|
|
|
|
|
Sergio Jesús González-Ambriz, Rolando Menchaca-Méndez, Sergio Alejandro Pinacho-Castellanos and Mario Eduardo Rivero-Ángeles
This paper presents the spectral gap-based topology control algorithm (SGTC) for wireless backhaul networks, a novel approach that employs the Laplacian Spectral Gap (LSG) to find expander-like graphs that optimize the topology of the network in terms of...
ver más
|
|
|
|
|
|
|
|
|
|
|
Sanaz Gheibi, Tania Banerjee, Sanjay Ranka and Sartaj Sahni
This paper proposes a new time-respecting graph (TRG) representation for contact sequence temporal graphs. Our representation is more memory-efficient than previously proposed representations and has run-time advantages over the ordered sequence of edges...
ver más
|
|
|
|
|
|
|
|
|
|
|
Nikolaos Zafeiropoulos, Pavlos Bitilis, George E. Tsekouras and Konstantinos Kotis
In the realm of Parkinson?s Disease (PD) research, the integration of wearable sensor data with personal health records (PHR) has emerged as a pivotal avenue for patient alerting and monitoring. This study delves into the complex domain of PD patient car...
ver más
|
|
|
|
|
|
|
|
|
|
|
Efstathios Konstantinos Anastasiadis and Ioannis Antoniou
We extend network analysis to directed criminal networks in the context of asymmetric links. We computed selected centralities, centralizations and the assortativity of a drug trafficking network with 110 nodes and 295 edges. We also monitored the centra...
ver más
|
|
|
|
|
|
|
|
|
|
|
Sorin Zoican, Roxana Zoican, Dan Galatchi and Marius Vochin
This paper illustrates a general framework in which a neural network application can be easily integrated and proposes a traffic forecasting approach that uses neural networks based on graphs. Neural networks based on graphs have the advantage of capturi...
ver más
|
|
|
|
|
|
|
|
|
|
|
Xin Tian and Yuan Meng
Multi-relational graph neural networks (GNNs) have found widespread application in tasks involving enhancing knowledge representation and knowledge graph (KG) reasoning. However, existing multi-relational GNNs still face limitations in modeling the excha...
ver más
|
|
|
|
|
|
|
|
|
|
|
Zengyu Cai, Chunchen Tan, Jianwei Zhang, Liang Zhu and Yuan Feng
As network technology continues to develop, the popularity of various intelligent terminals has accelerated, leading to a rapid growth in the scale of wireless network traffic. This growth has resulted in significant pressure on resource consumption and ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Kexiang Qian, Hongyu Yang, Ruyu Li, Weizhe Chen, Xi Luo and Lihua Yin
With the rapid growth of IoT devices, the threat of botnets is becoming increasingly worrying. There are more and more intelligent detection solutions for botnets that have been proposed with the development of artificial intelligence. However, due to th...
ver más
|
|
|
|
|
|
|
|
|
|
|
Zilin Zhao, Zhi Cai, Mengmeng Chang and Zhiming Ding
Unconventional events exacerbate the imbalance between regional transportation demand and limited road network resources. Scientific and efficient path planning serves as the foundation for rapidly restoring equilibrium to the road network. In real large...
ver más
|
|
|
|
|
|
|
|
|
|
|
Giorgio Lazzarinetti, Riccardo Dondi, Sara Manzoni and Italo Zoppis
Solving combinatorial problems on complex networks represents a primary issue which, on a large scale, requires the use of heuristics and approximate algorithms. Recently, neural methods have been proposed in this context to find feasible solutions for r...
ver más
|
|
|
|
|
|