R. Gopi¹, Mahantesh Mathapati², B. Prasad³, Sultan Ahmad⁴, Fahd N. Al-Wesabi⁵, Manal Abdullah Alohali^6,*, Anwer Mustafa Hilal⁷

CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 141-156, 2022, DOI:10.32604/cmc.2022.023306

Abstract Vehicular Ad hoc Network (VANET) has become an integral part of Intelligent Transportation Systems (ITS) in today's life. VANET is a network that can be heavily scaled up with a number of vehicles and road side units that keep fluctuating in real world. VANET is susceptible to security issues, particularly DoS attacks, owing to maximum unpredictability in location. So, effective identification and the classification of attacks have become the major requirements for secure data transmission in VANET. At the same time, congestion control is also one of the key research problems in VANET which aims at minimizing the time expended… More >

Wenzheng Yu¹, Xin Yao¹, Li Shao², Jing Liu¹, Yanbo Shen^3,4,*, Hanxiaoya Zhang⁵

CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 695-711, 2022, DOI:10.32604/cmc.2022.023191

Abstract In this paper, RS, GIS and GPS technologies are used to interpret the remote sensing images of the north shore of Qinghai Lake from 1987 to 2014 according to the inversion results of vegetation coverage (FVC), albedo, land surface temperature (LST), soil moisture (WET) and other major parameters after image preprocessing, such as radiometric correction, geometric correction and atmospheric correction. On this basis, the decision tree classification method based on landsat8 remote sensing image is used to classify the desertification land in this area, and the development and change of desertification in this period are analyzed. The results show that… More >

Kriti¹, Mohd Anul Haq², Urvashi Garg¹, Mohd Abdul Rahim Khan^2,*, V. Rajinikanth³

CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 939-957, 2022, DOI:10.32604/cmc.2022.023169

Abstract A crucial task in hyperspectral image (HSI) taxonomy is exploring effective methodologies to effusively practice the 3-D and spectral data delivered by the statistics cube. For classification of images, 3-D data is adjudged in the phases of pre-cataloging, an assortment of a sample, classifiers, post-cataloging, and accurateness estimation. Lastly, a viewpoint on imminent examination directions for proceeding 3-D and spectral approaches is untaken. In topical years, sparse representation is acknowledged as a dominant classification tool to effectually labels deviating difficulties and extensively exploited in several imagery dispensation errands. Encouraged by those efficacious solicitations, sparse representation (SR) has likewise been presented… More >

Huma Hasan Rizvi^1,2, Sadiq Ali Khan¹, Rabia Noor Enam², Kashif Nisar^3,*, Muhammad Reazul Haque⁴

CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1611-1626, 2022, DOI:10.32604/cmc.2022.023081

Abstract In an Underwater Wireless Sensor Network (UWSN), extreme energy loss is carried out by the early expiration of sensor nodes and causes a reduction in efficiency in the submerged acoustic sensor system. Systems based on clustering strategies, instead of each node sending information by itself, utilize cluster heads to collect information inside the clusters for forwarding collective information to sink. This can effectively minimize the total energy loss during transmission. The environment of UWSN is 3D architecture-based and follows a complex hierarchical clustering strategy involving its most effecting unique parameters such as propagation delay and limited transmission bandwidth. Round base… More >

Maedeh Mohammadi Azni¹, Mohammad Ali Sadrnia¹, Shahab S. Band^2,*, Zulkefli Bin Mansor³

CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 215-226, 2022, DOI:10.32604/cmc.2022.023030

Abstract Automobile power windows are mechanisms that can be opened and shut with the press of a button. Although these windows can comfort the effort of occupancy to move the window, failure to recognize the person's body part at the right time will result in damage and in some cases, loss of that part. An anti-pinch mechanism is an excellent choice to solve this problem, which detects the obstacle in the glass path immediately and moves it down. In this paper, an optimal solution is presented for fault detection of the anti-pinch window system. The anti-pinch makes it possible to detect… More >

Kiran Jot Singh¹, Divneet Singh Kapoor^1,*, Khushal Thakur¹, Anshul Sharma¹, Xiao-Zhi Gao²

CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 197-213, 2022, DOI:10.32604/cmc.2022.022989

Abstract The near future has been envisioned as a collaboration of humans with mobile robots to help in the day-to-day tasks. In this paper, we present a viable approach for a real-time computer vision based object detection and recognition for efficient indoor navigation of a mobile robot. The mobile robotic systems are utilized mainly for home assistance, emergency services and surveillance, in which critical action needs to be taken within a fraction of second or real-time. The object detection and recognition is enhanced with utilization of the proposed algorithm based on the modification of You Look Only Once (YOLO) algorithm, with… More >

Norah Saleh Alghamdi¹, Sami Bourouis^2,*, Nizar Bouguila³

CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1139-1156, 2022, DOI:10.32604/cmc.2022.022959

Abstract Interest in automated data classification and identification systems has increased over the past years in conjunction with the high demand for artificial intelligence and security applications. In particular, recognizing human activities with accurate results have become a topic of high interest. Although the current tools have reached remarkable successes, it is still a challenging problem due to various uncontrolled environments and conditions. In this paper two statistical frameworks based on nonparametric hierarchical Bayesian models and Gamma distribution are proposed to solve some real-world applications. In particular, two nonparametric hierarchical Bayesian models based on Dirichlet process and Pitman-Yor process are developed.… More >

Faheem Khan¹, Muhammad Zahid², Hüseyin Gürüler³, Ilhan Tarimer³, Taegkeun Whangbo^1,*

CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 663-678, 2022, DOI:10.32604/cmc.2022.022934

Abstract The Internet of thing (IoT) is a growing concept for smart cities, and it is compulsory to communicate data between different networks and devices. In the IoT, communication should be rapid with less delay and overhead. For this purpose, flooding is used for reliable data communication in a smart cities concept but at the cost of higher overhead, energy consumption and packet drop etc. This paper aims to increase the efficiency in term of overhead and reliability in term of delay by using multicasting and unicasting instead of flooding during packet forwarding in a smart city using the IoT concept.… More >

Rohit Raja¹, Chetan Swarup², Abhishek Kumar^3,*, Kamred Udham Singh⁴, Teekam Singh⁵, Dinesh Gupta⁶, Neeraj Varshney⁷, Swati Jain⁸

CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 2015-2031, 2022, DOI:10.32604/cmc.2022.022904

Abstract As far as the present state is concerned in detecting the behavioral pattern of humans (subject) using morphological image processing, a considerable portion of the study has been conducted utilizing frontal vision data of human faces. The present research work had used a side vision of human-face data to develop a theoretical framework via a hybrid analytical model approach. In this example, hybridization includes an artificial neural network (ANN) with a genetic algorithm (GA). We researched the geometrical properties extracted from side-vision human-face data. An additional study was conducted to determine the ideal number of geometrical characteristics to pick while… More >

Daniyal M. Alghazzawi¹, Osama Bassam J. Rabie¹, Surbhi Bhatia², Syed Hamid Hasan^1,*

CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1173-1193, 2022, DOI:10.32604/cmc.2022.022748

Abstract The Deep Neural Networks (DNN) training process is widely affected by backdoor attacks. The backdoor attack is excellent at concealing its identity in the DNN by performing well on regular samples and displaying malicious behavior with data poisoning triggers. The state-of-art backdoor attacks mainly follow a certain assumption that the trigger is sample-agnostic and different poisoned samples use the same trigger. To overcome this problem, in this work we are creating a backdoor attack to check their strength to withstand complex defense strategies, and in order to achieve this objective, we are developing an improved Convolutional Neural Network (ICNN) model… More >