The Kirchhoff Index of Hypercubes and Related Complex Networks by Jiabao Liu, Jinde Cao, Xiang-Feng Pan, Ahmed Elaiw

“…The resistance distance between any two vertices of G is defined as the network effective resistance between them if each edge of G is replaced by a unit resistor. …”
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Research on a stable clustering algorithm based on the optimal connectivity power for wireless sensor networks by LI Fang-min1, LIU Xin-hua1, KUANG Hai-lan1, FANG Yi-lin1

“…In realistic environment, the actual layout of nodes is easy to make network separated and nodes are always densely deployed in hot spots like the site of an accident or disaster where the competition intense was very high.A stable clustering algorithm based on the optimal connectivity power for wireless sensor networks was proposed.The algorithm makes use of the alterable power control technology to raise the channel utilization ratio and network throughput based on the optimal number of neighbors, and realizes the stable connectivity and clustering of network.The algorithm simplifies the topology of network so that prolong the network lifetime at the best.The simulation results show that the algorithm maintains the connectivity and stability of network effectively, and has good auto-adapted ability to environment and obvious effects in the promotion of whole performance of network.…”
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DESIGN OF TRANSLATION AMBIGUITY ELIMINATION METHOD BASED ON RECURRENT NEURAL NETWORKS by Jianzhou Cui

“…This translation model based on recurrent neural networks effectively eliminates the gradient imbalance problem generated during the translation ambiguity process. …”
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Correlation-immunity study of balanced H-Boolean functions by Wei-wei LI

“…As a novel definition,E-derivative was introduced to study problems that are extremely difficult to handle in the cryptographic system.By using the way of combining derivative with E-derivative and correlation-immunity of H-Boolean functions,the distribution structure of balanced H-Boolean functions were deeply analyzed,and some important results on how to determine whether or not a H-Boolean function has correlation-immunity with the relatively simplified method of distinguishing different structure were also obtained,which are going to play important roles in the field of cryptology and future worldwide applications.Beyond that,the problem of the most higher-order correlation-immunity of H-Boolean function which is also one of the most difficult unsolved problems in cryptology was solved successfully to improve the anti-attack ability of cryptosystem and ensured the secure transmission of secret information on the network effectively .…”
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Service priority-aware network traffic scheduling mechanism by Huahui LV, Zhida LIN, Hongcong HUANG

“…In view of the problem that network congestion which caused by the uneven distribution in large traffic data,a priority-aware dynamic network traffic scheduling mechanism was proposed.By using the token bucket algorithm,different buckets of different rates were assigned to different services according to the service priorities.The priorities of the service and the remaining buffer space of the user nodes was taken into account to deal with different services.At the same time,the traffic arrival factor,service factor and node cache were regarded as target to define a network traffic scheduling mechanism performance indicator:packet loss rate.The numerical results show that the proposed mechanism can rationally divide the service priorities in the network,effectively utilize the network resources,prevent the network congestion,enhance the network performance,and provide the users with more stable and reliable network service.…”
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P2Y Receptors in Synaptic Transmission and Plasticity: Therapeutic Potential in Cognitive Dysfunction by Segundo J. Guzman, Zoltan Gerevich

“…In the present paper we review cellular and network effects of P2Y receptors in the brain. We show that P2Y receptors inhibit the release of neurotransmitters, modulate voltage- and ligand-gated ion channels, and differentially influence the induction of synaptic plasticity in the prefrontal cortex, hippocampus, and cerebellum. …”
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Quality of service optimization algorithm based on deep reinforcement learning in software defined network by Cenhuishan LIAO, Junyan CHEN, Guanping LIANG, Xiaolan XIE, Xiaoye LU

“…Deep reinforcement learning has strong abilities of decision-making and generalization and often applies to the quality of service (QoS) optimization in software defined network (SDN).However, traditional deep reinforcement learning algorithms have problems such as slow convergence and instability.An algorithm of quality of service optimization algorithm of based on deep reinforcement learning (AQSDRL) was proposed to solve the QoS problem of SDN in the data center network (DCN) applications.AQSDRL introduces the softmax deep double deterministic policy gradient (SD3) algorithm for model training, and a SumTree-based prioritized empirical replay mechanism was used to optimize the SD3 algorithm.The samples with more significant temporal-difference error (TD-error) were extracted with higher probability to train the neural network, effectively improving the convergence speed and stability of the algorithm.The experimental results show that the proposed AQSDRL effectively reduces the network transmission delay and improves the load balancing performance of the network than the existing deep reinforcement learning algorithms.…”
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Energy-Balanced Density Control to Avoid Energy Hole for Wireless Sensor Networks by Jie Jia, Jian Chen, Xingwei Wang, Linliang Zhao

“…Combined with the accessibility condition, nodes on different energy layers are activated with a nonuniform distribution, so as to balance the energy depletion and enhance the survival of the network effectively. Extensive simulation results are presented to demonstrate the effectiveness of our algorithm.…”
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Enhancing environmental monitoring of harmful algal blooms with ConvLSTM image prediction by Sung Jae Kim, Yongbok Cho

“…By leveraging this spatiotemporal modeling framework, the ConvLSTM network effectively predicts future HAB concentrations with improved accuracy. …”
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Quality Assurance Competition Strategy under B2C Platform by Yunmiao Gui, Bengang Gong

“…Whether the seller or the platform that provides quality assurance policy is preferred depends on their influence on network effects. We show that the seller and the platform have no strong intention to improve the quality assurance level in the monopoly markets. …”
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MAC mechanism based on link prediction and network coding by HANGFeng-jun S, juan GONGWen, Zhe GENG

“…Experiment results show that this improved MAC protocol can increase network throughput and balance the load of the whole network effectively by using over-heard of nodes rationally, without causing concen-trating flows at the same time.…”
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Research on deep reinforcement learning in Internet of vehicles edge computing based on Quasi-Newton method by ZHANG Jianwu, LU Zetao, ZHANG Qianhua, ZHAN Ming

“…Compared to existing algorithms, the proposed algorithm improves the convergence and stability of task offloading significantly, addresses task offloading issues in vehicular networks effectively, and offers high practicality and reliability.…”
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Exploration of Mechanical Behaviors of Argillaceous Siltstone through Photoelastic Model Test and DEM Modelling by Weike Li, Jianqiang Han, Jie Cui, Weili Luo, Guangzao Zheng

“…The results show that both the photoelastic model and DEM modelling are able to capture the evolution of force chain network, effective contact number and stress concentration factor, and rheological behaviors when it is subjected to an increasing uniaxial load. …”
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Maize quality detection based on MConv-SwinT high-precision model. by Ning Zhang, Yuanqi Chen, Enxu Zhang, Ziyang Liu, Jie Yue

“…Experimental results demonstrate that the MC-Swin Transformer model proposed in this paper significantly outperforms traditional convolutional neural network models in key metrics such as accuracy, precision, recall, and F1 score, achieving a recognition accuracy rate of 99.89%. Thus, the network effectively and efficiently classifies different corn qualities. …”
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Fault Diagnosis of Bearings with Small Sample Size Using Improved Capsule Network and Siamese Neural Network by Jarula Yasenjiang, Yang Xiao, Chao He, Luhui Lv, Wenhao Wang

“…The dynamic routing mechanism of the capsule network effectively captures and integrates key fault features, improving the model’s feature representation and robustness. …”
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Graph neural network driven traffic prediction technology:review and challenge by Yi ZHOU, Shuting HU, Wei LI, Nan CHENG, Ning LU, Xuemin(Sherman) SHEN

“…With the rapid development of Internet of things and artificial intelligence technology, accurate analysis and prediction of traffic data have become the primary target of intelligent transportations.In recent years, the method of traffic forecasting has gradually changed from the classical model-driven type to the data-driven type.However, how to effectively analyze the spatial-temporal characteristics of road networks through big data is one of the key issues in the traffic prediction process.Spatiotemporal big data analysis is a powerful tool for the traffic prediction.The traffic network can be modeled as a graph network, while the deep learning method can be extended on the graph network.Utilizing graph neural networks, we can build the spatiotemporal prediction model, and obtain the spatial-temporal correlation between the sensor nodes in road networks effectively by using graph convolution, which can significantly improve the accuracy of traffic prediction models.The traffic forecasting technology driven by graph neural networks was explored, and two kinds of traffic prediction models based on the analysis of deep spatial-temporal characteristics were extracted.The actual cases were analyzed and evaluated to discuss the technical advantages and key challenges of graph neural networks in the traffic prediction.The potential issues of graph neural network driven prediction mechanisms were also excavated.…”
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The social welfare effect of e-commerce product reputation information asymmetry from the perspective of network externality. by Min Zhao, Shuyun Wang, Tongshui Xia

“…We recommend that the healthy development of e-commerce platforms proceeds from three aspects: building a reputation mechanism for e-commerce platforms that is jointly supervised by e-commerce platforms, third-party institutions, and social organizations; increasing the cost of punishment for violations; and exerting platform network effects to enhance the competitiveness of enterprises.…”
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Smart Agricultural Pest Detection Using I-YOLOv10-SC: An Improved Object Detection Framework by Wenxia Yuan, Lingfang Lan, Jiayi Xu, Tingting Sun, Xinghua Wang, Qiaomei Wang, Jingnan Hu, Baijuan Wang

“…The enhanced I-YOLOv10-SC network effectively addresses the challenges of detecting small and incomplete insect targets in tea plantations, offering high precision and recall rates, thus providing a solid technical foundation for intelligent pest monitoring and precise prevention in smart tea gardens.…”
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Re-Calibrating Network by Refining Initial Features Through Generative Gradient Regularization by Naim Reza, Ho Yub Jung

“…The experiments show that implementing this method on a pre-trained network effectively re-calibrates the network and augments higher variance filters of the initial layer of the network, which helps produce refined features. …”
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Mechanisms of nucleus accumbens deep brain stimulation in treating mental disorders by Hanyang Ruan, Geya Tong, Minghui Jin, Kathrin Koch, Zhen Wang

“…Finally, since treatment effects of NAc DBS are most probably also related to alterations in NAc connected circuits or networks, we review studies focusing on the investigation of NAc DBS network effects. By examining these various components that are assumed to be of relevance in the context of NAc DBS, this review will hopefully contribute to increasing our knowledge about the mechanisms underlying NAc DBS and optimizing future selection of optimal DBS targets.…”
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