Mohamed Ibrahim Waly¹, Mohamed Yacin Sikkandar¹, Mohamed Abdelkader Aboamer¹, Seifedine Kadry², Orawit Thinnukool^3,*

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3295-3309, 2022, DOI:10.32604/cmc.2022.020713

Abstract Biomedical imaging is an effective way of examining the internal organ of the human body and its diseases. An important kind of biomedical image is Pap smear image that is widely employed for cervical cancer diagnosis. Cervical cancer is a vital reason for increased women’s mortality rate. Proper screening of pap smear images is essential to assist the earlier identification and diagnostic process of cervical cancer. Computer-aided systems for cancerous cell detection need to be developed using deep learning (DL) approaches. This study introduces an intelligent deep convolutional neural network for cervical cancer detection and classification (IDCNN-CDC) model using biomedical… More >

Inam Ullah Khan¹, Muhammad Abul Hassan², Muhammad Fayaz³, Jeonghwan Gwak^4,5,6,7,*, Muhammad Adnan Aziz¹

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3653-3666, 2022, DOI:10.32604/cmc.2022.020697

Abstract Most interesting area is the growing demand of flying-IoT mergers with smart cities. However, aerial vehicles, especially unmanned aerial vehicles (UAVs), have limited capabilities for maintaining node energy efficiency. In order to communicate effectively, IoT is a key element for smart cities. While improving network performance, routing protocols can be deployed in flying-IoT to improve latency, packet drop rate, packet delivery, power utilization, and average-end-to-end delay. Furthermore, in literature, proposed techniques are very much complex which cannot be easily implemented in real-world applications. This issue leads to the development of lightweight energy-efficient routing in flying-IoT networks. This paper addresses the… More >

Niamat Hussain¹, Anees Abbas¹, Sang-Myeong Park¹, Seong Gyoon Park², Nam Kim^1,*

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3321-3331, 2022, DOI:10.32604/cmc.2022.020688

Abstract We designed and constructed a novel, compact tri-band monopole antenna for intelligent devices. Multiband behavior was achieved by placing inverted-L shaped stubs of various lengths in a triangular monopole antenna fed by a coplanar waveguide. The resonance frequency of each band can be controlled by varying the length of the corresponding stub. Three bands, at 2.4 (2.37–2.51), 3.5 (3.34–3.71), and 5.5 (4.6–6.4) GHz, were easily obtained using three stubs of different lengths. For miniaturization, a portion of the longest stub (at 2.4 GHz) was printed on the opposite side of the substrate, and connected to the main stub via a… More >

Aref Hassan Kurd Ali^1,*, Halikul Lenando¹, Slim Chaoui^2,3, Mohamad Alrfaay^1,4, Medhat A. Tawfeek^5,6

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 4147-4167, 2022, DOI:10.32604/cmc.2022.020659

Abstract Recently, Opportunistic Networks (OppNets) are considered to be one of the most attractive developments of Mobile Ad Hoc Networks that have arisen thanks to the development of intelligent devices. OppNets are characterized by a rough and dynamic topology as well as unpredictable contacts and contact times. Data is forwarded and stored in intermediate nodes until the next opportunity occurs. Therefore, achieving a high delivery ratio in OppNets is a challenging issue. It is imperative that any routing protocol use network resources, as far as they are available, in order to achieve higher network performance. In this article, we introduce the… More >

Disha Deotale¹, Madhushi Verma², P. Suresh³, Sunil Kumar Jangir⁴, Manjit Kaur², Sahar Ahmed Idris⁵, Hammam Alshazly^6,*

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3919-3938, 2022, DOI:10.32604/cmc.2022.020655

Abstract Nowadays, the most challenging and important problem of computer vision is to detect human activities and recognize the same with temporal information from video data. The video datasets are generated using cameras available in various devices that can be in a static or dynamic position and are referred to as untrimmed videos. Smarter monitoring is a historical necessity in which commonly occurring, regular, and out-of-the-ordinary activities can be automatically identified using intelligence systems and computer vision technology. In a long video, human activity may be present anywhere in the video. There can be a single or multiple human activities present… More >

Seonjae Kim, Dongsan Jun^*

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3267-3279, 2022, DOI:10.32604/cmc.2022.020651

Abstract Medical image compression is one of the essential technologies to facilitate real-time medical data transmission in remote healthcare applications. In general, image compression can introduce undesired coding artifacts, such as blocking artifacts and ringing effects. In this paper, we proposed a Multi-Scale Feature Attention Network (MSFAN) with two essential parts, which are multi-scale feature extraction layers and feature attention layers to efficiently remove coding artifacts of compressed medical images. Multi-scale feature extraction layers have four Feature Extraction (FE) blocks. Each FE block consists of five convolution layers and one CA block for weighted skip connection. In order to optimize the… More >

Syed Shabih Ul Hasan¹, Anwar Ghani¹, Ikram Ud Din², Ahmad Almogren^3,*, Ayman Altameem⁴

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3701-3716, 2022, DOI:10.32604/cmc.2022.020624

Abstract User authentication is one of the critical concerns of information security. Users tend to use strong textual passwords, but remembering complex passwords is hard as they often write it on a piece of paper or save it in their mobile phones. Textual passwords are slightly unprotected and are easily attackable. The attacks include dictionary, shoulder surfing, and brute force. Graphical passwords overcome the shortcomings of textual passwords and are designed to aid memorability and ease of use. This paper proposes a Process-based Pattern Authentication (PPA) system for Internet of Things (IoT) devices that does not require a server to maintain… More >

Kusum Yadav¹, Ali Alharbi¹, Anurag Jain^2,*, Rabie A. Ramadan¹

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3637-3652, 2022, DOI:10.32604/cmc.2022.020614

Abstract Internet of things (IoT) field has emerged due to the rapid growth of artificial intelligence and communication technologies. The use of IoT technology in modern healthcare environments is convenient for doctors and patients as it can be used in real-time monitoring of patients, proper administration of patient information, and healthcare management. However, the usage of IoT in the healthcare domain will become a nightmare if patient information is not securely maintained while transferring over an insecure network or storing at the administrator end. In this manuscript, the authors have developed a secure IoT healthcare monitoring system using the Blockchain-based XOR… More >

Wen-Tsai Sung¹, Sung-Jung Hsiao^2,*

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3529-3548, 2022, DOI:10.32604/cmc.2022.020613

Abstract This research uses the improved Quantum Particle Swarm Optimization (QPSO) algorithm to build an Internet of Things (IoT) life comfort monitoring system based on wireless sensing networks. The purpose is to improve the quality of intelligent life. The functions of the system include automatic basketball court lighting system, monitoring of infants’ sleeping posture and accidental falls of the elderly, human thermal comfort measurement and other related life comfort services, etc. On the hardware system of the IoT, this research is based on the latest version of ZigBee 3.0, which uses optical sensors, 3-axis accelerometers, and temperature/humidity sensors in the IoT… More >

Jae-Hyun Ro¹, Jong-Gyu Ha², Woon-Sang Lee², Young-Hwan You³, Hyoung-Kyu Song^2,*

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3625-3636, 2022, DOI:10.32604/cmc.2022.020596

Abstract This paper proposes the multiple-input multiple-output (MIMO) detection scheme by using the deep neural network (DNN) based ensemble machine learning for higher error performance in wireless communication systems. For the MIMO detection based on the ensemble machine learning, all learning models for the DNN are generated in offline and the detection is performed in online by using already learned models. In the offline learning, the received signals and channel coefficients are set to input data, and the labels which correspond to transmit symbols are set to output data. In the online learning, the perfectly learned models are used for signal… More >