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31 pages, 3949 KB

Open AccessArticle

A Railway Mobile Terminal Malware Detection Method Based on SE-ResNet

by Honglei Yao, Yijie Yang, Ning Dong and Wenjia Niu

Appl. Sci. 2025, 15(19), 10760; https://doi.org/10.3390/app151910760 - 6 Oct 2025

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This paper proposes a residual network model integrated with an attention mechanism module for the detection and classification of malware on railway mobile terminals. To address the issues of insufficient and imbalanced samples, Wasserstein Generative Adversarial Networks (WGANs) are utilized to synthesize grayscale image data of malware with high similarity to real samples. The performance of the model is evaluated on the publicly available CIC-InvesAndMal2019 dataset and an extended balanced dataset. Experimental results demonstrate that the synergistic integration of residual networks, WGANs, and attention mechanisms significantly enhances the performance of the malware detection model. In the context of railway applications, the proposed approach also achieves favorable classification performance when applied to image datasets derived from malware samples of railway mobile terminals. Multiple ablation studies are conducted to individually validate the contributions of each technical component in improving the classification model’s efficacy. The adoption of the SE-ResNet architecture combined with WGAN-based data augmentation presents a practical and efficient technical solution. Full article

(This article belongs to the Special Issue Intelligent Data Processing and Management: Technologies and Applications)

16 pages, 2722 KB

Open AccessArticle

Potentially Toxic Elements in Urban Soils from Public-Access Areas in the Rapidly Growing Megacity of Lagos, Nigeria

by Abimbola O. Famuyiwa, Christine M. Davidson, Sesugh Ande and Aderonke O. Oyeyiola

Toxics 2022, 10(4), 154; https://doi.org/10.3390/toxics10040154 - 23 Mar 2022

Cited by 10 | Viewed by 4105

Abstract

Rapid urbanization can lead to significant environmental contamination with potentially toxic elements (PTEs). This is of concern because PTEs are accumulative, persistent, and can have detrimental effects on human health. Urban soil samples were obtained from parks, ornamental gardens, roadsides, railway terminals and locations close to industrial estates and dumpsites within the Lagos metropolis. Chromium, Cu, Fe, Mn, Ni, Pb and Zn concentrations were determined using inductively coupled plasma mass spectrometry following sample digestion with aqua regia and application of the BCR sequential extraction procedure. A wide range of analyte concentrations was found—Cr, 19–1830 mg/kg; Cu, 8–11,700 mg/kg; Fe, 7460–166,000 mg/kg; Mn, 135–6100 mg/kg; Ni, 4–1050 mg/kg; Pb, 10–4340 mg/kg; and Zn, 61–5620 mg/kg—with high levels in areas close to industrial plants and dumpsites. The proportions of analytes released in the first three steps of the sequential extraction were Fe (16%) < Cr (30%) < Ni (46%) < Mn (63%) < Cu (78%) < Zn (80%) < Pb (84%), indicating that there is considerable scope for PTE (re)mobilization. Human health risk assessment indicated non-carcinogenic risk for children and carcinogenic risk for both children and adults. Further monitoring of PTE in the Lagos urban environment is therefore recommended. Full article

(This article belongs to the Special Issue Potentially Toxic Elements Pollution in Urban and Suburban Environments)

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17 pages, 3104 KB

Open AccessArticle

Data Sensing and Processing Tensioning System Based on the Internet of Things

by Xiaowen Chen and Guanci Yang

Appl. Sci. 2019, 9(2), 310; https://doi.org/10.3390/app9020310 - 16 Jan 2019

Cited by 1 | Viewed by 3188

Abstract

Tensioning is an important process for producing prestressed concrete beams and directly affects bridge performance and driving safety. Active sensing and management of tensioning process data can improve the efficiency of quality monitoring and level of prestressed concrete beams. To realize remote collection and quality monitoring of tensioning process data, a framework for data sensing and processing of tensioning system based on the Internet of Things (IoT) is proposed in this study. Firstly, we investigate the technical framework and techniques of the system and designs a work flow of sensing, transport, and application service layers. The architecture of the tensioning system is presented. Then we propose a data acquisition and preprocessing method for the sensing layer, put forwards the data-pushing mechanism of the transport layer, and designs the function and work flow of the application service layer. After that, .NET platform and Android Studio are used to implement the tensioning system based on Browser/Server (B/S) architecture and mobile terminals. Finally, the case results of the system in seven precast beam fields in the Hubei section of Zhengzhou–Wanzhou high-speed Railway are given, which show that the developed system realizes collection, active pushing, and remote monitoring of tensioning process data. Full article

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