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  • Open Access

    ARTICLE

    Identifying Cancer Disease Using Softmax-Feed Forward Recurrent Neural Classification

    P. Saranya*, P. Asha

    Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 1137-1149, 2023, DOI:10.32604/iasc.2023.031470

    Abstract In today’s growing modern world environment, as human food activities are changing, it is affecting human health, thus leading to diseases like cancer. Cancer is a complex disease with many subtypes that affect human health without premature treatment and cause death. So the analysis of early diagnosis and prognosis of cancer studies can improve clinical management by analyzing various features of observation, which has become necessary to classify the type in cancer research. The research needs importance to organize the risk of the cancer patients based on data analysis to predict the result of premature treatment. This paper introduces a… More >

  • Open Access

    ARTICLE

    Efficient Hardware Design of a Secure Cancellable Biometric Cryptosystem

    Lamiaa A. Abou Elazm1,2, Walid El-Shafai3,4, Sameh Ibrahim2, Mohamed G. Egila1, H. Shawkey1, Mohamed K. H. Elsaid2, Naglaa F. Soliman5, Hussah Nasser AlEisa6,*, Fathi E. Abd El-Samie3

    Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 929-955, 2023, DOI:10.32604/iasc.2023.031386

    Abstract Biometric security is a growing trend, as it supports the authentication of persons using confidential biometric data. Most of the transmitted data in multimedia systems are susceptible to attacks, which affect the security of these systems. Biometric systems provide sufficient protection and privacy for users. The recently-introduced cancellable biometric recognition systems have not been investigated in the presence of different types of attacks. In addition, they have not been studied on different and large biometric datasets. Another point that deserves consideration is the hardware implementation of cancellable biometric recognition systems. This paper presents a suggested hybrid cancellable biometric recognition system… More >

  • Open Access

    ARTICLE

    Real-Time Safety Helmet Detection Using Yolov5 at Construction Sites

    Kisaezehra1, Muhammad Umer Farooq1,*, Muhammad Aslam Bhutto2, Abdul Karim Kazi1

    Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 911-927, 2023, DOI:10.32604/iasc.2023.031359

    Abstract The construction industry has always remained the economic and social backbone of any country in the world where occupational health and safety (OHS) is of prime importance. Like in other developing countries, this industry pays very little, rather negligible attention to OHS practices in Pakistan, resulting in the occurrence of a wide variety of accidents, mishaps, and near-misses every year. One of the major causes of such mishaps is the non-wearing of safety helmets (hard hats) at construction sites where falling objects from a height are unavoidable. In most cases, this leads to serious brain injuries in people present at… More >

  • Open Access

    ARTICLE

    AI-Based Intelligent Model to Predict Epidemics Using Machine Learning Technique

    Liaqat Ali1, Saif E. A. Alnawayseh2, Mohammed Salahat3, Taher M. Ghazal4,5,*, Mohsen A. A. Tomh6, Beenu Mago7

    Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 1095-1104, 2023, DOI:10.32604/iasc.2023.031335

    Abstract The immediate international spread of severe acute respiratory syndrome revealed the potential threat of infectious diseases in a closely integrated and interdependent world. When an outbreak occurs, each country must have a well-coordinated and preventative plan to address the situation. Information and Communication Technologies have provided innovative approaches to dealing with numerous facets of daily living. Although intelligent devices and applications have become a vital part of our everyday lives, smart gadgets have also led to several physical and psychological health problems in modern society. Here, we used an artificial intelligence AI-based system for disease prediction using an Artificial Neural… More >

  • Open Access

    ARTICLE

    Novel Path Counting-Based Method for Fractal Dimension Estimation of the Ultra-Dense Networks

    Farid Nahli11, Alexander Paramonov1, Naglaa F. Soliman2, Hussah Nasser AlEisa3,*, Reem Alkanhel2, Ammar Muthanna1, Abdelhamied A. Ateya4

    Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 561-572, 2023, DOI:10.32604/iasc.2023.031299

    Abstract Next-generation networks, including the Internet of Things (IoT), fifth-generation cellular systems (5G), and sixth-generation cellular systems (6G), suffer from the dramatic increase of the number of deployed devices. This puts high constraints and challenges on the design of such networks. Structural changing of the network is one of such challenges that affect the network performance, including the required quality of service (QoS). The fractal dimension (FD) is considered one of the main indicators used to represent the structure of the communication network. To this end, this work analyzes the FD of the network and its use for telecommunication networks investigation… More >

  • Open Access

    ARTICLE

    Health Data Deduplication Using Window Chunking-Signature Encryption in Cloud

    G. Neelamegam*, P. Marikkannu

    Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 1079-1093, 2023, DOI:10.32604/iasc.2023.031283

    Abstract Due to the development of technology in medicine, millions of health-related data such as scanning the images are generated. It is a great challenge to store the data and handle a massive volume of data. Healthcare data is stored in the cloud-fog storage environments. This cloud-Fog based health model allows the users to get health-related data from different sources, and duplicated information is also available in the background. Therefore, it requires an additional storage area, increase in data acquisition time, and insecure data replication in the environment. This paper is proposed to eliminate the de-duplication data using a window size… More >

  • Open Access

    ARTICLE

    Anomaly Detection in Social Media Texts Using Optimal Convolutional Neural Network

    Swarna Sudha Muppudathi1, Valarmathi Krishnasamy2,*

    Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 1027-1042, 2023, DOI:10.32604/iasc.2023.031165

    Abstract Social Networking Sites (SNSs) are nowadays utilized by the whole world to share ideas, images, and valuable contents by means of a post to reach a group of users. The use of SNS often inflicts the physical and the mental health of the people. Nowadays, researchers often focus on identifying the illegal behaviors in the SNS to reduce its negative influence. The state-of-art Natural Language processing techniques for anomaly detection have utilized a wide annotated corpus to identify the anomalies and they are often time-consuming as well as certainly do not guarantee maximum accuracy. To overcome these issues, the proposed… More >

  • Open Access

    ARTICLE

    Mobility Aware Zone-Based Routing in Vehicle Ad hoc Networks Using Hybrid Metaheuristic Algorithm

    C. Nandagopal1,*, P. Siva Kumar2, R. Rajalakshmi3, S. Anandamurugan4

    Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 113-126, 2023, DOI:10.32604/iasc.2023.031103

    Abstract Vehicle Ad hoc Networks (VANETs) have high mobility and a randomized connection structure, resulting in extremely dynamic behavior. Several challenges, such as frequent connection failures, sustainability, multi-hop data transfer, and data loss, affect the effectiveness of Transmission Control Protocols (TCP) on such wireless ad hoc networks. To avoid the problem, in this paper, mobility-aware zone-based routing in VANET is proposed. To achieve this concept, in this paper hybrid optimization algorithm is presented. The hybrid algorithm is a combination of Ant colony optimization (ACO) and artificial bee colony optimization (ABC). The proposed hybrid algorithm is designed for the routing process which… More >

  • Open Access

    ARTICLE

    Proposed Privacy Preservation Technique for Color Medical Images

    Walid El-Shafai1,2, Hayam A. Abd El-Hameed3, Noha A. El-Hag4, Ashraf A. M. Khalaf3, Naglaa F. Soliman5, Hussah Nasser AlEisa6,*, Fathi E. Abd El-Samie1

    Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 719-732, 2023, DOI:10.32604/iasc.2023.031079

    Abstract Nowadays, the security of images or information is very important. This paper introduces a proposed hybrid watermarking and encryption technique for increasing medical image security. First, the secret medical image is encrypted using Advanced Encryption Standard (AES) algorithm. Then, the secret report of the patient is embedded into the encrypted secret medical image with the Least Significant Bit (LSB) watermarking algorithm. After that, the encrypted secret medical image with the secret report is concealed in a cover medical image, using Kekre’s Median Codebook Generation (KMCG) algorithm. Afterwards, the stego-image obtained is split into 16 parts. Finally, it is sent to… More >

  • Open Access

    ARTICLE

    Smart Lung Tumor Prediction Using Dual Graph Convolutional Neural Network

    Abdalla Alameen*

    Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 369-383, 2023, DOI:10.32604/iasc.2023.031039

    Abstract A significant advantage of medical image processing is that it allows non-invasive exploration of internal anatomy in great detail. It is possible to create and study 3D models of anatomical structures to improve treatment outcomes, develop more effective medical devices, or arrive at a more accurate diagnosis. This paper aims to present a fused evolutionary algorithm that takes advantage of both whale optimization and bacterial foraging optimization to optimize feature extraction. The classification process was conducted with the aid of a convolutional neural network (CNN) with dual graphs. Evaluation of the performance of the fused model is carried out with… More >

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