Dual Strategy of Reconfiguration with Capacitor Placement for Improvement Reliability and Power Quality in Distribution System by Ali Nasser Hussain, Wathiq Rafa Abed, Mohanad Muneer Yaqoob

“…The MOF was formulated to improve the power quality by increasing the voltage buses and reducing the power losses. While the constraints include limits of system reliability indices to provide optimal constraints on negative interactions of power quality. …”
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Artificial Intelligence‐Based Approaches for AAV Vector Engineering by Fangzhi Tan, Yue Dong, Jieyu Qi, Wenwu Yu, Renjie Chai

“…The advancement of artificial intelligence (AI), particularly machine learning, offers significant potential to accelerate capsid optimization while reducing development time and manufacturing costs. …”
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SpecPCM: A Low-Power PCM-Based In-Memory Computing Accelerator for Full-Stack Mass Spectrometry Analysis by Keming Fan, Ashkan Moradifirouzabadi, Xiangjin Wu, Zheyu Li, Flavio Ponzina, Anton Persson, Eric Pop, Tajana Rosing, Mingu Kang

“…We further optimize multilevel PCM devices for different tasks by using different materials. …”
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A Solution for Predicting the Timespan Needed for Grinding Roller Bearing Rings by Cezarina Chivu, Mitica Afteni, Gabriel Radu Frumusanu, Florin Susac

“…The optimal management of manufacturing processes can be achieved through a set of optimal decisions, which must be made to choose the best method to follow every time the process planner reaches a point when several potential manufacturing paths branch off. …”
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An efficient approach towards index structures for skyline queries by Huaiguang Song, Zhongbo Wu, Binglei Guo, Zhao Wu, Min Wang

“…Extensive experiments show that U-INDG outperforms the most efficient index-based skyline algorithms currently available. It significantly reduces query time across various types of datasets, with speedups ranging from approximately 2.4 $$\times $$ × to 7.8 $$\times $$ × compared to state-of-the-art algorithms, while ensuring stable performance.…”
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Learning efficient haptic shape exploration with a rigid tactile sensor array. by Sascha Fleer, Alexandra Moringen, Roberta L Klatzky, Helge Ritter

“…This environment contains a set of rigid static objects representing a selection of one-dimensional local shape features embedded in a 3D space: an edge, a flat and a convex surface. The proposed algorithm simultaneously optimizes main perception-action loop components: feature extraction, integration of features over time, and the control strategy, while continuously acquiring data online. …”
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DeepSARFlood: Rapid and automated SAR-based flood inundation mapping using vision transformer-based deep ensembles with uncertainty estimates by Nirdesh Kumar Sharma, Manabendra Saharia

“…Additionally, we develop a novel gain algorithm to identify diverse ensemble members and estimate uncertainty through deep ensembles. …”
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Machine learning, clinical-radiomics approach with HIM for hemorrhagic transformation prediction after thrombectomy and treatment by Sheng Hu, Junyu Liu, Jiayi Hong, Yuting Chen, Ziwen Wang, Jibo Hu, Shiying Gai, Xiaochao Yu, Jingjing Fu

“…The support vector machine (SVM) was the optimal ML algorithm for constructing the models. …”
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Innovative Treatment of Combat-Related Extraperitoneal Penetrating Rectal Injury with Intraluminal Vacuum Therapy: A Case Report by Yafa Shani Parnasa, Oded Cohen-Arazi, Gad Marom, Mahmoud Abu-Gazala, Noam Shussman, Miklosh Bala

“…This case highlights ILVT as a novel method for managing complicated blast-related rectal injuries. While there are limited publications on combat-related penetrating rectal injuries that provide evidence-based guidelines, we suggest an aggressive surgical approach combined with negative pressure wound therapy for optimal patient outcomes.…”
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Advances in UAV Path Planning: A Comprehensive Review of Methods, Challenges, and Future Directions by Wenlong Meng, Xuegang Zhang, Lvzhuoyu Zhou, Hangyu Guo, Xin Hu

“…A fundamental aspect of UAV autonomy lies in route optimization, which determines efficient paths while considering factors like mission goals, safety, and power consumption. …”
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Implementation of XGBoost Models for Predicting CO₂ Emission and Specific Tractor Fuel Consumption by Nebojša Balać, Zoran Mileusnić, Aleksandra Dragičević, Mihailo Milanović, Andrija Rajković, Rajko Miodragović, Olivera Ećim-Đurić

“…The CO₂ prediction model achieved an accuracy exceeding 80%, while the model for fuel consumption reached over 65%. …”
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The role of precision tool positioning in enhancing machining accuracy by Tuyboyov Oybek, Baydullayev Azamat, Jeltuxin Andrey, Muxiddinov Zayniddin

“…Hybrid optimization techniques, including genetic algorithms, effectively balanced the trade-off between precision and productivity, achieving a 10% reduction in production time without sacrificing accuracy. …”
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Design of a Heterogeneous-Based Network Intrusion Detection System and Compiler by Zhigui Lin, Xiaofeng Zhang, Qi Liu, Jun Cui

“…We construct an FPGA + CPU heterogeneous detection system featuring a five-tuple segmented matching architecture, which integrates hash bitmap and shift-or algorithms to achieve fast-pattern matching. A hardware compiler supporting 10,000+ detection rules is developed, enhancing hardware adaptability through packet optimization and mask compilation. …”
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Survey of Quantum Generative Adversarial Networks (QGAN) to Generate Images by Mohammadsaleh Pajuhanfard, Rasoul Kiani, Victor S. Sheng

“…In addition, developing QGANs can generate and train parameters in quantum approximation optimization algorithms. One of the useful applications of QGAN is generating medical datasets that can generate medical images from limited datasets to train specific medical models for the recognition of diseases.…”
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Linking Animal Feed Formulation to Milk Quantity, Quality, and Animal Health Through Data-Driven Decision-Making by Oreofeoluwa A. Akintan, Kifle G. Gebremedhin, Daniel Dooyum Uyeh

“…This review connects data-driven decision-making in optimizing feed formulation to enhance milk quantity and quality while addressing animal health implications. …”
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A Spatial–Temporal Time Series Decomposition for Improving Independent Channel Forecasting by Yue Yu, Pavel Loskot, Wenbin Zhang, Qi Zhang, Yu Gao

“…In this paper, we improve the performance of single-channel forecasting algorithms by designing an interpretable front-end that extracts the spatial–temporal components from the input multivariate time series. …”
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Enhanced CLIP-GPT Framework for Cross-Lingual Remote Sensing Image Captioning by Rui Song, Beigeng Zhao, Lizhi Yu

“…Remote Sensing Image Captioning (RSIC) aims to generate precise and informative descriptive text for remote sensing images using computational algorithms. Traditional “encoder-decoder” approaches face limitations due to their high training costs and heavy reliance on large-scale annotated datasets, hindering their practical applications. …”
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The Neural Frontier of Future Medical Imaging: A Review of Deep Learning for Brain Tumor Detection by Tarek Berghout

“…Some models integrate with Internet of Things (IoT) frameworks or federated learning for real-time diagnostics and privacy, often paired with optimization algorithms. However, the adoption of eXplainable AI (XAI) remains limited, despite its importance in building trust in medical diagnostics. …”
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Recent Advances in In Situ 3D Surface Topographical Monitoring for Additive Manufacturing Processes by Vignesh Suresh, Badrinath Balasubramaniam, Li-Hsin Yeh, Beiwen Li

“…Furthermore, the article discusses the state-of-the-art advancements in closed-loop feedback control systems, sensor fusion, and machine learning algorithms to integrate 3D surface data with various process signatures to dynamically adjust laser parameters and scan strategies. …”
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Gradient pooling distillation network for lightweight single image super-resolution reconstruction by Zhiyong Hong, GuanJie Liang, Liping Xiong

“…Extensive experimental results demonstrate that our proposed method achieves competitive performance while maintaining relatively low resource occupancy of the model. …”
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