the other algorithms by approximately 5% to 8%. …”
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Enhancing Pest Detection: Assessing Tuta absoluta (Lepidoptera: Gelechiidae) Damage Intensity in Field Images through Advanced Machine Learning by Edwin Lewıs, Atilla Erdinç, Yavuz Selim Şahin, Alperen Kaan Bütüner, Hilal Erdoğan

“…The performance of the DTs algorithm, as evidenced by a high precision and an accuracy rate of 0.98 and 0.99 respectively, testifies to its robust predictive and classification abilities. …”
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