Optimizing aerodynamic shape of benchmark problems using an improved Gaussian process regression algorithm by Youtao Xue, Yuxin Yang, Shaobo Yao, Wenwen Zhao, Lihua Chen

“…Qualitative and approximate comparative analysis of the results with other research groups on the same benchmark case validates the robustness and effectiveness of our proposed optimization framework.…”
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A parallel multi-objective genetic algorithm for scheduling scientific workflows in cloud computing by Muhammad Sardaraz, Muhammad Tahir

“…The proposed algorithm is evaluated with benchmark datasets and comparative results with the standard genetic algorithm, particle swarm optimization, and specialized scheduler are presented. …”
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Comparative Assessment of Data Quality Dimensions in Scientific Multimedia Indexing Process by Hamid Hassani, Azadeh Mohebi, Mohammad Javad Ershadi

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Research on test strategy for randomness based on deep learning by Dongyu CHEN, Hua CHEN, Limin FAN, Yifang FU, Jian WANG

“…In order to achieve better test performance, researches on the randomness test strategies based on deep learning were conducted, including the batch average strategy proposed by EUROCRYPT 2021 and the selection strategy for data unit size.By introducing the randomness statistical test model based on deep learning methods, the statistical distribution and test power expression of two test strategies were theoretically derived, and it was pointed out that: (i) the batch average strategy could amplify the prediction accuracy of the model, but it was prone to an increase in the probability of the second type of error in statistics, instead reducing the statistical test power; (ii) the smaller data units of the deep model generally obtained the more powerful statistical tests.Based on the above understanding, a new bit-level deep learning model was proposed for randomness statistical tests, which gained the advantage of prediction with 80 times fewer parameters and 50% samples, compared with the previous work on linear congruent generator (LCG) algorithm, and achieved significant prediction advantages with 10～20 times fewer parameters by extending the model to apply to 5～7 rounds of Speck, compared with the model proposed by Gohr.…”
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Research on test strategy for randomness based on deep learning by Dongyu CHEN, Hua CHEN, Limin FAN, Yifang FU, Jian WANG

“…In order to achieve better test performance, researches on the randomness test strategies based on deep learning were conducted, including the batch average strategy proposed by EUROCRYPT 2021 and the selection strategy for data unit size.By introducing the randomness statistical test model based on deep learning methods, the statistical distribution and test power expression of two test strategies were theoretically derived, and it was pointed out that: (i) the batch average strategy could amplify the prediction accuracy of the model, but it was prone to an increase in the probability of the second type of error in statistics, instead reducing the statistical test power; (ii) the smaller data units of the deep model generally obtained the more powerful statistical tests.Based on the above understanding, a new bit-level deep learning model was proposed for randomness statistical tests, which gained the advantage of prediction with 80 times fewer parameters and 50% samples, compared with the previous work on linear congruent generator (LCG) algorithm, and achieved significant prediction advantages with 10～20 times fewer parameters by extending the model to apply to 5～7 rounds of Speck, compared with the model proposed by Gohr.…”
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Research on image generation technology based on deep learning by Li Jinchen

“…Image generation has emerged as a prominent research area in contemporary academia, with a high possibility of exploration and practice.…”
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IoT Device Identification Techniques: A Comparative Analysis for Security Practitioners by Ashley Andrews, George Oikonomou, Simon Armour, Paul Thomas, Thomas Cattermole

“…Our novel approach in this paper is to provide a simple methodology for assessing and comparing research into IoT device identification, bypassing the need to delve into granular details such as specific algorithmic choices or feature selections, which are attributes not all papers have, and instead to focus on common attributes shared across papers. …”
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Cost-effectiveness of follow-up algorithms for chronic thromboembolic pulmonary hypertension in pulmonary embolism survivors by Dieuwke Luijten, Wilbert B. van den Hout, Gudula J.A.M. Boon, Stefano Barco, Harm Jan Bogaard, Marion Delcroix, Karl-Friedrich Kreitner, Matthias Held, Menno V. Huisman, Luis Jara-Palomares, Stavros V. Konstantinides, Lucia J.M. Kroft, Albert T.A. Mairuhu, Lilian J. Meijboom, Thijs E. van Mens, Maarten K. Ninaber, Esther J. Nossent, Piotr Pruszczyk, Luca Valerio, Anton Vonk Noordegraaf, Frederikus A. Klok

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FixedSum: A Novel Algorithm for Generating Weight Vectors in Decomposition-Based Multiobjective Optimization by Syed Zaffar Qasim, Muhammad Ali Ismail

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Multi-objective DG placement in radial distribution systems using the IbI logic algorithm by Nitin Saxena, M Pandit, L Srivastava

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Early Detection of Congenital Heart Diseases among Infants Using Artificial Neural Network Algorithm by Lucy Ifeyinwa Ezigbo, Anthony Kwubeghari, Francis Okoye

“…Although the use of Logistic Regression algorithm attained a high level of performance with an accuracy of 95.00%, but it still falls below the proposed ANN algorithm. …”
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Robust cooperative spectrum sensing in cognitive radio blockchain network using SHA-3 algorithm by Evelyn Ezhilarasi I, J. Christopher Clement

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Sex classification accuracy through machine learning algorithms - morphometric variables of human ear and nose by Tej Kaur, Kewal Krishan, Akanksha Sharma, Ankita Guleria, Vishal Sharma

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Comparative Studies of Descriptor-Based Image Matching Techniques for AAV Applications by Tomasz Pogorzelski, Teresa Zielinska

“…This article presents the results of comparative studies of typical image feature-matching algorithms. …”
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Urban Mobility Choices of University Students: Insights into Satisfaction Levels and Preferences in the Thessaloniki Metropolitan Area by Efstathios Bouhouras, Thomas Dimos, Dimitrios Mastoras, Socrates Basbas

“…Our research contributes to the literature by applying a standardized methodology using an algorithm developed by the European Commission; the satisfaction levels among university students for private car and public transport in those years were determined. …”
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Comparative estimation of spring forms of triticale according to some quantitative traits by P. I. Stepochkin, T. S. Bauer

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Research progress on test scenario of ship autonomous navigation by Lijia CHEN, Kai WANG, Liwen HUANG, Shengwei LI, Xinwei ZHOU, Yanzhi LIU

“…The performance and characteristics of different scenario construction methods are compared and described, and the problems of scenario construction methods are analyzed in combination with different testing requirements such as algorithm verification optimization, performance evaluation, and safety verification. …”
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Comparative analysis of image mosaicing techniques for aerial agriculture field imaging by Maria John, S. Santhanalakshmi, J Amudha, Jianfeng Zhou

“…The objective of this work is to evaluate and compare image mosaicing techniques, focusing primarily on agricultural datasets. …”
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Comparative Analysis of Deep Learning Models for Intrusion Detection in IoT Networks by Abdullah Waqas, Sultan Daud Khan, Zaib Ullah, Mohib Ullah, Habib Ullah

“…This study addresses the problem of detecting intrusions in IoT environments by evaluating the performance of deep learning (DL) models under different data and algorithmic conditions. We conducted a comparative analysis of three widely used DL models—Convolutional Neural Networks (CNNs), Long Short-Term Memory (LSTM), and Bidirectional LSTM (biLSTM)—across four benchmark IoT intrusion detection datasets: BoTIoT, CiCIoT, ToNIoT, and WUSTL-IIoT-2021. …”
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Comparing bioinformatic pipelines for microbial 16S rRNA amplicon sequencing. by Andrei Prodan, Valentina Tremaroli, Harald Brolin, Aeilko H Zwinderman, Max Nieuwdorp, Evgeni Levin

“…Microbial amplicon sequencing studies are an important tool in biological and biomedical research. Widespread 16S rRNA gene microbial surveys have shed light on the structure of many ecosystems inhabited by bacteria, including the human body. …”
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