Optimal Guidance Law for Critical Safe Miss Distance Evasion by Chengze Wang, Jiamin Yan, Rui Lyu, Zhuo Liang, Yang Chen

“…If the evader effectively utilizes perceptual information, they can narrowly escape the lethal zone while minimizing energy consumption, thereby avoiding excessive and unnecessary maneuvers. …”
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Patterns of Open Innovation Between Industry and University: A Fuzzy Cluster Analysis Based on the Antecedents of Their Collaboration by Marius Băban, Călin Florin Băban

“…Using the typical value of the fuzzifier factor of this algorithm equal to 2, three distinct clusters were identified with respect to these antecedents as low, insecure, and responsive open innovators. …”
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Impact of the Global Financial Crisis on the Business Cycle in the Visegrad Group by Bartosz Pawęta

“…Research Design & Methods: Visegrad Group’s business cycles were determined by employing Hodrick and Prescott filter to extract cyclical fluctuations, while Bry and Boschan algorithm was applied to identify the turning points of the cycles. …”
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Integrating distributed photovoltaic and energy storage in 5G networks for sustainable IoT applications by Yi Zhong, Yiting Wu, Yi Zheng, Xiaohu Ge

“…By utilizing IoT characteristics, we propose a dual-layer modeling algorithm that maximizes carbon efficiency and return on investment while ensuring service quality. …”
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Automatic Optimal Design Method for Minimum Total Resistance Hull Based on Enhanced FFD Method by Shuhui Guo, Baoji Zhang, Zheng Tian, Jie Liu, Hailin Tang

“…To this end, an integrated, fully automated optimization program was developed based on Python, incorporating Enhanced Free-Form Deformation (FFD) technology, scripted CFD numerical evaluation, and the Particle Swarm Optimization (PSO) algorithm. This program allowed precise control of hull form, improving efficiency while reducing costs. …”
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Neural Network-Based Imitation Learning for Approximating Stochastic Battery Management Systems by Andrea Pozzi, Alessandro Incremona, Daniele Toti

“…Specifically, the proposed method leverages the Dataset Aggregation algorithm to overcome the issue of distributional shift, a common limitation in imitation learning frameworks. …”
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Dynamic trajectories of land use and land cover changes in Lombok Island, West Nusa Tenggara, Indonesia by H. Oğuz Çoban, Miftahul Irsyadi Purnama

“…These findings underscore the urgent need for sustainable land management policies to balance development and ecological preservation while mitigating future forest losses.…”
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Research on wear and grinding models of high-speed turnouts based on semi-Hertz contact by Jincheng Li, Yayun Qi, Pengpeng Wu, Junjun Ding, Haohao Ding

“…The ideal profile update step for the turnout rail is 0.05 mm, and the adaptive filtering algorithm, tailored to the turnout characteristics, smooths wear distribution effectively while retaining crucial data features. …”
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Scalable THz Network-On-Chip Architecture for Multichip Systems by Esmaeel Tahanian, Alireza Tajary, Mohsen Rezvani, Mansoor Fateh

“…While THz wireless network-on-chip (WiNoC) introduces considerably high bandwidth, due to the high path loss, it cannot be used for communication between far apart nodes, especially in a multichip architecture. …”
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A Simulation Based Metaheuristics for Capacitated Vehicle Routing Problem by Tamara Latifah Jasmine, Heru Purboyo Hidayat Putro, Niken Prilandita, Gatot Yudoko

“…The methodology utilizes a simheuristics approach, integrating a Genetic Algorithm (GA) to determine optimal routing solutions, while employing Discrete Event Simulation (DES) to incorporate key economic, environmental, and social variables. …”
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Autonomous defect estimation in aluminum plate and prognosis through stochastic process modeling by Mrudul Jambulkar, Shivam Ojha, Amit Shelke, Anowarul Habib

“…Scanning Acoustic Microscopy (SAM) images serve as the data source, from which comprehensive features are extracted in time, frequency, and time-frequency domains using Short-Time Fourier Transform (STFT). The K-means algorithm enables precise localization and sizing of surface defects without prior labels, while the gamma process captures the stochastic progression of damage over time. …”
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Dynamic Coal Flow-Based Energy Consumption Optimization of Scraper Conveyor by Qi Lu, Yonghao Chen, Xiangang Cao, Tao Xie, Qinghua Mao, Jiewu Leng

“…The multi-objective optimization model for energy consumption is solved using the NSGA-II-ARSBX algorithm, yielding a 33.7% reduction in energy consumption, while the lump coal area is reduced by 27.7%, indicating a trade-off between energy efficiency and coal fragmentation. …”
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Deep learning-based energy efficient LSFD weights prediction for user centric cell free massive MIMO system by Moustafa Mohamed, Salwa El-Ramly, Bassant Abdelhamid

“…These models are trained using dataset generated from heuristic sparse LSFD optimization algorithm, this allows the models to learn the sparsity nature of the system and apply AP-UE association based on the values of the predicted LSFD weights at the receiver side while using the large scale fading coefficients as the models’ input. …”
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A cartographic generalization method for 3D visualization of trajectories in space–time cubes: case study of epidemic spread by Fei Yang, Jie Shen, Fengzhen Zhu, Junrui Zhang

“…The proposed method incorporates a 3D generalization algorithm that mitigates visual stickiness, while leveraging a 3D line field visualization technique to optimize opacity, thereby minimizing visual occlusion and spatial clutter. …”
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A Correlational Study on Architectural Design and Thermal Distribution Patterns Using a Novel Multi-Terminal Approach in Cylindrical Li-Ion Cell-Integrated Battery Packs by Sagar D, Raja Ramar, Shama Ravichandran

“…Finally, while forced air cooling effectively lowers peak temperature, it is insufficient in addressing thermal distribution and heat spot formation. …”
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End-to-end deep learning pipeline for real-time Bragg peak segmentation: from training to large-scale deployment by Cong Wang, Valerio Mariani, Frédéric Poitevin, Matthew Avaylon, Jana Thayer

“…We present an end-to-end deep learning pipeline with three key components: (1) a data engine that combines traditional algorithms with our peak matching algorithm to generate high-quality training data at scale, (2) a modular architecture that scales from a few million to hundreds of million parameters, enabling us to train large expert-level models offline while deploying smaller, distilled models at the edge, and (3) a decoupled producer-consumer architecture that separates specialized data source layer from model inference, enabling flexible deployment across diverse computing environments. …”
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Elevator Control Simulation Using Fuzzy Logic Management by Mehr Ali Qasimi, Asmatullah Nashir

“…This work addresses the problem by developing an elevator group controller using a fuzzy algorithm. This project is designed to handle the necessary passenger traffic density while maintaining acceptable passenger waiting times by integrating a fuzzy controller into an elevator system. …”
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CriSALAD: Robust Visual Place Recognition Using Cross-Image Information and Optimal Transport Aggregation by Jinyi Xu, Yuhang Ming, Minyang Xu, Yaqi Fan, Yuan Zhang, Wanzeng Kong

“…Specifically, we adapt pre-trained VFMs for VPR by incorporating a parameter-efficient adapter inspired by Xception, ensuring effective task adaptation while preserving computational efficiency. Additionally, we employ the Sinkhorn Algorithm for Locally Aggregated Descriptors (SALAD) as a global descriptor to enhance place recognition accuracy. …”
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Towards Robust Speech Models: Mitigating Backdoor Attacks via Audio Signal Enhancement and Fine-Pruning Techniques by Heyan Sun, Qi Zhong, Minfeng Qi, Uno Fang, Guoyi Shi, Sanshuai Cui

“…Second, we apply an adaptive fine-pruning algorithm to selectively deactivate malicious neurons while preserving the model’s linguistic capabilities. …”
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Two-Phase Globally Coupled Low-Density Parity Check Decoding Aided with Early Termination and Forced Convergence by Kun Zhu, Hongwen Yang

“…To enhance the decoding efficiency of Globally Coupled (GC) LDPC codes, we incorporated Early Termination (ET) and Forced Convergence (FC) into the local/global two-phase decoding algorithm to expedite the decoding process. The two-phase decoding scheme integrates the ET technique to halt unnecessary iterations in the local decoding phase while employing the FC technique to accelerate convergence in the global phase decoding. …”
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