Walid El-Shafai^1,2, Amira A. Mahmoud¹, El-Sayed M. El-Rabaie¹, Taha E. Taha¹, Osama F. Zahran¹, Adel S. El-Fishawy¹, Naglaa F. Soliman³, Amel A. Alhussan^4,*, Fathi E. Abd El-Samie¹

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 3455-3472, 2022, DOI:10.32604/cmc.2022.028722

Abstract The segmentation process requires separating the image region into sub-regions of similar properties. Each sub-region has a group of pixels having the same characteristics, such as texture or intensity. This paper suggests an efficient hybrid segmentation approach for different medical image modalities based on particle swarm optimization (PSO) and improved fast fuzzy C-means clustering (IFFCM) algorithms. An extensive comparative study on different medical images is presented between the proposed approach and other different previous segmentation techniques. The existing medical image segmentation techniques incorporate clustering, thresholding, graph-based, edge-based, active contour, region-based, and watershed algorithms. This paper extensively analyzes and summarizes the… More >

Muhammad Naeem Akbar^1,*, Farhan Riaz¹, Ahmed Bilal Awan¹, Muhammad Attique Khan², Usman Tariq³, Saad Rehman²

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 2555-2576, 2022, DOI:10.32604/cmc.2022.028696

Abstract Human Action Recognition (HAR) is a current research topic in the field of computer vision that is based on an important application known as video surveillance. Researchers in computer vision have introduced various intelligent methods based on deep learning and machine learning, but they still face many challenges such as similarity in various actions and redundant features. We proposed a framework for accurate human action recognition (HAR) based on deep learning and an improved features optimization algorithm in this paper. From deep learning feature extraction to feature classification, the proposed framework includes several critical steps. Before training fine-tuned deep learning… More >

Farag Azzedin^*, Husam Suwad, Md Mahfuzur Rahman

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 3003-3020, 2022, DOI:10.32604/cmc.2022.028646

Abstract This article presents an asset-based security system where security practitioners build their systems based on information they own and not solicited by observing attackers’ behavior. Current security solutions rely on information coming from attackers. Examples are current monitoring and detection security solutions such as intrusion prevention/detection systems and firewalls. This article envisions creating an imbalance between attackers and defenders in favor of defenders. As such, we are proposing to flip the security game such that it will be led by defenders and not attackers. We are proposing a security system that does not observe the behavior of the attack. On… More >

Amel Boudelaa¹, Zohra Abdelhafidi¹, Nasreddine Lagraa¹, Chaker Abdelaziz Kerrache¹, Muhammad Bilal², Daehan Kwak^3,*, Mohamed Bachir Yagoubi¹

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 2495-2512, 2022, DOI:10.32604/cmc.2022.028619

Abstract Vehicular Social Networks (VSNs) is the bridge of social networks and Vehicular Ad-Hoc Networks (VANETs). VSNs are promising as they allow the exchange of various types of contents in large-scale through Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communication protocols. Vehicular Named Data Networking (VNDN) is an auspicious communication paradigm for the challenging VSN environment since it can optimize content dissemination by decoupling contents from their physical locations. However, content dissemination and caching represent crucial challenges in VSNs due to short link lifetime and intermittent connectivity caused by vehicles’ high mobility. Our aim with this paper is to improve content delivery and… More >

Hui Han^1,2, Wunan Wan^1,2,*, Jinquan Zhang^1,2, Zhi Qin^1,2, Xiaofang Qiu^1,2, Shibin Zhang^1,2, Jinyue Xia³

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 2651-2662, 2022, DOI:10.32604/cmc.2022.028607

Abstract With the growing maturity of blockchain technology, its peer-to-peer model and fully duplicated data storage pattern enable blockchain to act as a distributed ledger in untrustworthy environments. Blockchain storage has also become a research hotspot in industry, finance, and academia due to its security, and its unique data storage management model is gradually becoming a key technology to play its value in various fields’ applications. However, with the increasing amount of data written into the blockchain, the blockchain system faces many problems in its actual implementation of the application, such as high storage space occupation, low data flexibility and availability,… More >

K. Vijaya Kumar¹, E. Laxmi Lydia², Ashit Kumar Dutta³, Velmurugan Subbiah Parvathy⁴, Gobi Ramasamy⁵, Irina V. Pustokhina^6,*, Denis A. Pustokhin⁷

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 2541-2554, 2022, DOI:10.32604/cmc.2022.028570

Abstract Recently, big data becomes evitable due to massive increase in the generation of data in real time application. Presently, object detection and tracking applications becomes popular among research communities and finds useful in different applications namely vehicle navigation, augmented reality, surveillance, etc. This paper introduces an effective deep learning based object tracker using Automated Image Annotation with Inception v2 based Faster RCNN (AIA-IFRCNN) model in big data environment. The AIA-IFRCNN model annotates the images by Discriminative Correlation Filter (DCF) with Channel and Spatial Reliability tracker (CSR), named DCF-CSRT model. The AIA-IFRCNN technique employs Faster RCNN for object detection and tracking,… More >

Prasanalakshmi Balaji^1,*, B. Sri Revathi², Praveetha Gobinathan³, Shermin Shamsudheen³, Thavavel Vaiyapuri⁴

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 2275-2291, 2022, DOI:10.32604/cmc.2022.028560

Abstract Recently medical image classification plays a vital role in medical image retrieval and computer-aided diagnosis system. Despite deep learning has proved to be superior to previous approaches that depend on handcrafted features; it remains difficult to implement because of the high intra-class variance and inter-class similarity generated by the wide range of imaging modalities and clinical diseases. The Internet of Things (IoT) in healthcare systems is quickly becoming a viable alternative for delivering high-quality medical treatment in today’s e-healthcare systems. In recent years, the Internet of Things (IoT) has been identified as one of the most interesting research subjects in… More >

R. Meenakshi¹, R. Ponnusamy^1,*, Saleh Alghamdi², Osama Ibrahim Khalaf³, Youseef Alotaibi⁴

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 3473-3495, 2022, DOI:10.32604/cmc.2022.028540

Abstract In 2017, it was estimated that the number of persons of all ages visually affected would be two hundred and eighty-five million, of which thirty-nine million are blind. There are several innovative technical solutions available to facilitate the movement of these people. The next big challenge for technical people is to give cost-effective solutions. One of the challenges for people with visual impairments is navigating safely, recognizing obstacles, and moving freely between locations in unfamiliar environments. A new mobile application solution is developed, and the application can be installed in android mobile. The application will visualize the environment with portable… More >

Manar M. Aldaseen¹, Khaled M. Matrouk¹, Laiali H. Almazaydeh^2,*, Khaled M. Elleithy³

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 3969-3981, 2022, DOI:10.32604/cmc.2022.028520

Abstract The Wireless Sensor Networks (WSNs) are characterized by their widespread deployment due to low cost, but the WSNs are vulnerable to various types of attacks. To defend against the attacks, an effective security solution is required. However, the limits of these networks’ battery-based energy to the sensor are the most critical impediments to selecting cryptographic techniques. Consequently, finding a suitable algorithm that achieves the least energy consumption in data encryption and decryption and providing a highly protected system for data remains the fundamental problem. In this research, the main objective is to obtain data security during transmission by proposing a… More >

Awad Ali^1,*, Reyazur Rashid Irshad¹, Ahmed Abdu Alattaab¹, Aamir Fatahayab²

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 2663-2678, 2022, DOI:10.32604/cmc.2022.028503

Abstract The Wireless Sensor Network (WSN) is regarded as the fastest expanding technological trend in recent years due its application in a variety of sectors. In the monitoring region, several sensor nodes with various sensing capabilities are installed to gather appropriate data and communicate it to the gateway. The proposed system of the heterogeneous WSN employing LoRaWAN-Zigbee based hybrid communication is explored in this research study. To communicate in a network, two Long–Range Wide Area Network (LoRaWAN) sensor clusters and two Zigbee sensor clusters are employed, together with two Zigbee and LoRaWAN converters. The suggested Golden eagle shepherd optimization (GESO) method… More >