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- research-articleNovember 2024
SCCGCN: A Skip-Connection Coupled Graph Convolutional Network with Dynamic Fusion Attention Mechanism for Traffic Flow Prediction
IoTML '24: Proceedings of the 2024 4th International Conference on Internet of Things and Machine LearningPages 19–23https://doi.org/10.1145/3697467.3697586Traffic flow demand prediction is crucial for optimizing traffic resources and improving urban transportation. Given the complexity of real-world traffic data, effective modeling of spatiotemporal dynamics is essential. This paper introduces a novel ...
- research-articleJuly 2024
Interactive dynamic diffusion graph convolutional network for traffic flow prediction
Information Sciences: an International Journal (ISCI), Volume 677, Issue Chttps://doi.org/10.1016/j.ins.2024.120938AbstractCapturing the temporal and spatial features, and the spatiotemporal correlations in traffic networks is the essential task for accurate traffic flow prediction. Although most existing models have explored the temporal features deeply, the ...
- research-articleJanuary 2024
Enhanced S-boxes for the Advanced Encryption Standard with maximal periodicity and better avalanche property
AbstractThis paper investigates a particular family of enhanced substitution boxes for the Advanced Encryption Standard. In contrast to the original substitution box design where each input has relatively short orbit lengths, the modified S-...
Highlights- This paper investigates a particular family of enhanced substitution boxes for the Advanced Encryption Standard.
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- ArticleDecember 2023
Periodic-Aware Network for Fine-Grained Action Recognition
AbstractRecently, skeleton-based action recognition has gained increasing attention and achieved remarkable results in coarse-grained action recognition. Despite the positive results shown in these attempts, they are less effective in scenarios that ...
- research-articleSeptember 2023
Fixed-time periodic stabilization of discontinuous reaction–diffusion Cohen–Grossberg neural networks
Neural Networks (NENE), Volume 166, Issue CPages 354–365https://doi.org/10.1016/j.neunet.2023.07.017AbstractThis paper aims to study the fixed-time stabilization of a class of delayed discontinuous reaction–diffusion Cohen–Grossberg neural networks. Firstly, by providing some relaxed conditions containing indefinite functions and based on inequality ...
Highlights- Providing novel fixed-time stability criteria for reaction–diffusion Cohen–Grossberg neural networks.
- Transforming the solution of the discontinuous RDCGNNs into periodic solution of ordinary differential systems.
- Achieving the ...
- rapid-communicationAugust 2023
Longest bordered and periodic subsequences
AbstractWe present an algorithm computing the longest periodic subsequence of a string of length n in O ( n 7 ) time with O ( n 3 ) space. We obtain improvements when restricting the exponents or extending the search allowing the reported subsequence to ...
Highlights- Generalization from the longest periodic substring to subsequences.
- Computation of the longest periodic subsequence within polynomial time bounds.
- Inclusion of subperiodic subsequences eases the computation.
- Conditional lower ...
- research-articleJuly 2023
- articleJuly 2023
A Novel Multi-Domain Adaptation-Based Method for Blast Furnace Anomaly Detection
International Journal of Web Services Research (IJWSR-IGI), Volume 20, Issue 1Pages 1–14https://doi.org/10.4018/IJWSR.326753In the steelmaking process, ensuring stable and reliable furnace plays a vital role for guaranteeing production quality of steel products. Traditional methods for detecting furnace anomalies in blast furnaces rely on operator judgment models built upon ...
- research-articleJune 2023
RSPHUIM: Recent Short Period High Utility Itemset Mining
AbstractThe past two decades have seen a great amount of research being done in the field of Frequent Pattern Mining (FPM). Utility Oriented Pattern Mining has emerged as an important area where the profit of the itemset is taken into consideration. High ...
- research-articleApril 2023
Cluster-based industrial KPIs forecasting considering the periodicity and holiday effect using LSTM network and MSVR
Advanced Engineering Informatics (ADEI), Volume 56, Issue Chttps://doi.org/10.1016/j.aei.2023.101916AbstractKey performance indicators (KPIs) are key indicators to measure the status and performance of various facilities, time, and resources in the process of production and life. Forecasting industrial KPIs helps in analyzing the future state to make ...
- ArticleMarch 2023
Finding the Cyclic Covers of a String
AbstractWe introduce the concept of cyclic covers, which generalizes the classical notion of covers in strings. Given any nonempty string X of length n, a factor W of X is called a cyclic cover if every position of X belongs to an occurrence of a cyclic ...
- ArticleMay 2023
Multi-user Service Placement in LEO Satellite Constellations
AbstractWith the rapid development of the research of space-air-ground integrated network, the importance of studying low Earth orbit (LEO) satellite network has become increasingly prominent. One of the important research directions is to cope with the ...
- ArticleNovember 2022
Analysis of Ciphertext Behaviour Using the Example of the AES Block Cipher in ECB, CBC, OFB and CFB Modes of Operation, Using Multiple Encryption
Intelligent Information and Database SystemsPages 621–629https://doi.org/10.1007/978-3-031-21967-2_50AbstractThis paper explores the Advance Encryption Standard (AES) block cipher in Electronic Code Book (ECB), Cipher Block Chaining (CBC), Output Feedback (OFB) and Cipher Feedback (CFB) modes of operation to compare the characteristic properties of ...
- research-articleSeptember 2022
Periodicity counting in videos with unsupervised learning of cyclic embeddings
Pattern Recognition Letters (PTRL), Volume 161, Issue CPages 59–66https://doi.org/10.1016/j.patrec.2022.07.013Highlights- We introduce a new method to measure periodicity on any video, even out of the “daily-life” domain.
We introduce a context-agnostic unsupervised method to count periodicity in videos. Current methods estimate periodicity for a specific type of application (e.g. some repetitive human motion). We propose a novel method that provides a ...
- research-articleAugust 2022
PCS-LSTM: A hybrid deep learning model for multi-stations joint temperature prediction based on periodicity and closeness
Neurocomputing (NEUROC), Volume 501, Issue CPages 151–161https://doi.org/10.1016/j.neucom.2022.06.015AbstractTemperature is one of the most important meteorological elements, which affects the daily lives of people all over the world. Owing to the rapid development of meteorological facilities, the number of meteorological observation stations on earth ...
- research-articleJune 2022
- ArticleMay 2022
- research-articleMarch 2022
On Hankel determinants for Dyck paths with peaks avoiding multiple classes of heights
European Journal of Combinatorics (EJCM), Volume 101, Issue Chttps://doi.org/10.1016/j.ejc.2021.103478AbstractFor any integer m ≥ 2 and a set V ⊂ { 1 , … , m }, let ( m , V ) denote the union of congruence classes of the elements in V modulo m. We study the Hankel determinants for the number of Dyck paths with peaks avoiding the heights in the ...