CSA: Utility Optimization Scheduling Algorithm for IoT Blockchain Sharding Committees by Xin Cong, Qi Jing, Lingling Zi, Changjiang Lin

“…CSA dynamically adjusts the committee members to achieve near-optimal solutions while addressing operational constraints. Theoretical analysis demonstrates the convergence bounds of the algorithm and its robustness against Sybil and eclipse attacks, ensuring high entropy for committee selection. …”
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A Clustering Algorithm for Large Datasets Based on Detection of Density Variations by Adrián Josué Ramírez-Díaz, José Francisco Martínez-Trinidad, Jesús Ariel Carrasco-Ochoa

“…However, while these algorithms can adapt to large datasets by building clusters with arbitrary shapes by identifying low-density regions, they usually struggle to identify density variations. …”
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Robust Crater Detection Algorithm Based on Maximum Entropy Threshold Segmentation by Peng Wu, Rongjun Mu, Yanpeng Deng

“…The proposed method has the following advantages: (1) it has strong robustness and is capable of extracting complete craters under multiple illumination conditions, which makes it suitable for the extraction of large-scale planetary and lunar images; (2) the extracted crater edges are clear and complete and do not merge with the surrounding environment edge; and (3) it avoids the problem of parameter sensitivity that is present in a traditional CDA algorithm. The proposed method was verified using an image taken by the Chang’e-2 lunar probe, and a comparison with the traditional method based on morphology and adaptive Canny edge detection shows that the number of craters detected increases by more than 35%, while the computational efficiency is improved by more than 40%.…”
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Implementation and Performance Evaluation of Quantum Machine Learning Algorithms for Binary Classification by Surajudeen Shina Ajibosin, Deniz Cetinkaya

“…The results showed that quantum algorithms demonstrated competitive performance against their classical counterparts in terms of accuracy, while QSVC performed better than QNN. …”
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Function Synthesis Algorithm of RTD-Based Universal Threshold Logic Gate by Maoqun Yao, Kai Yang, Congyuan Xu, Jizhong Shen

“…The universal logic gate has become an important unit circuit of digital circuit design because of its powerful logic function, while the threshold logic gate is a suitable unit to design the universal logic gate, but the function synthesis algorithm for the n-variable logical function implemented by the RTD-based universal logic gate (UTLG) is relatively deficient. …”
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FDM-RTDETR: A Multi-Scale Small Target Detection Algorithm by Hongya Wang, Yongtao Yu, Zhaoxia Tang

“…To address challenges in uncrewed aerial vehicles (UAV) object detection including complex backgrounds, severe occlusion, dense small objects, and varying lighting conditions, we propose FDM-DETR, a novel detection algorithm specifically designed for small objects in UAV imagery. …”
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Spatiotemporal Mapping of Grazing Livestock Behaviours Using Machine Learning Algorithms by Guo Ye, Rui Yu

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A feature enhancement FCOS algorithm for dynamic traffic object detection by Tuqiang Zhou, Wei Liu, Haoran Li

“…Second, a dual attention module was designed to filter object feature information while reducing the amount of computation. Finally, in the detection part, the feature expression ability of shallow network was further enhanced by multi-scale feature fusion module, and the effectiveness of the proposed algorithm was verified using Cityscapes dataset. …”
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Lead Time for Cities of Northern India by Using Multiparameter EEW Algorithm by Rakhi Bhardwaj, Mukat Lal Sharma

“…The estimated lead time includes the time to reach S-wave after subtraction of the sum of P-wave arrival time at the station, time taken by EEW algorithm, transmission and processing delay. The study reveals that for Dehradun, Hardwar, Roorkee, Muzaffarnagar, Meerut, and Delhi the minimum calculated lead time is 5, 11, 20, 35, and 68 sec while the maximum lead time is 37, 36, 47, 59, and 90 sec, respectively. …”
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A Heuristic Algorithm for Locating Line-to-Line Faults in Photovoltaic Systems by Jia-Zhang Jhan, Bo-Hong Li, Hsun-Tsung Chiu, Hong-Chan Chang, Cheng-Chien Kuo

“…This paper proposes a heuristic algorithm for accurately locating such faults in PV arrays based on module group voltage measurements. …”
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Road Event Detection and Classification Algorithm Using Vibration and Acceleration Data by Abiel Aguilar-González, Alejandro Medina Santiago

“…In this work, we propose a Random Forest-based event classification algorithm designed to handle the unique patterns of vibration and acceleration data in road event detection for an urban traffic scenario. …”
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Quantum approximate optimization algorithms for maximum cut on low-girth graphs by Tongyang Li, Yuexin Su, Ziyi Yang, Shengyu Zhang

“…On the other hand, we conduct numerical experiments to compare the best-known classical local algorithms and QAOA with constant depth. Our results demonstrate that QAOA outperforms these best-known classical algorithms by 0.3% to 5.2% on several additive product graphs, while ma-QAOA further enhances this advantage by an additional 0.6% to 2.5%. …”
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Exploration-Driven Genetic Algorithms for Hyperparameter Optimisation in Deep Reinforcement Learning by Bartłomiej Brzęk, Barbara Probierz, Jan Kozak

“…This paper investigates the application of genetic algorithms (GAs) for hyperparameter optimisation in deep reinforcement learning (RL), focusing on the Deep Q-Learning (DQN) algorithm. …”
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Encryption Algorithm MLOL: Security and Efficiency Enhancement Based on the LOL Framework by Xinyue Zhang, Daoguang Mu, Wenzheng Zhang, Xinfeng Dong

“…It significantly simplifies security evaluation, making it suitable for automated analysis tools, and offers a feasible new approach for AEAD algorithm design.…”
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An Optimized Power Load Forecasting Algorithm Based on VMD‐SMA‐LSTM by Wei Liu, Fan Hua, Yongping Cui, Yangchao Xu, Han Liu

“…This study introduces an enhanced power load forecasting algorithm, integrating slime mould algorithm (SMA) and long short‐time memory (LSTM) to effectively address the hyperparameter challenges associated with LSTM, while also applying variational modal decomposition (VMD) to load forecasting. …”
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Developing an efficient algorithm for robust school bus routing with heterogeneous fleet by Mohamad Ali Movafaghpour

“…We propose a heuristic algorithm to generate extreme scenarios. Each scenario is generated in order to make the last found optimal solution into an infeasible one as much as possible.Findings: Experimental results show that deploying this novel algorithm for generating extreme scenarios, efficiently produces diverse scenarios. …”
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Research on Lightweight Small Object Detection Algorithm Based on Context Representation by Li Qiang, Cui Jianghui

“…This paper proposes a lightweight framework algorithm based on a contextual semantic fusion model, which is built upon the YOLOv7 model. …”
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Black box algorithms and the rights of individuals: no easy solution to the “explainability” problem by Jarek Gryz, Marcin Rojszczak

“…As a result, since the introduction of the GDPR there has been an ongoing discussion about not only the need to introduce such a right, but also about its scope and practical consequences in the digital world. While there is no doubt that the right to explanation may be very difficult to implement due to technical challenges, any difficulty in explaining how algorithms work cannot be considered a sufficient reason to completely abandon this legal safeguard. …”
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Edge detection of aerial images using artificial bee colony algorithm by Nurdan Akhan Baykan, Elif Deniz Yelmenoglu

“…In many studies, metaheuristic algorithms have been used for obtaining better results. …”
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Quantification of MODIS Land Surface Temperature Downscaled by Machine Learning Algorithms by Qi Su, Xiangchen Meng, Lin Sun, Zhongqiang Guo

“…This study presents a comprehensive evaluation of machine learning (ML)-based downscaling algorithms to enhance the spatial resolution of MODIS LST data from 960 m to 30 m, leveraging auxiliary variables including vegetation indices, terrain parameters, and land surface reflectance. …”
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