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 >

Xiaoyan Zhu¹, Ruchun Jia², Tingrui Zhang³, Song Yao^4,*

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 4363-4377, 2024, DOI:10.32604/cmc.2023.045615 - 26 March 2024

Abstract The traditional air traffic control information sharing data has weak security characteristics of personal privacy data and poor effect, which is easy to leads to the problem that the data is usurped. Starting from the application of the ATC (automatic train control) network, this paper focuses on the zero trust and zero trust access strategy and the tamper-proof method of information-sharing network data. Through the improvement of ATC’s zero trust physical layer authentication and network data distributed feature differentiation calculation, this paper reconstructs the personal privacy scope authentication structure and designs a tamper-proof method of… 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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Ligang Yuan^1,*, Jiazhi Jin¹, Yan Xu², Ningning Zhang³, Bing Zhang⁴

Computer Systems Science and Engineering, Vol.44, No.2, pp. 1171-1185, 2023, DOI:10.32604/csse.2023.027221 - 15 June 2022

Abstract Weather is a key factor affecting the control of air traffic. Accurate recognition and classification of similar weather scenes in the terminal area is helpful for rapid decision-making in air traffic flow management. Current researches mostly use traditional machine learning methods to extract features of weather scenes, and clustering algorithms to divide similar scenes. Inspired by the excellent performance of deep learning in image recognition, this paper proposes a terminal area similar weather scene classification method based on improved deep convolution embedded clustering (IDCEC), which uses the combination of the encoding layer and the decoding… 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 >