Advancements and challenges in inverse lithography technology: a review of artificial intelligence-based approaches by Yixin Yang, Kexuan Liu, Yunhui Gao, Chen Wang, Liangcai Cao

“…The review tracks recent advancements of ILT in model improvement and algorithmic efficiency. Challenges such as extended computational runtimes and mask-writing complexities are summarized, with potential solutions discussed. …”
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Polymer electrolyte membrane fuel cell performance Revolutionized: Artificial intelligence-validated asymmetric flow channels enhance mass transport via hybrid analytical-numerical... by Nima Ahmadi, Ghader Rezazadeh

“…Experimental validation confirms a current density improvement of up to 5.6 % over conventional designs, while Artificial Intelligence (AI)-driven optimization via a hybrid Convolutional Neural Network and Genetic Algorithm independently identifies the same optimal configuration. …”
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Scheduling Approach for the Simulation of a Sustainable Resource Supply Chain by Henning Strubelt, Sebastian Trojahn, Sebastian Lang, Abdulrahman Nahhas

“…This paper deals with the optimization of logistics processes at an underground waste storage site by means of solving scheduling issues and reducing setup times, with the help of a simulation model. …”
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Two-Layer Predictive Control of a Continuous Biodiesel Transesterification Reactor by Hongyan Shi, Dingding Wang, Decheng Yuan, Tianran Wang

“…Based on a validated mechanistic model, the least squares (LS) algorithm is used to identify the finite step response (FSR) process model adapted in the controller. …”
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Predicted indirectly recognizable HLA epitopes scores and clinical outcomes after haploidentical stem cell transplantation in pediatric patients with relapsed neuroblastoma by Eun Seop Seo, Eun Seop Seo, In Hwa Jeong, In Hwa Jeong, Hee Young Ju, Ju Kyung Hyun, Ji Won Lee, Keon Hee Yoo, Won Young Heo, Ki Woong Sung, Hee Won Cho, Eun-Suk Kang

“…IntroductionThe Predicted Indirectly ReCognizable HLA Epitopes (PIRCHE) model is a recently developed algorithm that predicts indirect T-cell recognition by calculating the number of such epitopes in donor-recipient pairs.MethodsIn this study, the clinical significance of PIRCHE was evaluated in pediatric patients with relapsed/progressed neuroblastoma undergoing haploidentical stem cell transplantation (haplo-SCT).ResultsA higher PIRCHE-I score was associated with faster platelet recovery (P = 0.007) and lower incidence of hemorrhagic cystitis (13% vs. 41%, P = 0.028) and invasive fungal infections (0% vs. 18%, P = 0.045). …”
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sEMG-based gesture recognition using multi-stream adaptive CNNs with integrated residual modules by Yutong Xia, Dawei Qiu, Cheng Zhang, Jing Liu

“…In the future, in order to deal with differences in sEMG signals caused by variations among individuals, a universal multi-gesture recognition algorithm should be developed. Meanwhile, the model should focus on optimizing and streamlining the network to reduce computational load.…”
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Research on Fuzzy Decision-Making Method of Task Allocation for Ship Multiagent Collaborative Design by Jinghua Li, Yiying Wang, Boxin Yang, Qinghua Zhou, Feihui Yuan

“…Finally, through example verification and comparative analysis with the Round-Robin algorithm (RR) and the Weighted Round-Robin (WRR) algorithm, the validity, feasibility, and stability of the multidesign agent-task allocation decision-making method proposed in this paper are verified, and it is proved that the task allocation method takes the bilateral needs of the task and the design agent into account, solves the optimal allocation strategy of collaborative design tasks, and realizes the balanced allocation between the ship collaborative design task and the design agent.…”
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ACCURACY ANALYSIS OF GALILEO CODE POSITIONING FOR UAV by Klaudia CYBULSKA-GAC, Kamil KRASUSKI, Adam CIEĆKO

“…The Galileo SPP code method algorithm was used to determine the UAV coordinates. …”
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The Adversarial Robust and Generalizable Stereo Matching for Infrared Binocular Based on Deep Learning by Bowen Liu, Jiawei Ji, Cancan Tao, Jujiu Li, Yingxun Wang

“…To compute the matching cost volume, we apply the multi-scale census transform to the input stereo images. …”
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Human Action Recognition Method Based on Multi-channel Fusion by Zhiyong TAO, Xijun GUO, Xiaokui REN, Ying LIU, Zemin WANG

“…Balancing the characteristics of each channel further improves the accuracy of action recognition.Results and Discussion Comprehensive experiments are conducted on public datasets and in real-world environments to evaluate the effectiveness of the proposed model. …”
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A Synergistic Approach to Colon Cancer Detection: Leveraging EfficientNet and NSGA-II for Enhanced Diagnostic Performance by Noushin Saba, Afia Zafar, Mohsin Suleman, Kainat Zafar, Shahneer Zafar, Adil Ali Saleem, Hafeez Ur Rehman Siddiqui, Muhammad Iqbal, Syed Sajid Ullah

“…We employed EfficientNet, a state-of-the-art convolutional neural network, to extract intricate features from histopathological images, alongside the Non-dominated Sorting Genetic Algorithm II for optimal feature selection. This hybrid approach significantly enhances diagnostic performance while reducing computational complexity. …”
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Fingerprint Classification Based on Multilayer Extreme Learning Machines by Axel Quinteros, David Zabala-Blanco

“…While advanced classification algorithms, including support vector machines (SVMs), multilayer perceptrons (MLPs), and convolutional neural networks (CNNs), have demonstrated near-perfect accuracy (approaching 100%), their high training times limit their widespread applicability across institutions. …”
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Lightweight deep neural network for contour detection and extraction of wheat spikes in complex field environments by Xin Xu, Haiyang Zhang, Jiangchuan Lu, Ziyi Guo, Juanjuan Zhang, Jibo Yue, Hongbo Qiao, Xinming Ma

“…Results Independent test set validation shows the improved model achieves 83.9% contour integrity recognition rate and 92.4% mAP@0.5, exceeding baseline by 3.2 and 5.3% points respectively. …”
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Using Deep Learning Techniques to Enhance Blood Cell Detection in Patients with Leukemia by Mahwish Ilyas, Muhammad Bilal, Nadia Malik, Hikmat Ullah Khan, Muhammad Ramzan, Anam Naz

“…This supports early diagnosis and monitoring, which leads to more effective treatments and improved results for cancer patients. To accomplish this task, we use digital image processing techniques and then apply the convolutional neural network (CNN) deep learning algorithm to blood sample images. …”
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Machine learning for defect condition rating of wall wooden columns in ancient buildings by Yufeng Li, Wu Ouyang, Zhenbo Xin, Houjiang Zhang, Shuqi Sun, Dian Zhang, Wenbo Zhang

“…The RBF neural network model achieved the highest accuracy (94.57 %) on the feature fusion dataset, while Grey Wolf Optimizer (GWO) optimization further improved accuracy to 96.74 %. …”
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Advanced Interpretation of Bullet-Affected Chest X-Rays Using Deep Transfer Learning by Shaheer Khan, Nirban Bhowmick, Azib Farooq, Muhammad Zahid, Sultan Shoaib, Saqlain Razzaq, Abdul Razzaq, Yasar Amin

“…Special deep learning algorithms went through a process of optimization before researchers improved their ability to detect and place objects. …”
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A New Efficient Classifier for Bird Classification Based on Transfer Learning by Lesia Mochurad, Stanislav Svystovych

“…An optimal model architecture was built using the transfer learning approach. …”
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A Two-Step Approach for Airborne Delay Minimization Using Pretactical Conflict Resolution in Free-Route Airspace by Ramazan Kursat Cecen, Cem Cetek

“…According to this comparison, both metaheuristics algorithms produce near optimal solutions in a reasonably short time. …”
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Deep Reinforcement Learning-Based Attention Decision Network for Agile Earth Observation Satellite Scheduling by Dongning Liu, Guanghui Zhou

“…Moreover, a start-time-shift-based local search is proposed to improve the observation plan generated by the ADN model. …”
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Enhanced YOLO11 for lightweight and accurate drone-based maritime search and rescue object detection. by Beigeng Zhao, Jiawen Zhao, Rui Song, Lizhi Yu, Xia Zhang, Jiren Liu

“…In the lightweight complexity range, the proposed model achieves a relative accuracy improvement of 20.85% to 43.70% compared to these state-of-the-art methods. …”
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