Identification of PET/CT radiomic signature for classification of locally recurrent rectal cancer: A network-based feature selection approach by Sara Dalmonte, Maria Adriana Cocozza, Dajana Cuicchi, Daniel Remondini, Lorenzo Faggioni, Paolo Castellucci, Andrea Farolfi, Emilia Fortunati, Alberta Cappelli, Riccardo Biondi, Arrigo Cattabriga, Gilberto Poggioli, Stefano Fanti, Gastone Castellani, Francesca Coppola, Nico Curti

“…Feature selection was performed using a novel approach derived from gene expression analysis, based on the DNetPRO algorithm. The prediction was done using a Support Vector Classifier (SVC) with a 10-fold cross-validation. …”
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Mapping the EORTC QLQ-C30 and QLQ-LC13 to the SF-6D utility index in patients with lung cancer using machine learning and traditional regression methods by Longlin Jiang, Kexun Li, Simiao Lu, Zhou Hong, Yifang Wang, Qin Xie, Qin He, Sirui Wei, Aoru Zhou, Hong Kang, Xuefeng Leng, Qing Yang, Yan Miao

“…Conclusions This study developed an optimized mapping algorithm to predict the utility index from the QLQ-C30 QLQ-LC13 to the SF-6D. …”
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User Random Access Technology Based on Beam Hopping Satellite Communication System by Zixuan HUANG, Jiaxi ZHOU, Jing ZHANG, Zhengyu ZHANG

“…On the basis of geosynchronous earth orbit multi-beam satellite communication systems, this paper designed the process of user random access to the network and specifi c signaling interaction under the agile beam mechanism, and proposed the scheduling strategy and allocation scheme of the agile signaling beam.This scheme increased the fl exibility of access resource allocation under the premised of ensured that all users could accessed the network, eff ectively improved the utilization rate of satellite network resources.The request of user access to the satellite communication network belongs to the burst type, it is more suitable to use the random competition access, so this paper based on the general random competition access strategy, proposed an adaptive random competition access algorithm based on the heat value, based on the heat value predicted by the network side, the user selects diff erent random access strategies for access.Through the simulation and analysis of the optimization algorithm, it is proved that the algorithm could eff ectively reduced the probability of access collision under various network loads, so as to achieved the purpose of users quickly accessing the network.…”
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Assessing the Effectiveness of DL-Clustering for Energy Optimization in Wireless Sensor Networks by Shailaja S. Halli, Poornima G Patil

“…In order to find the ideal choice for the input, the algorithm classifies system decisions, mobile data collectors, routing, and mobility. …”
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Distributed Formation Control with Obstacle and Collision Avoidance for Hypersonic Gliding Vehicles Subject to Multiple Constraints by Zhen Zhang, Yifan Luo, Yaohong Qu

“…The algorithm implements a control framework designed to be of two terms: distributed virtual controller and actual control input solver. …”
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An efficient real-time signal processing method for satellite laser ranging. by Jinyu Wang, Wei Zhu, Weiming Gong

“…To address these problems, we propose a new, efficient real-time SLR data processing method. This algorithm combines single-stage filtering with a histogram-based approach and incorporates polynomial fitting to establish a predictive model. …”
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A joint three-plane physics-constrained deep learning based polynomial fitting approach for MR electrical properties tomography by Kyu-Jin Jung, Thierry G. Meerbothe, Chuanjiang Cui, Mina Park, Cornelis A.T. van den Berg, Stefano Mandija, Dong-Hyun Kim

“…To estimate tissue electrical properties, various reconstruction algorithms have been proposed. However, physics-based reconstructions are prone to various artifacts such as noise amplification and boundary artifact. …”
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Outdoor Environment Design Optimization of an Office Building Based on Indoor Thermal Conditions and Building Energy Performance by Yaolin Lin, Tao Huang, Wei Yang, Melissa Chan, Chun-Qing Li, Mingqi Dai, Pengju Chen

“…Thirdly, two machine learning prediction algorithms were used to develop discomfort degree hours and energy consumption models, and the artificial neural network models were found to have better prediction performance with R-squares greater than 0.99. …”
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Hybrid Hunger Games Search optimization using a neural networks approach applied to UAVs by Nadia Samantha Zuñiga-Peña, Salatiel Garcia-Nava, Norberto Hernandez-Romero, Juan Carlos Seck-Touh-Mora

“…Optimization methods like population-based algorithms are valuable when applied to multidimensional and nonlinear problems. …”
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Smart agriculture: utilizing machine learning and deep learning for drought stress identification in crops by Tariq Ali, Saif Ur Rehman, Shamshair Ali, Khalid Mahmood, Silvia Aparicio Obregon, Rubén Calderón Iglesias, Tahir Khurshaid, Imran Ashraf

“…Abstract Plant stress reduction research has advanced significantly with the use of Artificial Intelligence (AI) techniques, such as machine learning and deep learning. …”
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A comprehensive techno-economic analysis for a PHEV-integrated microgrid system involving wind uncertainty and diverse demand side management policies by Bishwajit Dey, Laishram Khumanleima Chanu, Gulshan Sharma, Pitshou N. Bokoro

“…Some of the additional benefits of implementing the hybrid DSM strategy were a 24 % reduction in peak load demand, a 22 % improvement in load factor, and 50 kWh of energy saved at the end of the day. …”
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Use of Spectral Clustering for Identifying Circulation Patterns of the East Korea Warm Current and Its Extension by Eun Young Lee, Dong Eun Lee, Hye-Ji Kim, Haedo Baek, Young Ho Kim, Young-Gyu Park

“…By applying a spectral clustering algorithm, three distinct patterns in the East Korea Warm Current (EKWC) and its extension were identified from daily maps of reanalyzed sea surface heights spanning the past 30 years. …”
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Pilot-Based Codebook Non-Orthogonal Artificial Noise Schemes for Physical Layer Security: Secrecy Capacity Optimization Under Unknown Eavesdropper Channels by Yi Zhang, Yebo Gu, Tao Zhao, Bo Wang

“…However, the design of NORAN leads to a reduction in the channel capacity of legitimate channels, thereby limiting its application in practical systems. …”
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High-Level Synthesis: Productivity, Performance, and Software Constraints by Yun Liang, Kyle Rupnow, Yinan Li, Dongbo Min, Minh N. Do, Deming Chen

“…The stereo matching algorithms achieve between 3.5X and 67.9X speedup over software (but still less than manual RTL design) with a fivefold reduction in design effort versus manual RTL design.…”
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Adaptive Determination of Optimum Switching Frequency in SiC-PWM-Based Motor Drives: A Speed-Dependent Core Loss Correction Approach by Sepideh Amirpour, Sima Soltanipour, Torbjorn Thiringer, Pranav Katta

“…The analysis integrates electromagnetic field simulations in Ansys Maxwell with the drive system control algorithm in Ansys Twin Builder, ensuring an accurate representation of their interactions. …”
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Abnormal activity in the brainstem affects gait in a neuromusculoskeletal model by Daisuke Ichimura, Makoto Sawada, Kenji Wada, Ritsuko Hanajima

“…Results The normal models walked successfully following internal parameter optimization using standard genetic algorithms. In an abnormal model, 156 freezing of gait events were detected among 40,000 parameter sets using a freezing of gait-identifying algorithm. …”
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Energy Demand Response in a Food-Processing Plant: A Deep Reinforcement Learning Approach by Philipp Wohlgenannt, Sebastian Hegenbart, Elias Eder, Mohan Kolhe, Peter Kepplinger

“…Although RL is slightly less efficient in cost reduction, it significantly outperforms in computational speed, being approximately 20 times faster. …”
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Goal-directed dehydration therapy in sepsis and acute respiratory distress syndrome guided by volumetric hemodynamic monitoring by N. O. Khromacheva, E. V. Fot, V. V. Kuzkov, M. Yu. Kirov

“…The extravascular compartment dehydration algorithm attenuated pulmonary edema and acute kidney injury more efficiently. …”
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Is there a competitive advantage to using multivariate statistical or machine learning methods over the Bross formula in the hdPS framework for bias and variance estimation? by Mohammad Ehsanul Karim, Yang Lei

“…Tailoring the choice of method to the epidemiological scenario is essential for optimizing the balance between bias reduction and precision.…”
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A sustainable neuromorphic framework for disease diagnosis using digital medical imaging by Rutwik Gulakala, Marcus Stoffel

“…Making use of sparse signal transmissions as in the human brain, a neuromorphic algorithm for imaging diagnostics is introduced. Methods:: A novel, sustainable, brain-inspired spiking neural network is proposed to perform the multi-class classification of digital medical images. …”
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