Intelligent anti-jamming decision algorithm of bivariate frequency hopping pattern based on ET-PPO by Yibo CHEN, Zhijin ZHAO

“…In order to further improve its anti-interference ability in complex electromagnetic environment, a PPO algorithm based on weighted importance sampling and eligibility traces (ET-PPO) was proposed.On the basis of the traditional frequency hopping pattern, time-varying parameters were introduced, and the bivariate frequency hopping pattern decision problem was modeled as a Markov decision problem through the construction of the state-action-reward triple.Aiming at the high variance problem of the sample update method of an actor network of the PPO algorithm, weighted importance sampling was introduced to reduce the variance, and the action selection strategy of Beta distribution was used to enhance the stability of the learning stage.Aiming at the problem of slow convergence speed of the evaluator network, the eligibility trace method was introduced, which better balanced the convergence speed and the global optimal solution.The algorithm comparison simulation results in different electromagnetic interference environments show that ET-PPO has better adaptability and stability, and has better performance against obstruction interference and sweep frequency interference.…”
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A GIS Partial Discharge Pattern Recognition Method Based on Improved CBAM-ResNet by Di Hu, Zhong Chen, Wei Yang, Taiyun Zhu, Yanguo Ke, Kaiyang Yin

“…Different types of partial discharge (PD) cause different damages to gas-insulated substation (GIS), so it is very important to correctly identify the type of PD for evaluating the GIS insulation condition. The traditional PD pattern recognition algorithm has the limitations of low recognition accuracy and slow recognition speed in engineering applications. …”
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Building electrical consumption patterns forecasting based on a novel hybrid deep learning model by Nasser Shahsavari-Pour, Azim Heydari, Farshid Keynia, Afef Fekih, Aylar Shahsavari-Pour

“…Existing models often fail to account for the complex and nonlinear characteristics of energy consumption patterns, resulting in suboptimal prediction performance. …”
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An Efficient Dropout for Robust Deep Neural Networks by Yavuz Çapkan, Aydın Yeşildirek

“…Overfitting remains a major difficulty in training deep neural networks, especially when attempting to achieve good generalization in complex classification tasks. …”
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Microscopic Structure and Strength Variation Patterns of Fiber-Modified Coarse-Grained Sulfate Saline Soil by DING Jin-hua, LI Jia-jun, GONG Miao-miao, LUO Wei, LI Teng-fei

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Prospective risk scenario set construction and patternized response strategy for AC/DC distribution system by TANG Zhaojie, ZHANG Mingchen, ZHAN Huiyu, BAI Jingjing, LUO Lizi

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Surveillance of surgical-site infections and antimicrobial resistance patterns in a tertiary hospital in Alexandria, Egypt by May Raouf, Thoraya Ghazal, Mohamed Kassem, Abdelfattah Agamya, Amira Amer

“…This study aimed to evaluate incidence and risk factors of surgical site infections (SSIs), etiological pathogens and AMR patterns identification. …”
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Urine Metabolomic Patterns to Discriminate the Burnout Levels and Night-Shift-Related Stress in Healthcare Professionals by Andreea Petra Ungur, Andreea-Iulia Socaciu, Maria Barsan, Armand Gabriel Rajnoveanu, Razvan Ionut, Carmen Socaciu, Lucia Maria Procopciuc

“…<b>Purpose</b>: Comparative evaluation of urine metabolite patterns that may discriminate the burnout levels and the effects of night shifts on healthcare professionals. …”
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Explainable AI Meets Synthetic Data: A Deep Learning Framework for Detecting Network Intrusion in NextG Network Infrastructure by Md Junayed Hossain, Khorshed Alam, Md Fahad Monir, Md Mozammal Hoque, Tarem Ahmed

“…In today&#x2019;s digitally driven world, network security has become a top accountability as cyberattacks become more sophisticated, especially within emerging NextG network infrastructures. …”
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Hybrid Dynamic Network Data Envelopment Analysis by Ling Li, Fengshan Wang

“…We vertically deal with intermediate products between divisions with assignable inputs in the network structure and, horizontally, we extend network structure by means of a dynamic pattern with unrelated activities between two succeeding periods. …”
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Revisiting Information Cascades in Online Social Networks by Michael Sidorov, Ofer Hadar, Dan Vilenchik

“…It is widely believed that a user’s activity pattern in Online Social Networks (OSNs) is strongly influenced by their friends or the users they follow. …”
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Artificial intelligence and machine learning techniques for suicide prediction: Integrating dietary patterns and environmental contaminants by Mayyas Al-Remawi, Ahmed S.A. Ali Agha, Faisal Al-Akayleh, Faisal Aburub, Rami A. Abdel-Rahem

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Uncovering nonlinear patterns in time-sensitive prehospital breathing emergencies: an exploratory machine learning study by Peter Hill, Daniel Jonsson, Jakob Lederman, Peter Bolin, Veronica Vicente

“…Multiple ML models, random forest, gradient boosting, neural networks, and logistic regression were trained to probe potential nonlinear patterns and interactions, not with the primary goal of predictive accuracy. …”
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Redefining Urban Traffic Dynamics With TCN-FL Driven Traffic Prediction and Control Strategies by K. M. Karthick Raghunath, C. Rohith Bhat, Venkatesan Vinoth Kumar, Velmurugan Athiyoor Kannan, T. R. Mahesh, K. Manikandan, N. Krishnamoorthy

“…In this approach, every point in the intelligent city network, including traffic sensors and cameras, serves to collectively comprehend traffic patterns without disclosing raw data. …”
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Personalized region of interest recommendation through adaptive fusion of multi-dimensional user preferences by Qing Tang, Shenghua Xu, Zhuolu Wang, Yong Wang, Shichuan Liu, Haiqin Hua

“…This process involves analyzing users’ historical check-in data within location networks, which helps capture spatial activity preferences and predict regional movement patterns. …”
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Green Infrastructure Network Planning in Urban Fringe Areas Based on the Characteristics of Agricultural and Forestry Landscape Ecological Network in a Metropolitan City by Dongmeng Wang, Can Zhao, Baolin Xia, Chenming Zhang, Dezheng Kong, Qindong Fan

“…Finally, based on the evaluation results, a classified network planning was conducted, and a triple-network integrated planning strategy was proposed. …”
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Advances in Neural Network assisted Tool Pressure Prediction by Göltl Florian, Harst Felix, Birkert Arndt, Stache Nicolaj C.

“…It has been demonstrated that convolutional neural networks (CNNs) can predict pressure distributions from spotting patterns. …”
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A novel robust network construction and analysis workflow for mining infant microbiota relationships by Wei Jiang, Yue Zhai, Dongbo Chen, Qinghua Yu

“…Understanding the relationships within the microbiota is essential to linking its maturation process to these outcomes. Several network-based methods have been developed to analyze the developing patterns of infant microbiota, but evaluating the reliability and effectiveness of these approaches remains a challenge. …”
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A Review of Link Prediction Algorithms in Dynamic Networks by Mengdi Sun, Minghu Tang

“…After summarizing and comparing the common datasets and evaluation indicators for dynamic network link prediction, we briefly review classic related algorithms in recent years, and classify them according to the network changes, sampling methods, underlying principles of algorithms, and other classification methods. …”
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Two patterns in apical dendrite extensions of projection neurons within cerebral cortex of reeler mutant mice by Ryoichi Ichikawa, Ryoichi Ichikawa

“…I aimed to investigate the projection target-specific regulation of this apical dendrite extension pattern in reeler mice.MethodsTo this end, three types of projection neurons–corticospinal (CS), corticothalamic (CT), and corticocallosal (CC) neurons–were evaluated using retrograde labeling techniques.Results and discussionReeler CS neurons displayed a congregation pattern of apical dendritic terminal tips in a specific upper cortical zone, whereas reeler CC neurons exhibited a dispersed pattern of scattered tips throughout the cortex. …”
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