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  • Open Access

    ARTICLE

    Digital Twin Modeling and Simulation Optimization of Transmission Front and Middle Case Assembly Line

    Xianfeng Cao1, Meihua Yao2, Yahui Zhang3,*, Xiaofeng Hu4, Chuanxun Wu3

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 3233-3253, 2024, DOI:10.32604/cmes.2023.030773

    Abstract As the take-off of China’s macro economy, as well as the rapid development of infrastructure construction, real estate industry, and highway logistics transportation industry, the demand for heavy vehicles is increasing rapidly, the competition is becoming increasingly fierce, and the digital transformation of the production line is imminent. As one of the most important components of heavy vehicles, the transmission front and middle case assembly lines have a high degree of automation, which can be used as a pilot for the digital transformation of production. To ensure the visualization of digital twins (DT), consistent control logic, and real-time data interaction,… More > Graphic Abstract

    Digital Twin Modeling and Simulation Optimization of Transmission Front and Middle Case Assembly Line

  • Open Access

    ARTICLE

    Deep Learning-Based Digital Image Forgery Detection Using Transfer Learning

    Emad Ul Haq Qazi1,*, Tanveer Zia1, Muhammad Imran2, Muhammad Hamza Faheem1

    Intelligent Automation & Soft Computing, Vol.38, No.3, pp. 225-240, 2023, DOI:10.32604/iasc.2023.041181

    Abstract Deep learning is considered one of the most efficient and reliable methods through which the legitimacy of a digital image can be verified. In the current cyber world where deepfakes have shaken the global community, confirming the legitimacy of a digital image is of great importance. With the advancements made in deep learning techniques, now we can efficiently train and develop state-of-the-art digital image forensic models. The most traditional and widely used method by researchers is convolution neural networks (CNN) for verification of image authenticity but it consumes a considerable number of resources and requires a large dataset for training.… More >

  • Open Access

    ARTICLE

    Coverless Image Steganography System Based on Maze Game Generation

    Al Hussien Seddik Saad1, Mohammed S. Reda2, Gamal M. Behery2, Ahmed A. El-harby2, Mohammed Baz3, Mohamed Abouhawwash4,5,*, Ahmed Ismail Ebada6

    Intelligent Automation & Soft Computing, Vol.38, No.2, pp. 125-138, 2023, DOI:10.32604/iasc.2023.032084

    Abstract The trend of digital information transformation has become a topic of interest. Many data are threatening; thus, protecting such data from attackers is considered an essential process. Recently, a new methodology for data concealing has been suggested by researchers called coverless steganography. Coverless steganography can be accomplished either by building an image database to match its image subblocks with the secret message to obtain the stego image or by generating an image. This paper proposes a coverless image steganography system based on pure image generation using secret message bits with a capacity higher than the other traditional systems. The system… More >

  • Open Access

    ARTICLE

    Using MsfNet to Predict the ISUP Grade of Renal Clear Cell Carcinoma in Digital Pathology Images

    Kun Yang1,2,3, Shilong Chang1, Yucheng Wang1, Minghui Wang1, Jiahui Yang1, Shuang Liu1,2,3, Kun Liu1,2,3, Linyan Xue1,2,3,*

    CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 393-410, 2024, DOI:10.32604/cmc.2023.044994

    Abstract Clear cell renal cell carcinoma (ccRCC) represents the most frequent form of renal cell carcinoma (RCC), and accurate International Society of Urological Pathology (ISUP) grading is crucial for prognosis and treatment selection. This study presents a new deep network called Multi-scale Fusion Network (MsfNet), which aims to enhance the automatic ISUP grade of ccRCC with digital histopathology pathology images. The MsfNet overcomes the limitations of traditional ResNet50 by multi-scale information fusion and dynamic allocation of channel quantity. The model was trained and tested using 90 Hematoxylin and Eosin (H&E) stained whole slide images (WSIs), which were all cropped into 320… More >

  • Open Access

    ARTICLE

    Physics Based Digital Twin Modelling from Theory to Concept Implementation Using Coiled Springs Used in Suspension Systems

    Mohamed Ammar1,*, Alireza Mousavi1, Hamed Al-Raweshidy2,*

    Digital Engineering and Digital Twin, Vol.2, pp. 1-31, 2024, DOI:10.32604/dedt.2023.044930

    Abstract The advent of technology around the globe based on the Internet of Things, Cloud Computing, Big Data, Cyber-Physical Systems, and digitalisation. This advancement introduced industry 4.0. It is challenging to measure how enterprises adopt the new technologies. Industry 4.0 introduced Digital Twins, given that no specific terms or definitions are given to Digital Twins still challenging to define or conceptualise the Digital Twins. Many academics and industries still use old technologies, naming it Digital Twins. This young technology is in danger of reaching the plateau despite the immense benefit to sectors. This paper proposes a novel and unique definition for… More >

  • Open Access

    EDITORIAL

    Introduction to the Journal of Digital Engineering and Digital Twin

    Satya Atluri1, Leiting Dong2,*

    Digital Engineering and Digital Twin, Vol.1, pp. 1-2, 2023, DOI:10.32604/dedt.2023.028823

    Abstract This article has no abstract. More >

  • Open Access

    ARTICLE

    Integration of Digital Twins and Artificial Intelligence for Classifying Cardiac Ischemia

    Mohamed Ammar1,*, Hamed Al-Raweshidy2,*

    Journal on Artificial Intelligence, Vol.5, pp. 195-218, 2023, DOI:10.32604/jai.2023.045199

    Abstract Despite advances in intelligent medical care, difficulties remain. Due to its complicated governance, designing, planning, improving, and managing the cardiac system remains difficult. Oversight, including intelligent monitoring, feedback systems, and management practises, is unsuccessful. Current platforms cannot deliver lifelong personal health management services. Insufficient accuracy in patient crisis warning programmes. No frequent, direct interaction between healthcare workers and patients is visible. Physical medical systems and intelligent information systems are not integrated. This study introduces the Advanced Cardiac Twin (ACT) model integrated with Artificial Neural Network (ANN) to handle real-time monitoring, decision-making, and crisis prediction. THINGSPEAK is used to create an… More >

  • Open Access

    ARTICLE

    Use of Geographic Information System and Digital Elevation Model to Analyze the Hydro-Morphometric Characteristics of the Tshopo River Sub-Catchments, Democratic Republic of Congo

    Utilisation du système d’information géographique et modèle numérique de terrain dans l’analyse des caractéristiques hydro-morphométriques des sous-bassins versants de la rivière Tshopo, République démocratique du Congo

    Faidance Mashauri1,2,*, Mokili Mbuluyo1,3, Nsalambi Nkongolo2,4

    Revue Internationale de Géomatique, Vol.32, pp. 99-122, 2023, DOI:10.32604/rig.2023.044899

    Abstract The analysis and quantification of hydro-morphometric characteristics are essential for better management of water resources and more effective planning of hydroelectric projects in the Tshopo basin. Unfortunately, few studies have been carried out to assess these characteristics at the scale of this basin. Our methodological approach consists of using Geographic Information System (GIS) software analysis tools applied to the Digital Elevation Model (DEM) derived from the Advanced Land Observing Satellite (ALOS) World 3D-30m image. This enabled us to automatically extract the hydrographic network and generate the Tshopo sub-watersheds. The results of this analysis show that the Tshopo catchment area is… More >

  • Open Access

    ARTICLE

    Digital Image Encryption Algorithm Based on Double Chaotic Map and LSTM

    Luoyin Feng1,*, Jize Du2, Chong Fu1

    CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 1645-1662, 2023, DOI:10.32604/cmc.2023.042630

    Abstract In the era of network communication, digital image encryption (DIE) technology is critical to ensure the security of image data. However, there has been limited research on combining deep learning neural networks with chaotic mapping for the encryption of digital images. So, this paper addresses this gap by studying the generation of pseudo-random sequences (PRS) chaotic signals using dual logistic chaotic maps. These signals are then predicted using long and short-term memory (LSTM) networks, resulting in the reconstruction of a new chaotic signal. During the research process, it was discovered that there are numerous training parameters associated with the LSTM… More >

  • Open Access

    ARTICLE

    Hybrid Dynamic Optimization for Multilevel Security System in Disseminating Confidential Information

    Shahina Anwarul1, Sunil Kumar2, Ashok Bhansali3, Hammam Alshazly4,*, Hany S. Hussein5,6

    Computer Systems Science and Engineering, Vol.47, No.3, pp. 3145-3163, 2023, DOI:10.32604/csse.2023.041061

    Abstract Security systems are the need of the hour to protect data from unauthorized access. The dissemination of confidential information over the public network requires a high level of security. The security approach such as steganography ensures confidentiality, authentication, integrity, and non-repudiation. Steganography helps in hiding the secret data inside the cover media so that the attacker can be confused during the transmission process of secret data between sender and receiver. Therefore, we present an efficient hybrid security model that provides multifold security assurance. To this end, a rectified Advanced Encryption Standard (AES) algorithm is proposed to overcome the problems existing… More >

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