Location-Aware Cross-Layer Design Using Overlay Watermarks by Xianbin Wang, Paul Ho, Yiyan Wu

“…Therefore, efficient collaborative signal processing algorithms that consume less energy for computation and less bandwidth for communication are needed. …”
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Generalizability of machine learning models for diabetes detection a study with nordic islet transplant and PIMA datasets by Dinesh Chellappan, Harikumar Rajaguru

“…Researchers utilizing a hybrid feature extraction method such as Artificial Bee Colony (ABC) and Particle Swarm Optimization (PSO) followed by metaheuristic feature selection algorithms as Harmonic Search (HS), Dragonfly Algorithm (DFA), Elephant Herding Algorithm (EHA). …”
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Exploring the role of Energy Communities: A Comprehensive Review by M. Asim Amin, Renato Procopio, Marco Invernizzi, Andrea Bonfiglio, Youwei Jia

“…The present review aimed to investigate and examine the significance of EC structures and to start an inclusive foundation for the broader implementation of EC for energy decentralization to figure out the research gaps and ensure that Machine Learning (ML) based solutions are essential tools to study and further discussed the several ML-based algorithms based on their objectives. Moreover, a comprehensive literature review is conducted to compare the possible strategies and tools that could be implemented in EC. …”
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QPPLab: A generally applicable software package for detecting, analyzing, and visualizing large-scale quasiperiodic spatiotemporal patterns (QPPs) of brain activity by Nan Xu, Behnaz Yousefi, Nmachi Anumba, Theodore J. LaGrow, Xiaodi Zhang, Shella Keilholz

“…QPPLab integrates correlation-based iterative algorithms, supports customizable parameter settings, and features automated workflows to simplify analysis. …”
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Optimization of hybrid photovoltaic-thermal systems integrated into buildings: Impact of bi-fluid exchangers and filling gases on the thermal and electrical performances of solar c... by Kokou Aménuvéla Toka, Yawovi Nougbléga, Komi Apélété Amou

“…The equations were discretized using the implicit finite difference method and solved using the Thomas and Gauss-Seidel algorithms. The results demonstrated an 18% enhancement in thermal efficiency with the utilization of neon. …”
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Application of Deep Learning to Identify Flutter Flight Testing Signals Parameters and Analysis of Real F-18 Flutter Flight Test Data by Sami Abou-Kebeh, Roberto Gil-Pita, Manuel Rosa-Zurera

“…We explore the preliminary viability of different deep learning networks and compare their performances to existing methods such as the PRESTO algorithm and Laplace Wavelet Matching Pursuit estimation. …”
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Systematic Literature Review Methodology for Drone Recharging Processes in Agriculture and Disaster Management by Leonardo Grando, Juan Fernando Galindo Jaramillo, José Roberto Emiliano Leite, Edson Luiz Ursini

“…It highlights recent advancements, including various algorithms for path and mission planning, while identifying ongoing challenges, particularly the scarcity of studies on the recharging coordination that affects UAV operations in these fields. …”
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Determination of an Indoor Target Position: An Accurate and Adaptable Approach Based on Differential Positioning by Siye Wang, Chang Ding, Weiqing Huang, Yanfang Zhang, Jianguo Jiang, Shaoyi Zhu, Yue Cui, Jun-yu Lin

“…In this work, we adopt a differential signal strength method in the design of our new indoor localization algorithm. The proposed algorithm reduces errors in the time domain by smoothing out the wireless signal fluctuations, thus stabilizing the signal; a single exponential algorithm is applied to the signal strength parameters collected to accomplish this. …”
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A Retroperitoneal Leiomyosarcoma Presenting as an Adrenal Incidentaloma in a Subject on Warfarin by Ishrat N. Khan, Mohamed A. Adlan, Michael J. Stechman, Lakdasa D. Premawardhana

“…Adrenal incidentalomas (AIs) are mostly benign and nonsecretory. Management algorithms lack sensitivity when assessing malignant potential, although functional status is easier to assess. …”
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Deep(er) reconstruction of imaging Cherenkov detectors with swin transformers and normalizing flow models by C Fanelli, J Giroux, J Stevens

“…Fast reconstruction algorithms are essential for near real-time alignment, calibration, data quality control, and efficient analysis. …”
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Bacterial Isolates and Antibiotic Sensitivity among Gambian Children with Severe Acute Malnutrition by Uduak A. Okomo, Danlami Garba, Augustin E. Fombah, Ousman Secka, Usman N. A. Ikumapayi, Jacob. J. Udo, Martin O. C. Ota

“…Establishing the pattern of infection and antimicrobial sensitivities in the local environment is critical to rational use of antibiotics and the development of management algorithms. Methods. Morbidity history and physical examination of 140 children with severe acute malnutrition were recorded. …”
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Gut–brain axis and neuropsychiatric health: recent advances by Ceymi Doenyas, Gerard Clarke, Renáta Cserjési

“…There is also evidence that the gut–brain axis plays a role in obesity and machine learning algorithms may assist in differentiating between obese and overweight individuals based on their microbiota data. …”
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Prediction of Network Threats and Attacks by Mathematical Simulation by Daniil Doroshenko

“…Using these models makes it possible to create precise algorithms to prevent attacks, which in turn achieve the reliability and security of the network infrastructure. …”
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Incorporation of Histogram Intersection and Semantic Information into Non-Negative Local Laplacian Sparse Coding for Image Classification by Ying Shi, Yuan Wan, Xinjian Wang, Huanhuan Li

“…Experimental results on four standard and three maritime image datasets demonstrate superior performance compared to the previous six algorithms. Specifically, the classification accuracy of our approach improved by 5% to 19% compared to the previous six methods. …”
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Comparative Analysis of Pre-trained based CNN-RNN Deep Learning Models on Anomaly-5 Dataset for Action Recognition by Fayaz Ahmed Memon, Umair Ali Khan, Pardeep Kumar, Imtiaz Ali Halepoto, Farida Memon

“…In addition of this, a new dataset is developed called Anomaly-5 that can helps as a valuable resource for training and evaluating action recognition algorithms. …”
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A multi-attribute decision making context for supply chain management using possibility single-valued neutrosophic soft settings by Saeed Muhammad, Basit Ali Muhammed, Rahman Atiqe Ur, Yasir Hayat Malik Muhammad

“…The suggested algorithm’s robustness is confirmed by comparison to evaluate its dependability and adaptability for modeling uncertainties related to the supplier selection problem.…”
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Learning-based DoS attack game strategy over multi-process systems by Zhiqiang Hang, Xiaolin Wang, Fangfei Li, Yi-ang Ren, Haitao Li

“…To solve this problem, we employed the multi-agent deep deterministic policy gradient algorithm. Numerical experiments demonstrate that the algorithm is effective for solving the game problem and exhibits convergence in multi-agent environments, outperforming other algorithms.…”
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Two-stage deep reinforcement learning method for agile optical satellite scheduling problem by Zheng Liu, Wei Xiong, Zhuoya Jia, Chi Han

“…A neural network is designed as the observation scheduling network to determine observation actions for the sequenced tasks, which is well trained by the soft actor-critic algorithm. Finally, extensive experiments show that the proposed method, along with the designed mechanisms and strategy, is superior to comparison algorithms in terms of solution quality, generalization performance, and computation efficiency.…”
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Automatic Measuring Approach and Device for Mature Rapeseed’s Plant Type Parameters by Shengyong Xu, Jinming Wang, Hao Tian, Bo Wang

“…The system software is used to connect and control CCD camera and other hardware and run specific image processing algorithms to process and analyze videos to obtain plant type parameters. …”
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TopoQual polishes circular consensus sequencing data and accurately predicts quality scores by Minindu Weerakoon, Sangjin Lee, Emily Mitchell, Haynes Heaton

“…TopoQual leverages techniques including partial order alignments (POA), topologically parallel bases, and deep learning algorithms to polish consensus sequences. Our results demonstrate that TopoQual corrects approximately 31.9% of errors in PacBio consensus sequences. …”
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