Optional and mandatory assignment strategies for dynamic vehicle routing with time windows by Mustafa Demirbilek

“…After optimizing the methods through sensitivity analyses, we evaluated their performance against Clarke and Wright's Savings Algorithm (CW) across various real-world-inspired scenarios, including different time window lengths, interarrival times, and region types. …”
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A speed optimization model for connected and autonomous vehicles at expressway tunnel entrance under mixed traffic environment. by Jianrong Cai, Yang Liu, Zhixue Li

“…Firstly, a CAV speed optimization model is established based on a shooting heuristic algorithm. The model targets the minimization of the weighted sum of the speed difference between adjacent vehicles and the time taken to reach the tunnel entrance. …”
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Reinforcement-Learning-Based Edge Offloading Orchestration in Computing Continuum by Ioana Ramona Martin, Gabriel Ioan Arcas, Tudor Cioara

“…The learning agent’s performance was evaluated using different hyperparameter configurations and varying episode lengths or knowledge graph model sizes. …”
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Graph-Based Semi-Supervised Learning with Bipartite Graph for Large-Scale Data and Prediction of Unseen Data by Mohammad Alemi, Alireza Bosaghzadeh, Fadi Dornaika

“…Lastly, most graph-based algorithms rely on affinity matrices that capture pairwise similarities across all data points, thus limiting their scalability to large-scale databases. …”
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Advanced hybrid computational analysis of febuxostat solubility using machine learning in supercritical processing method by Turki Al Hagbani, Rami M. Alzhrani, Majed Ahmed Algarni

“…The final models obtained were then evaluated and compared using different criteria. With the R2 criterion, the GPR predictive model has a score of 0.819 and the KNN model has a score of 0.854, but the voting model has a score of 0.980, which shows that the combined voting method using the other two models has a better result than both of them. …”
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A Novel Architecture for Addressing the Throughput Bottleneck in Spaceborne Solid-State Recorder for Electromagnetic Spectrum Sensors by Xufeng Li, Li Zhou, Yan Zhu

“…Data are distributed and stored in different memory regions controlled by separate FPGAs. …”
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Silent speech recognition using visual cascading fusion of tongue-lip movements based on pre-trained and fine-tuned model by Chongchong Yu, Xuening Wang, Zhaopeng Qian

“…Traditionally, in the field of SSR using tongue-lip visual information, data augmentation and feature fusion have received the most attention. Different from traditional approaches, we proposed to fuse the tongue-lip visual information by a cascading fusion algorithm to achieve “visual co-occurrence” of the tongue and lip frame by frame. …”
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An Optical Sensor for Measuring In-Plane Linear and Rotational Displacement by Suhana Jamil Ahamed, Michael Aaron McGeehan, Keat Ghee Ong

“…The reliability of the predicted linear and rotational displacement results was evaluated using two different color gradient wheels: a wheel with changing color hue, and another wheel with changing color hue and saturation. …”
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Angle Estimation for Range-Spread Targets Based on Scatterer Energy Focusing by Zekai Huang, Peiwu Jiang, Maozhong Fu, Zhenmiao Deng

“…Finally, the angle of the energy-focused signal is estimated using the sum-and-difference amplitude comparison method. The proposed method can effectively focus the scatterers’ energy. …”
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Using N-Version Architectures for Railway Segmentation with Deep Neural Networks by Philipp Jaß, Carsten Thomas

“…In addition, we implement a new method for evaluating and combining prediction confidence values in the N-version architecture during runtime. …”
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Lightweight terminal cross-domain authentication protocol in edge computing environment by Hongying ZHU, Xinyou ZHANG, Huanlai XING, Li FENG

“…Edge computing has gained widespread usage in intelligent applications due to its benefits, including low latency, high bandwidth, and cost-effectiveness.However, it also faces many security challenges due to its distributed, real-time, multi-source and heterogeneous data characteristics.Identity authentication serves as the initial step for terminal to access to the network and acts as the first line of defense for edge computing.To address the security issues in the edge computing environment, a terminal cross-domain authentication protocol suitable for the edge computing environment was proposed based on the ＆quot;cloud-edge-end＆quot; three-level network authentication architecture.Access authentication was implemented between terminals and local edge nodes based on the SM9 algorithm, and session keys were negotiated.The secret key was combined with symmetric encryption technology and hash function to achieve cross-domain authentication for the terminal.The pseudonym mechanism was used in the authentication process to protect the privacy of end users.The terminal only needs to register once, and it can roam randomly between different security domains.BAN logic was used to prove the correctness of the protocol and analyze its security.The results show that this protocol is capable of resisting common attacks in IoT scenarios, and it features characteristics such as single sign-on and user anonymity.The performance of the cross-domain authentication protocol was evaluated based on computational and communication costs, and compared with existing schemes.The experimental results show that this protocol outperforms other schemes in terms of computational and communication costs, making it suitable for resource-constrained terminal devices.Overall, the proposed protocol offers lightweight and secure identity authentication within edge computing environments.…”
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Energy aware resource management in 6G IoT networks using STAR RIS by Ali Alqahtani, Neeti Taneja, Ashu Taneja, Nayef Alqahtani

“…The system spectral efficiency and energy efficiency is evaluated for different RIS elements N and transmit power levels $$P_{max}$$ . …”
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CAPSE-ViT: A Lightweight Framework for Underwater Acoustic Vessel Classification Using Coherent Spectral Estimation and Modified Vision Transformer by Najamuddin NAJAMUDDIN, Usman Ullah SHEIKH, Ahmad Zuri SHA’AMERI

“…The major challenge is inserting area-specific understanding into ML frameworks to extract features that effectively distinguish between different vessel types. In this study, we propose a model that uses the coherently averaged power spectral estimation (CAPSE) algorithm. …”
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Transcriptome signature for multiple biotic and abiotic stress in barley (Hordeum vulgare L.) identifies using machine learning approach by Bahman Panahi

“…The C4.5 algorithm demonstrated superior accuracy in predicting stress-responsive signatures. …”
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Mapping Soil Available Nitrogen Using Crop-Specific Growth Information and Remote Sensing by Xinle Zhang, Yihan Ma, Shinai Ma, Chuan Qin, Yiang Wang, Huanjun Liu, Lu Chen, Xiaomeng Zhu

“…These remote sensing variables were combined with soil sample data, crop type information, and crop growth period data as predictive factors and input into a Random Forest (RF) model optimized using the Optuna hyperparameter tuning algorithm. The accuracy of different strategies was evaluated using 5-fold cross-validation. …”
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BIMSSA: enhancing cancer prediction with salp swarm optimization and ensemble machine learning approaches by Pinakshi Panda, Sukant Kishoro Bisoy, Amrutanshu Panigrahi, Abhilash Pati, Bibhuprasad Sahu, Zheshan Guo, Haipeng Liu, Prince Jain

“…Then, majority voting was used to build an ensemble of the top three algorithms. The ensemble ML-based model BIMSSA was evaluated using microarray data from four different cancer types: Adult acute lymphoblastic leukemia and Acute myelogenous leukemia (ALL-AML), Lymphoma, Mixed-lineage leukemia (MLL), and Small round blue cell tumors (SRBCT).ResultsIn terms of accuracy, the proposed BIMSSA (Boruta + IMRMR + SSA) achieved 96.7% for ALL-AML, 96.2% for Lymphoma, 95.1% for MLL, and 97.1% for the SRBCT cancer datasets, according to the empirical evaluations.ConclusionThe results show that the proposed approach can accurately predict different forms of cancer, which is useful for both physicians and researchers.…”
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Needle detection and localisation for robot‐assisted subretinal injection using deep learning by Mingchuan Zhou, Xiangyu Guo, Matthias Grimm, Elias Lochner, Zhongliang Jiang, Abouzar Eslami, Juan Ye, Nassir Navab, Alois Knoll, Mohammad Ali Nasseri

“…The algorithm was evaluated by comparing the depth of the top and bottom edge of the predicted bounding box to the ground truth. …”
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Identification of anoikis-related genes classification patterns and immune infiltration characterization in chronic rhinosinusitis with nasal polyps based on machine learning by Ziqi Chen, Lingmei Qu, Qing Hao, Shuang Teng, Shuo Liu, Qin Wu, Hongtian Yi, Xianji Shen, Liang Li, Zhaonan Xu, Yanan Sun

“…Immune cell infiltration was analysed using the CIBERSORT algorithm. CRSwNP samples were classified via consensus clustering. …”
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Analysis of Blockchain-Technology by Danylo Dvorchuk, Iryna Shpinareva

“…The study explores the comparative advantages and limitations of different blockchain architectures and evaluates emerging optimization techniques such as hybrid consensus algorithms and artificial intelligence-based enhancements. …”
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Building radiomics models based on ACR TI-RADS combining clinical features for discriminating benign and malignant thyroid nodules by Xingxing Chen, Xingxing Chen, Lili Zhang, Bin Chen, Jiajia Lu

“…A total of 107 radiomics features were extracted from the US images, and the radiomics score (Rad-score) was constructed using the Least Absolute Shrinkage and Selection Operator (LASSO) algorithm. Different models were created using logistic regression, including the clinic-ACR score (Clin+ACR), clinic-Rad score (Clin+Rad), ACR score-Rad score (ACR+Rad), and combined clinic-ACR score-Rad score (Clin+ACR+Rad). …”
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