Aamer Khan¹, Insaf Ullah^2,*, Fahad Algarni³, Muhammad Naeem¹, M. Irfan Uddin⁴, Muhammad Asghar Khan²

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4293-4306, 2022, DOI:10.32604/cmc.2022.017318

Abstract Recent years have witnessed growing scientific research interest in the Internet of Things (IoT) technologies, which supports the development of a variety of applications such as health care, Industry 4.0, agriculture, ecological data management, and other various domains. IoT utilizes the Internet as a prime medium of communication for both single documents as well as multi-digital messages. However, due to the wide-open nature of the Internet, it is important to ensure the anonymity, untraceably, confidentiality, and unforgeability of communication with efficient computational complexity and low bandwidth. We designed a light weight and secure proxy blind signcryption for multi-digital messages based… More >

Hyun Kyu Shin¹, Ha Young Kim², Sang Hyo Lee^3,*

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5059-5071, 2022, DOI:10.32604/cmc.2022.017262

Abstract The durability performance of reinforced concrete (RC) building structures is significantly affected by the corrosion of the steel reinforcement due to chloride penetration, thus, the chloride ion diffusion coefficient should be investigated through experiments or theoretical equations to assess the durability of an RC structure. This study aims to predict the chloride ion diffusion coefficient of concrete, a heterogeneous material. A convolutional neural network (CNN)-based regression model that learns the condition of the concrete surface through deep learning, is developed to efficiently obtain the chloride ion diffusion coefficient. For the model implementation to determine the chloride ion diffusion coefficient, concrete… More >

Talha Ahmed Khan, Khizar Abbas, Afaq Muhammad, Wang-Cheol Song^*

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4323-4340, 2022, DOI:10.32604/cmc.2022.017118

Abstract The scope of the 5G network is not only limited to the enhancements in the form of the quality of service (QoS), but it also includes a wide range of services with various requirements. Besides this, many approaches and platforms are under the umbrella of 5G to achieve the goals of end-to-end service provisioning. However, the management of multiple services over heterogeneous platforms is a complex task. Each platform and service have various requirements to be handled by domain experts. Still, if the next-generation network management is dependent on manual updates, it will become impossible to provide seamless service provisioning… More >

Shubha Sumesh¹, John Yearwood¹, Shamsul Huda¹ and Shafiq Ahmad^2,*

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4503-4521, 2022, DOI:10.32604/cmc.2022.015474

Abstract

Clinical Study and automatic diagnosis of electrocardiogram (ECG) data always remain a challenge in diagnosing cardiovascular activities. The analysis of ECG data relies on various factors like morphological features, classification techniques, methods or models used to diagnose and its performance improvement. Another crucial factor in the methodology is how to train the model for each patient. Existing approaches use standard training model which faces challenges when training data has variation due to individual patient characteristics resulting in a lower detection accuracy. This paper proposes an adaptive approach to identify performance improvement in building a training model that analyze global training… More >

Nasir Mahmood^*, Muhammad Usman Ghani Khan

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4411-4428, 2022, DOI:10.32604/cmc.2022.013956

Abstract This study proposes an architecture for the prediction of extremist human behaviour from projected suicide bombings. By linking ‘dots’ of police data comprising scattered information of people, groups, logistics, locations, communication, and spatiotemporal characters on different social media groups, the proposed architecture will spawn beneficial information. This useful information will, in turn, help the police both in predicting potential terrorist events and in investigating previous events. Furthermore, this architecture will aid in the identification of criminals and their associates and handlers. Terrorism is psychological warfare, which, in the broadest sense, can be defined as the utilisation of deliberate violence for… More >

Mosleh M. Abualhaj^*, Abdelrahman H. Hussein, Qasem M. Kharma, Qusai Y. Shambour, Sumaya N. Al-Khatib

Intelligent Automation & Soft Computing, Vol.31, No.3, pp. 1971-1980, 2022, DOI:10.32604/iasc.2022.021458

Abstract IPv6 protocol is the future of IP networks due to its large IP address capacity. One of the key consequences of this large capacity is that the IP protocol header has enlarged from 20-byte in IPv4 to 40-byte in IPv6. This will consume a considerable share of the bandwidth (BW) for VoIP applications, which produce small packets in tens of bytes only. To handle this issue, we have introduced an efficient technique to use the superfluous fields in the VoIP packet header, including the IPv6 header, to hold the voice data of the packet. This introduced technique is called the… More >

Himanshu Padole^*, S. D. Joshi, Tapan K. Gandhi

Intelligent Automation & Soft Computing, Vol.31, No.3, pp. 1655-1669, 2022, DOI:10.32604/iasc.2022.021310

Abstract Many methods have been proposed in the literature for diagnosis of Alzheimer's disease (AD) in the early stages, among which the graph-based methods have been more popular, because of their capability to utilize the relational information among different brain regions. Here, we design a novel graph signal processing based integrated AD detection model using multimodal deep learning that simultaneously utilizes both the static and the dynamic brain connectivity based features extracted from resting-state fMRI (rs-fMRI) data to detect AD in the early stages. First, our earlier proposed state-space model (SSM) based graph connectivity dynamics characterization method is used to design… More >

Mustafa Kara^1,*, Muhammed Ali Aydın^1,2, Hasan Hüseyin Balık¹

Intelligent Automation & Soft Computing, Vol.31, No.3, pp. 1901-1918, 2022, DOI:10.32604/iasc.2022.021309

Abstract Peer-to-peer VoIP applications are exposed to threats in the Internet environment as they carry out conversations over the Internet, which is an electronic communication line, and its security has always been largely a matter of concern. Authentication of the caller is the first line of defense among the security principles and is an important principle to provide security in VoIP application. Authentication methods in VoIP applications are usually based on trusted third parties or through centralized architecture. This situation creates problems in terms of single point of failure and privacy in call security over IP based communications. However, blockchain technology… More >

Hisham Raad Jafer Merzeh^1,*, Mustafa Kara², Muhammed Ali Aydın³, Hasan Hüseyin Balık¹

Intelligent Automation & Soft Computing, Vol.31, No.3, pp. 1953-1970, 2022, DOI:10.32604/iasc.2022.021297

Abstract The Internet of things (IoT) became quickly one of the most popular and most discussed topics in research. Studies paid attention to the Internet stuff, primarily to new products that aim to achieve greater efficiency and simplicity in life. IoT may cover several fields of the smart environment. Because of the data exposure that occurs when data is transferred via various channels, data protection issues have become a major problem as the company continues to expand. When user privacy and property are taken into consideration, the situation may become much worse. As a result, the authentication process for communicating entities… More >

Asadullah Shaikh^1,*, Syed Rizwan², Abdullah Alghamdi¹, Noman Islam², M.A. Elmagzoub¹, Darakhshan Syed²

Intelligent Automation & Soft Computing, Vol.31, No.3, pp. 1529-1546, 2022, DOI:10.32604/iasc.2022.021163

Abstract Fault localization is one of the main tasks of software debugging. Developers spend a lot of time, cost, and effort to locate the faults correctly manually. For reducing this effort, many automatic fault localization techniques have been proposed, which inputs test suites and outputs a sorted list of faulty entities of the program. For further enhancement in this area, we developed a system called SILearning, which is based on invariant analysis. It learns from some existing fixed bugs to locate faulty methods in the program. It combines machine-learned ranking, program invariant differences, and spectrum-based fault localization (SBFL). Using the execution… More >