Computer Vision-Based Concrete Crack Identification Using MobileNetV2 Neural Network and Adaptive Thresholding by Li Hui, Ahmed Ibrahim, Riyadh Hindi

“…A dataset including 40,000 images was adopted and preprocessed using various thresholding techniques, of which adaptive thresholding was selected for developing the crack evaluation algorithm. While both the convolutional neural network (CNN) and MobileNetV2 indicated comparable accuracy levels in crack detection, the MobileNetV2 model’s significantly smaller size makes it a more efficient selection for crack detection using mobile devices. …”
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Recursive Objective Space Exploration (ROSE): A computationally efficient deterministic approach for bi-objective optimization. by Ihab Hashem, Viviane De Buck, Seppe Seghers, Jan Van Impe

“…Our approach is inspired by how plants efficiently explore physical space in search of light energy, balancing exploration and exploitation while minimizing biomass cost. The algorithm navigates the objective space without revisiting previously explored areas by solving intermediate SOOPs visualized as branches within this space. …”
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Classification of skin diseases with deep learning based approaches by Merve Okumuş Sarı, Kübra Keser

“…When SVM classification with the Relief algorithm was used for the same rates, the accuracy rate was 92.10%. …”
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Nonlinear Sliding-Mode Super-Twisting Reaching Law for Unmanned Surface Vessel Formation Control Under Coupling Deception Attacks by Yifan Wang, Qiang Zhang, Yaping Zhu, Yancai Hu, Xin Hu

“…Finally, the stability of the algorithm is verified through Lyapunov theory. Under the same coupling deception probability, the nonlinear sliding-mode super-twisting reaching law algorithm designed in this paper enables the leader ship and each follower ship to reach stability within about 12s, and the formation system maintains its formation while also improving the control accuracy of each individual ship.…”
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Optimal micro-grid battery scheduling within a comprehensive smart pricing scheme by Mohammed Ashraf Ali, Ahmad H. Besheer, Hassan M. Emara, Ahmed Bahgat

“…Abstract The challenge of optimizing battery operating revenue while mitigating aging costs remains inadequately addressed in current literature. …”
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Dose distribution comparison using image registration principles by Meryeme Bellahsaouia, Ibtissam Zidouh, Ouadie Kabach, Wafae Chfeq, Assia Arctout, Taher Elkhoukhi, Elmahjoub Chakir

“…This study introduces a novel algorithm based on image registration principles to address these limitations. …”
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Advancing low‐light object detection with you only look once models: An empirical study and performance evaluation by Samier Uddin Ahammad Shovo, Md. Golam Rabbani Abir, Md. Mohsin Kabir, M. F. Mridha

“…The ExDark dataset is a dataset that consists of adequate low‐light images, modified to simulate realistic low‐light scenarios, and employed for evaluation. The deep learning algorithm optimises YOLO's architecture for low‐light detection by adapting the network structure and training strategies while preserving the algorithm's integrity. …”
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Reconstruction for Rolling Bearing Vibration Signals Integrating 5G-NR-LDPC Codes and Weighted Compressed Sensing by Chao Wang, Hua Xu, Guangxing Ni, Wenjuan Shi

“…Simulation results validate the effectiveness of the proposed 5G-WCS algorithm, demonstrating its capability to achieve desirable quality of signal reconstruction while maintaining high compression of rolling bearing vibration signals. …”
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Program Scheduling With Multi-Skill and External Resource Coordination Consideration Using Improved NSGA-II: Case Study by Heng Zhang, Jingbo Zhou, Huaying Ruan, Yixuan Qin

“…Subsequently, an enhanced fast and elitist non-dominated sorting genetic algorithm (NSGA-II) was developed by integrating heuristic-based population initialization and adaptive genetic strategies. …”
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Joint Optimization of Berths and Quay Cranes Considering Carbon Emissions: A Case Study of a Container Terminal in China by Houjun Lu, Xiao Lu

“…The increasing complexity of berth allocation now requires compliance to vessel service standards while controlling carbon emissions. This study presents an integrated model that incorporates tidal factors into the joint optimization of berth and quay crane operations, addressing both service standards and emissions during port stays and crane activities, and further designs a PSO-GA hybrid algorithm, combining particle swarm optimization (PSO) with crossover and mutation operators from a genetic algorithm (GA), to enhance optimization accuracy and efficiency. …”
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A Hybrid Deep Learning Model for UAV Path Planning in Dynamic Environments by Junchi Zhang, Yanning Xian, Xun Zhu, Hongtao Deng

“…Thus, an effective path-planning algorithm is essential for navigating UAVs through complex terrains. …”
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Coverage optimization and node minimization in WSNs: an enhanced hybrid PSO approach with spatial position encoding by Yinghua Tong, Lianhai Lin, Liqin Tian, Zhigang Wang, Wenxing Wu, Junyi Wu

“…This paper presents an enhanced hybrid particle swarm optimization (EHPSO) algorithm that incorporates a spatial position encoding (SPE) strategy to optimize coverage while dynamically adjusting the number of sensors deployed in WSNs. …”
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Efficient search, mapping, and optimization of multi‐protein genetic systems in diverse bacteria by Iman Farasat, Manish Kushwaha, Jason Collens, Michael Easterbrook, Matthew Guido, Howard M Salis

“…We developed a computational approach to build predictive models and identify optimal sequences and expression levels, while circumventing combinatorial explosion. Maximally informative genetic system variants were first designed by the RBS Library Calculator, an algorithm to design sequences for efficiently searching a multi‐protein expression space across a > 10,000‐fold range with tailored search parameters and well‐predicted translation rates. …”
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Prediction model of middle school student performance based on MBSO and MDBO-BP-Adaboost method by Rencheng Fang, Tao Zhou, Baohua Yu, Zhigang Li, Long Ma, Tao Luo, Yongcai Zhang, Xinqi Liu

“…Predictions of student performance are important to the education system as a whole, helping students to know how their learning is changing and adjusting teachers' and school policymakers' plans for their future growth. …”
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Diagnostic Utility of Broad Range Bacterial 16S rRNA Gene PCR with Degradation of Human and Free Bacterial DNA in Bloodstream Infection Is More Sensitive Than an In-House Developed... by Petra Rogina, Miha Skvarc, David Stubljar, Romina Kofol, Achim Kaasch

“…Broad range 16S rRNA gene PCR was performed from whole blood (SepsiTest) or blood plasma (IHP) and compared to blood culture results. …”
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Phase Diagram of Extensive-Rank Symmetric Matrix Denoising beyond Rotational Invariance by Jean Barbier, Francesco Camilli, Justin Ko, Koki Okajima

“…In this case, the information-theoretic limits and an efficient Bayes-optimal denoising algorithm, called the rotational invariant estimator, are known. …”
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Autonomous and adaptive congestion control for machine-type communication in cellular network by Qi Pan, Xiangming Wen, Zhaoming Lu, Wenpeng Jing, Haijun Zhang

“…Simultaneously, an effective estimation algorithm for the traffic load of base stations is also designed to represent the network traffic load without frequent information exchanges among devices or base stations. …”
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Several Theses in Support of an Integrative Understanding of the Administrative Process by P. I. Kononov

“…Examples are given that show the existence of a common algorithm for resolving administrative cases by both administrative-public bodies and courts, which indicates a single procedural nature of the corresponding types of judicial and extrajudicial activities and the absence of fundamental differences between them. …”
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Mixed Event-Frame Vision System for Daytime Preceding Vehicle Taillight Signal Measurement Using Event-Based Neuromorphic Vision Sensor by Zhengfa Liu, Guang Chen, Ya Wu, Jiatong Du, Jörg Conradt, Alois Knoll

“…The event-based neuromorphic vision sensor is a bioinspired sensor that records pixel-level intensity changes, called events, as well as the whole picture of the scene. The events naturally respond to illumination changes (such as the ON and OFF state of taillights) in the scene with very low latency. …”
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Design of FPGA-Based Accelerator for Convolutional Neural Network under Heterogeneous Computing Framework with OpenCL by Li Luo, Yakun Wu, Fei Qiao, Yi Yang, Qi Wei, Xiaobo Zhou, Yongkai Fan, Shuzheng Xu, Xinjun Liu, Huazhong Yang

“…Among these, FPGA can accelerate the computation by mapping the algorithm to the parallel hardware instead of CPU, which cannot fully exploit the parallelism. …”
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