Dalia H. Elkamchouchi¹, Jaber S. Alzahrani², Hany Mahgoub^3,4, Amal S. Mehanna⁵, Anwer Mustafa Hilal^6,*, Abdelwahed Motwakel⁶, Abu Sarwar Zamani⁶, Ishfaq Yaseen⁶

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 6617-6634, 2022, DOI:10.32604/cmc.2022.031909

Abstract The recent technological developments have revolutionized the functioning of Wireless Sensor Network (WSN)-based industries with the development of Internet of Things (IoT). Internet of Drones (IoD) is a division under IoT and is utilized for communication amongst drones. While drones are naturally mobile, it undergoes frequent topological changes. Such alterations in the topology cause route election, stability, and scalability problems in IoD. Encryption is considered as an effective method to transmit the images in IoD environment. The current study introduces an Atom Search Optimization based Clustering with Encryption Technique for Secure Internet of Drones (ASOCE-SIoD) environment. The key objective of… More >

Heba G. Mohamed¹, Saud S. Alotaibi², Majdy M. Eltahir³, Heba Mohsen⁴, Manar Ahmed Hamza^5,*, Abu Sarwar Zamani⁵, Ishfaq Yaseen⁵, Abdelwahed Motwakel⁵

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5441-5458, 2022, DOI:10.32604/cmc.2022.031887

Abstract The Internet of Drones (IoD) offers synchronized access to organized airspace for Unmanned Aerial Vehicles (known as drones). The availability of inexpensive sensors, processors, and wireless communication makes it possible in real time applications. As several applications comprise IoD in real time environment, significant interest has been received by research communications. Since IoD operates in wireless environment, it is needed to design effective intrusion detection system (IDS) to resolve security issues in the IoD environment. This article introduces a metaheuristics feature selection with optimal stacked autoencoder based intrusion detection (MFSOSAE-ID) in the IoD environment. The major intention of the MFSOSAE-ID… More >

Arooj Nasir^1,2, Dumitru Baleanu^3,4,5, Ali Raza^6,*, Pervez Anwar⁷, Nauman Ahmed⁸, Muhammad Rafiq⁹, Tahir Nawaz Cheema¹⁰

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5717-5734, 2022, DOI:10.32604/cmc.2022.031879

Abstract In 2020, the reported cases were 0.12 million in the six regions to the official report of the World Health Organization (WHO). For most children infected with leprosy, 0.008629 million cases were detected under fifteen. The total infected ratio of the children population is approximately 4.4 million. Due to the COVID-19 pandemic, the awareness programs implementation has been disturbed. Leprosy disease still has a threat and puts people in danger. Nonlinear delayed modeling is critical in various allied sciences, including computational biology, computational chemistry, computational physics, and computational economics, to name a few. The time delay effect in treating leprosy… More >

Ngo Quang Trung, Nguyen Van Thanh^*

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 6535-6546, 2022, DOI:10.32604/cmc.2022.031815

Abstract Sustainable marketing, often known as green marketing, has grown in popularity over the last two decades. Government is currently putting pressure to encourage firms to become environmentally aware in multiple aspects like human and financial utilization, advertisement, and product movement. Different types of companies are including many environmental campaigns into their own products to take advantage of the problem. Although many scholars have addressed the relevance of green marketing as well as theory development, this study is unique in that it examines both techniques in a fuzzy context. The integrated Fuzzy Multicriteria Decision Making Model (MCDM) of the analytical hierarchy… More >

Abdullah A. Asiri¹, Muhammad Aamir², Ahmad Shaf^2,*, Tariq Ali², Muhammad Zeeshan³, Muhammad Irfan⁴, Khalaf A. Alshamrani¹, Hassan A. Alshamrani¹, Fawaz F. Alqahtani¹, Ali H. D. Alshehri¹

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5735-5753, 2022, DOI:10.32604/cmc.2022.031747

Abstract The precise brain tumor diagnosis is critical and shows a vital role in the medical support for treating tumor patients. Manual brain tumor segmentation for cancer analysis from many Magnetic Resonance Images (MRIs) created in medical practice is a problematic and timewasting task for experts. As a result, there is a critical necessity for more accurate computer-aided methods for early tumor detection. To remove this gap, we enhanced the computational power of a computer-aided system by proposing a fine-tuned Block-Wise Visual Geometry Group19 (BW-VGG19) architecture. In this method, a pre-trained VGG19 is fine-tuned with CNN architecture in the block-wise mechanism… More >

Gürcan Çetin^*

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 4519-4539, 2022, DOI:10.32604/cmc.2022.031734

Abstract Recently, machine learning algorithms have been used in the detection and classification of network attacks. The performance of the algorithms has been evaluated by using benchmark network intrusion datasets such as DARPA98, KDD’99, NSL-KDD, UNSW-NB15, and Caida DDoS. However, these datasets have two major challenges: imbalanced data and high-dimensional data. Obtaining high accuracy for all attack types in the dataset allows for high accuracy in imbalanced datasets. On the other hand, having a large number of features increases the runtime load on the algorithms. A novel model is proposed in this paper to overcome these two concerns. The number of… More >

Hanan M. Alghamdi¹, Saadia H.A. Hamza², Aisha M. Mashraqi³, Sayed Abdel-Khalek^4,5,*

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5985-5999, 2022, DOI:10.32604/cmc.2022.031732

Abstract World Wide Web enables its users to connect among themselves through social networks, forums, review sites, and blogs and these interactions produce huge volumes of data in various forms such as emotions, sentiments, views, etc. Sentiment Analysis (SA) is a text organization approach that is applied to categorize the sentiments under distinct classes such as positive, negative, and neutral. However, Sentiment Analysis is challenging to perform due to inadequate volume of labeled data in the domain of Natural Language Processing (NLP). Social networks produce interconnected and huge data which brings complexity in terms of expanding SA to an extensive array… More >

Salem Alkhalaf^*, Fahad Alturise

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 6393-6405, 2022, DOI:10.32604/cmc.2022.031698

Abstract Software-defined network (SDN) is a new form of network architecture that has programmability, ease of use, centralized control, and protocol independence. It has received high attention since its birth. With SDN network architecture, network management becomes more efficient, and programmable interfaces make network operations more flexible and can meet the different needs of various users. The mainstream communication protocol of SDN is OpenFlow, which contains a Match Field in the flow table structure of the protocol, which matches the content of the packet header of the data received by the switch, and completes the corresponding actions according to the matching… More >

Yang Wu¹, Lei Guo¹, Xiaodong Dai¹, Bin Zhang¹, Dong-Won Park², Ming Ma^1,*

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5911-5924, 2022, DOI:10.32604/cmc.2022.031664

Abstract Action recognition has become a current research hotspot in computer vision. Compared to other deep learning methods, Two-stream convolutional network structure achieves better performance in action recognition, which divides the network into spatial and temporal streams, using video frame images as well as dense optical streams in the network, respectively, to obtain the category labels. However, the two-stream network has some drawbacks, i.e., using dense optical flow as the input of the temporal stream, which is computationally expensive and extremely time-consuming for the current extraction algorithm and cannot meet the requirements of real-time tasks. In this paper, instead of the… More >

Anwer Mustafa Hilal^1,2,*, Aisha Hassan Abdalla Hashim¹, Sami Dhahbi³, Dalia H. Elkamchouchi⁴, Jaber S. Alzahrani⁵, Mrim M. Alnfiai⁶, Amira Sayed A. Aziz⁷, Abdelwahed Motwakel²

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 6547-6561, 2022, DOI:10.32604/cmc.2022.031660

Abstract Wireless Sensor Networks (WSN) interlink numerous Sensor Nodes (SN) to support Internet of Things (loT) services. But the data gathered from SNs can be divulged, tempered, and forged. Conventional WSN data processes manage the data in a centralized format at terminal gadgets. These devices are prone to attacks and the security of systems can get compromised. Blockchain is a distributed and decentralized technique that has the ability to handle security issues in WSN. The security issues include transactions that may be copied and spread across numerous nodes in a peer-peer network system. This breaches the mutual trust and allows data… More >