Public perception of accuracy-fairness trade-offs in algorithmic decisions in the United States. by Mehdi Mourali, Dallas Novakowski, Ruth Pogacar, Neil Brigden

“…Gender and social justice orientations also significantly predicted EIA support. Overall, findings demonstrate multidimensional drivers of algorithmic fairness attitudes, underscoring divisions around equality versus equity principles. …”
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A Multi-Strategy Improved Honey Badger Algorithm for Engineering Design Problems by Tao Han, Tingting Li, Quanzeng Liu, Yourui Huang, Hongping Song

“…The dynamic density factor of water waves is added to improve the search efficiency of the algorithm in the solution space. Lens opposition learning based on the principle of lens imaging is also introduced to enhance the ability of the algorithm to get rid of local optimums. …”
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A New Bootstrap Based Algorithm for Hotelling’s T2 Multivariate Control Chart by A. Mostajeran, N. Iranpanah, R. Noorossana

“…The new bootstrap algorithm is also applied to a real data set.…”
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C-mixture and multi-constraints based genetic algorithm for collaborative data publishing by Yogesh R. Kulkarni, T. Senthil Murugan

“…From the experimentation, we proved that the proposed algorithm maintained the privacy and utility as compared with the existing algorithm. …”
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Training RBF NN Using Sine-Cosine Algorithm for Sonar Target Classification by Yixuan WANG, LiPing YUAN, Mohammad KHISHE, Alaveh MORIDI, Fallah MOHAMMADZADE

“…In order to overcome these issues, the sine-cosine algorithm (SCA) has been used to train RBF NNs in this work. …”
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Dynamic Beam Hopping Algorithm for LEO Satellite Systems Based on User Grouping by Qing SHU, Weibiao LI, Zuolin JIN, Zhong ZHENG, Yongbo ZHANG, Zesong FEI

“…., the number of concurrently serving users is increased.To address the above problems, it proposed a dynamic beam hopping (BH) scheme based on user grouping for communication service coverage.The proposed method utilized the sparsity of the angular domain channel distribution to adaptively divide user groups accorded to the beam direction where the user energy is maximum.The number of co-channel user groups was constrained by power and interference constraints, limiting the reduction of communication traffic delay, as power limitations on the satellite make the number of RF chains limited and increased the number of simultaneously served user groups increased the interference between user groups.So the BH scheme with beam cluster grouping was further proposed, when the beam clusters reduced the user delay by increased the number of users served at the same moment.Since the above problem was non-convex, it adopt a data-driven determinantal point process (DPP) learning method to simplify the beam scheduling in BH scheme.Simulation results showed that the dynamic BH algorithm based on user grouping could effectively reduce the average user delay by more than 52% compared with the single-beam scheme, also verifies the versatility of the DPP learning.…”
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Accelerating Bayesian hierarchical clustering of time series data with a randomised algorithm. by Robert Darkins, Emma J Cooke, Zoubin Ghahramani, Paul D W Kirk, David L Wild, Richard S Savage

“…This has necessitated the development of new and innovative statistical algorithms to get the most from experimental data. For example, faster algorithms make practical the analysis of larger genomic data sets, allowing us to extend the utility of cutting-edge statistical methods. …”
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Machine learning for brain tumor classification: evaluating feature extraction and algorithm efficiency by Krishan Kumar, Kiran Jyoti, Krishan Kumar

“…A case study with interpretable machine learning is also presented in the paper.…”
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Path Planning for Wall-Climbing Robots Using an Improved Sparrow Search Algorithm by Wenyuan Xu, Chao Hou, Guodong Li, Chuang Cui

“…Further path planning simulation experiments demonstrate the algorithm’s effectiveness, with the planned paths not only consuming less energy but also exhibiting shorter path lengths, fewer turns, and smaller steering angles.…”
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Minimising latency of pitch detection algorithms for live vocals on low-cost hardware

“…Many papers have been published over the past six decades assessing and comparing the accuracy of pitch detection algorithms on various signals, including vocals. However, very little information is available concerning the latency of pitch detection algorithms and methods with which this can be minimised. …”
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Modeling Chandy–Lamport Distributed Snapshot Algorithm Using Colored Petri Net by Saeid Pashazadeh, Basheer Zuhair Jaafar Al-Basseer, Jafar Tanha

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Evaluation of the Performance of Unsupervised Learning Algorithms for Intrusion Detection in Unbalanced Data Environments by Gutierrez-Portela Fernando, Almenares Mendoza Florina, Calderon-Benavides Liliana

“…This study evaluated the performance of unsupervised machine learning algorithms for intrusion detection in unbalanced data environments using the BoT-IoT dataset. …”
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On the Use of Perfect Sequences and Genetic Algorithms for Estimating the Indoor Location of Wireless Sensors by M. Ferreira, J. Bagarić, Jose M. Lanza-Gutierrez, S. Priem-Mendes, J. S. Pereira, Juan A. Gomez-Pulido

“…Finally, genetic algorithms were used for searching the optimal location of these fixed sensors, therefore minimizing the location estimation error.…”
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Evaluating Machine Learning Algorithms for Financial Fraud Detection: Insights from Indonesia by Cheng-Wen Lee, Mao-Wen Fu, Chin-Chuan Wang, Muh. Irfandy Azis

“…The study utilized Multiple Linear Regression along with advanced classification algorithms such as Logistic Regression, K-Nearest Neighbors (KNN), Support Vector Machine (SVM), Decision Tree, and Random Forest, to detect financial statement fraud. …”
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Compressive sensing based data gathering algorithm over unreliable links in WSN by Ce ZHANG, Xia ZHANG, Ou LI, Guan-lin MEI, Zhe HAN, Da-long ZHANG, Guang-yi LIU

“…To solve the problem that the ubiquitous unreliable links in the WSN influence the performance of the compressive sensing (CS) based data gathering,first the relationship between the reconstruction SNR of CS-based data gathering algorithm and the bit-error-ratio (BER) were simulated quantitatively.Then classify two cases were classified,namely light-payload and heavy-payload,relying on the analysis of wireless link packet loss characteristics.The random packet loss model was conceived to describe the packet loss under light-payload scenario.Further the neighbor topology spatial correlation prediction-based CS data gathering (CS-NTSC) algorithm was proposed,which utilized the nodes spatial correlation to reduce the impact of error.Additionally,the node pseudo-failure model was conceived to describe the packet loss occurred in network congestion,and then the sparse schedule-aided CS data gathering (CS-SSDG) algorithm were conceived,for the purpose of changing the sparsity of measurement matrix and avoiding measurements amongst the nodes affected by unreliable links,thus weakening the impact of error/loss on data reconstruction.Simulation analysis indicates that the proposed algorithms are not only capable of improving the accuracy of the data reconstruction without extra energy,but also effectively reducing the impact affected by the unreliable links imposed on CS-based data gathering.…”
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When Large Language Models Meet Evolutionary Algorithms: Potential Enhancements and Challenges by Chao Wang, Jiaxuan Zhao, Licheng Jiao, Lingling Li, Fang Liu, Shuyuan Yang

“…Pre-trained large language models (LLMs) exhibit powerful capabilities for generating natural text. Evolutionary algorithms (EAs) can discover diverse solutions to complex real-world problems. …”
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FPGA-Based Particle Swarm Collaborative Target Localization Algorithm for UAV Swarms by Chuanhao Zhang, Changsheng Li, Zhipeng Chen, Haojie Li, Hang Yu

“…These strategies collectively enhance the performance of the PSO algorithm in localization tasks. Comparative simulations conducted across a range of operational scenarios demonstrate that the algorithm not only ensures high localization accuracy but also delivers excellent real-time performance and rapid convergence. …”
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Electronic Information Signal Recognition Based on a Stochastic Neural Network Algorithm by Jiaye Wang

“…With the continuous increase of L, the training error of SCN network and TSVD-SCN network will be reduced to very small, and the training error of TSVD-SCN network is also less than SCN. Conclusion. The accuracy of the algorithm model proposed in this paper is higher than that of the SCN model. …”
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Research on Multi-peak MPPT of Photovoltaic Array Based on Improved ICA Algorithm by ZANG Xiaodi, LIU Lu

“…Secondly, the adaptive revolution factor is introduced to improve the local optimization ability of the algorithm, and the optimal value selection mechanism is used to retain the excellent factor of the original empire to improve the convergence speed of the algorithm. …”
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Control Algorithm for Renewable Energy Standalone System with Power Quality and Demand Management by Lingappa Jaklair, Guduri Yesuratnam, Pannala Mallikarjuna Sarma

“…The VSC is driven using a time domain-based signal decomposition algorithm consisting a 3-phase dual reduced order generalized integrators frequency Locked loop (DROGI-FLL). …”
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