Ruchun Jia¹, Jianwei Zhang^1,*, Yi Lin¹, Yunxiang Han¹, Feike Yang²

CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 2523-2546, 2024, DOI:10.32604/cmc.2024.047543 - 15 May 2024

Abstract In order to enhance the accuracy of Air Traffic Control (ATC) cybersecurity attack detection, in this paper, a new clustering detection method is designed for air traffic control network security attacks. The feature set for ATC cybersecurity attacks is constructed by setting the feature states, adding recursive features, and determining the feature criticality. The expected information gain and entropy of the feature data are computed to determine the information gain of the feature data and reduce the interference of similar feature data. An autoencoder is introduced into the AI (artificial intelligence) algorithm to encode and… More >

Shuting Ge^1,2, Jin Ren^2,3,*, Yihua Shi⁴, Yujun Zhang¹, Shunzhi Yang², Jinfeng Yang²

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3215-3245, 2024, DOI:10.32604/cmc.2023.046746 - 26 March 2024

Abstract In air traffic control communications (ATCC), misunderstandings between pilots and controllers could result in fatal aviation accidents. Fortunately, advanced automatic speech recognition technology has emerged as a promising means of preventing miscommunications and enhancing aviation safety. However, most existing speech recognition methods merely incorporate external language models on the decoder side, leading to insufficient semantic alignment between speech and text modalities during the encoding phase. Furthermore, it is challenging to model acoustic context dependencies over long distances due to the longer speech sequences than text, especially for the extended ATCC data. To address these issues,… More >

Othman S. Al-Heety^1,*, Zahriladha Zakaria^1,*, Ahmed Abu-Khadrah², Mahamod Ismail³, Sarmad Nozad Mahmood⁴, Mohammed Mudhafar Shakir⁵, Sameer Alani⁶, Hussein Alsariera¹

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2103-2127, 2024, DOI:10.32604/cmes.2023.029509 - 15 December 2023

Abstract Intelligent traffic control requires accurate estimation of the road states and incorporation of adaptive or dynamically adjusted intelligent algorithms for making the decision. In this article, these issues are handled by proposing a novel framework for traffic control using vehicular communications and Internet of Things data. The framework integrates Kalman filtering and Q-learning. Unlike smoothing Kalman filtering, our data fusion Kalman filter incorporates a process-aware model which makes it superior in terms of the prediction error. Unlike traditional Q-learning, our Q-learning algorithm enables adaptive state quantization by changing the threshold of separating low traffic from… More >

Peiyuan Jiang¹, Weijun Pan^1,*, Jian Zhang¹, Teng Wang¹, Junxiang Huang²

CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 911-940, 2023, DOI:10.32604/cmc.2023.041772 - 31 October 2023

Abstract

This study aims to address the deviation in downstream tasks caused by inaccurate recognition results when applying Automatic Speech Recognition (ASR) technology in the Air Traffic Control (ATC) field. This paper presents a novel cascaded model architecture, namely Conformer-CTC/Attention-T5 (CCAT), to build a highly accurate and robust ATC speech recognition model. To tackle the challenges posed by noise and fast speech rate in ATC, the Conformer model is employed to extract robust and discriminative speech representations from raw waveforms. On the decoding side, the Attention mechanism is integrated to facilitate precise alignment between input features and

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Ahmed Alsheikhy^1,*, Yahia Said¹, Tawfeeq Shawly²

Computer Systems Science and Engineering, Vol.46, No.1, pp. 1109-1126, 2023, DOI:10.32604/csse.2023.035135 - 20 January 2023

Abstract Due to excessive car usage, pollution and traffic have increased. In urban cities in Saudi Arabia, such as Riyadh and Jeddah, drivers and air quality suffer from traffic congestion. Although the government has implemented numerous solutions to resolve this issue or reduce its effect on the environment and residents, it still exists and is getting worse. This paper proposes an intelligent, adaptive, practical, and feasible deep learning method for intelligent traffic control. It uses an Internet of Things (IoT) sensor, a camera, and a Convolutional Neural Network (CNN) tool to control traffic in real time.… More >

I. Ambika^1,*, Surbhi Bhatia², Shakila Basheer³, Pankaj Dadheech⁴

Computer Systems Science and Engineering, Vol.45, No.2, pp. 1323-1342, 2023, DOI:10.32604/csse.2023.030786 - 03 November 2022

Abstract A set of mobile devices that employs wireless transmission for communication is termed Mobile Ad hoc Networks (MANETs). Offering better communication services among the users in a centralized organization is the primary objective of the MANET. Due to the features of MANET, this can directly End-to-End Delay (EED) the Quality of Service (QoS). Hence, the implementation of resource management becomes an essential issue in MANETs. This paper focuses on the efficient Resource Allocation (RA) for many types of Traffic Flows (TF) in MANET. In Mobile Ad hoc Networks environments, the main objective of Resource Allocation… More >

Fangwei Zhang^1,2, Yi Zhao^3,*, Jun Ye⁴, Shuhong Wang⁵, Jingyi Hu⁶

CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.2, pp. 1589-1602, 2023, DOI:10.32604/cmes.2022.022431 - 27 October 2022

Abstract The purpose of this study is to reduce the uncertainty in the calculation process on hesitant fuzzy sets (HFSs). The innovation of this study is to unify the cardinal numbers of hesitant fuzzy elements (HFEs) in a special way. Firstly, a probability density function is assigned for any given HFE. Thereafter, equal-probability transformation is introduced to transform HFEs with different cardinal numbers on the condition into the same probability density function. The characteristic of this transformation is that the higher the consistency of the membership degrees in HFEs, the higher the credibility of the mentioned More >

Zhibo Gao^1,2, Kejun Long^1,2,*, Chaoqun Li², Wei Wu^1,2, Lee. D. Han³

CMC-Computers, Materials & Continua, Vol.61, No.1, pp. 345-361, 2019, DOI:10.32604/cmc.2019.06235

Abstract One problem with the existing dynamic exclusive bus lane strategies is that bus signal priority strategies with multi-phase priority request at intersections are not adequately considered. The principle of bus signal priority level was designed based on the isolated multi-phase structure principle consideration of the bus signal priority, and a new priority approach for the dynamic exclusive bus lane was proposed. Two types of priority strategies, green extension and red truncation, were proposed for current phase and next phase buses, respectively. The control parameters including minimum green time, green extension time, maximum green time and… More >

Kaijun Xu^∗, Yusheng Yao, Shanshan Li

Computer Systems Science and Engineering, Vol.33, No.5, pp. 335-344, 2018, DOI:10.32604/csse.2018.33.335

Abstract The flight lateral conflict model which is based on human subjective factors has always been a research hotspot for training flight. In order to effectively evaluate the safety interval and lateral collision risk in training airspace, in this paper, pilot subjective factors were modeled. It was studied in lateral conflict risk of low altitude complex flight by flight performance shaping factor. By analyzing flight data of a flight training institution in China, it is pointed that the lateral collision risk in specific training airspace meets the requirement of safety target level of international civil aviation More >

Kaijun Xu¹, Xueting Chen², Yusheng Yao¹, Shanshan Li¹

Intelligent Automation & Soft Computing, Vol.24, No.3, pp. 603-611, 2018, DOI:10.31209/2018.100000027

Abstract The lateral conflict risk assessment of low-altitude training airspace strategic planning, which is based on the TSE errors has always been a difficult task for training flight research. In order to effectively evaluate the safety interval and lateral collision risk in training airspace, in this paper, TSE error performance using a weakly supervised learning method was modelled. First, the lateral probability density function of TSE is given by using a multidimensional random variable covariance matrix, and the risk model of a training flight lateral collision based on TSE error is established. The lateral conflict risk More >