Naigong Yu^*, Hejie Yu

CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.2, pp. 1147-1169, 2022, DOI:10.32604/cmes.2022.019430 - 14 March 2022

Abstract The entorhinal-hippocampus structure in the mammalian brain is the core area for realizing spatial cognition. However, the visual perception and loop detection methods in the current biomimetic robot navigation model still rely on traditional visual SLAM schemes and lack the process of exploring and applying biological visual methods. Based on this, we propose a map construction method that mimics the entorhinal-hippocampal cognitive mechanism of the rat brain according to the response of entorhinal cortex neurons to eye saccades in recent related studies. That is, when mammals are free to watch the scene, the entorhinal cortex… More >

Reza Shokri-Gharelo¹, Ali Bandehagh^1,*, Mohammad Anwar Hossain^2,*

Phyton-International Journal of Experimental Botany, Vol.91, No.7, pp. 1403-1417, 2022, DOI:10.32604/phyton.2022.020431 - 14 March 2022

Abstract Drought stress is one of the most important abiotic stresses that plants face frequently in nature. Under drought conditions, many morphological, physiological, and molecular aspects of plants are changed and as a result plants experience a remarkable reduction in growth, yield, and reproduction. To expand our understanding of the molecular basis of the plant response to drought stress, the proteomic profile and protein-protein network of canola (Brassica napus L.) were studied. The focus was to show molecular mechanisms related to canola susceptibility to drought stress. The experiment used a completely randomized design, implemented in a hydroponic… More >

Adel D. Rajab^*

CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 2077-2092, 2022, DOI:10.32604/cmc.2022.025736 - 24 February 2022

Abstract In the Internet of Things (IoT)-based smart city applications, employing the Data Collectors (DC) as the data brokers between the nodes and Base Station (BS) can be a promising solution to enhance the energy efficiency of energy-constrained IoT sensor nodes. There are several schemes that utilize mobile DCs to collect the data packets from sensor nodes. However, moving DCs along the hundreds of thousands of sensors sparsely distributed across a smart city is considered a design challenge in such schemes. Another concern lies in how these mobile DCs are being powered. Therefore, to overcome these… More >

Muhammad Irfan^1,*, Nasir Ayub², Faisal Althobiani³, Zain Ali⁴, Muhammad Idrees⁵, Saeed Ullah², Saifur Rahman¹, Abdullah Saeed Alwadie¹, Saleh Mohammed Ghonaim³, Hesham Abdushkour³, Fahad Salem Alkahtani¹, Samar Alqhtani⁶, Piotr Gas⁷

CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 2141-2158, 2022, DOI:10.32604/cmc.2022.025466 - 24 February 2022

Abstract One of the major concerns for the utilities in the Smart Grid (SG) is electricity theft. With the implementation of smart meters, the frequency of energy usage and data collection from smart homes has increased, which makes it possible for advanced data analysis that was not previously possible. For this purpose, we have taken historical data of energy thieves and normal users. To avoid imbalance observation, biased estimates, we applied the interpolation method. Furthermore, the data unbalancing issue is resolved in this paper by Nearmiss undersampling technique and makes the data suitable for further processing.… More >

Mouazma Batool¹, Yazeed Yasin Ghadi², Suliman A. Alsuhibany³, Tamara al Shloul⁴, Ahmad Jalal¹, Jeongmin Park^5,*

CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1747-1764, 2022, DOI:10.32604/cmc.2022.025112 - 24 February 2022

Abstract Nowadays, activities of daily living (ADL) recognition system has been considered an important field of computer vision. Wearable and optical sensors are widely used to assess the daily living activities in healthy people and people with certain disorders. Although conventional ADL utilizes RGB optical sensors but an RGB-D camera with features of identifying depth (distance information) and visual cues has greatly enhanced the performance of activity recognition. In this paper, an RGB-D-based ADL recognition system has been presented. Initially, human silhouette has been extracted from the noisy background of RGB and depth images to track More >

Mahmoud Ragab^1,2,3,*, Ali Altalbe¹, Abdullah Saad Al-Malaise ALGhamdi⁴, S. Abdel-khalek^5,6, Rashid A. Saeed⁷

CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 365-380, 2022, DOI:10.32604/cmc.2022.024932 - 24 February 2022

Abstract The smart city comprises various interlinked elements which communicate data and offers urban life to citizen. Unmanned Aerial Vehicles (UAV) or drones were commonly employed in different application areas like agriculture, logistics, and surveillance. For improving the drone flying safety and quality of services, a significant solution is for designing the Internet of Drones (IoD) where the drones are utilized to gather data and people communicate to the drones of a specific flying region using the mobile devices is for constructing the Internet-of-Drones, where the drones were utilized for collecting the data, and communicate with More >

Changsung Lee^1,3, Junsung Kim^2,3, Jaewook Jung³, Jungsuk Baik³, Jong-Moon Chung^3,*

CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 727-738, 2022, DOI:10.32604/cmc.2022.024824 - 24 February 2022

Abstract Packet duplication (PD) with dual connectivity (DC) was newly introduced in the 5G New Radio (NR) specifications to meet the stringent ultra reliable low latency communication (URLLC) requirements. PD technology uses duplicated packets in the packet data convergence protocol (PDCP) layer that are transmitted via two different access nodes (ANs) to the user equipment (UE) in order to enhance the reliability performance. However, PD can result in unnecessary retransmissions in the lower layers since the hybrid automatic retransmission request (HARQ) operation is unaware of the transmission success achieved through the alternate DC link to the… More >

Elias Hossain¹, Mohammed Alshehri², Sultan Almakdi^2,*, Hanan Halawani², Md. Mizanur Rahman³, Wahidur Rahman⁴, Sabila Al Jannat⁵, Nadim Kaysar⁶, Shishir Mia⁴

CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1713-1746, 2022, DOI:10.32604/cmc.2022.024822 - 24 February 2022

Abstract Diabetes Mellitus is one of the most severe diseases, and many studies have been conducted to anticipate diabetes. This research aimed to develop an intelligent mobile application based on machine learning to determine the diabetic, pre-diabetic, or non-diabetic without the assistance of any physician or medical tests. This study's methodology was classified into two the Diabetes Prediction Approach and the Proposed System Architecture Design. The Diabetes Prediction Approach uses a novel approach, Light Gradient Boosting Machine (LightGBM), to ensure a faster diagnosis. The Proposed System Architecture Design has been combined into seven modules; the Answering… More >

Kazem Nouri^1,*, Milad Fahimi¹, Leila Torkzadeh¹, Dumitru Baleanu^2,3

CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1495-1514, 2022, DOI:10.32604/cmc.2022.024406 - 24 February 2022

Abstract The novel Coronavirus COVID-19 emerged in Wuhan, China in December 2019. COVID-19 has rapidly spread among human populations and other mammals. The outbreak of COVID-19 has become a global challenge. Mathematical models of epidemiological systems enable studying and predicting the potential spread of disease. Modeling and predicting the evolution of COVID-19 epidemics in near real-time is a scientific challenge, this requires a deep understanding of the dynamics of pandemics and the possibility that the diffusion process can be completely random. In this paper, we develop and analyze a model to simulate the Coronavirus transmission dynamics… More >

Tamer AbuKhalil¹, Bassam A. Y. Alqaralleh^2,*, Ahmad H. Al-Omari³

CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 57-71, 2022, DOI:10.32604/cmc.2022.024367 - 24 February 2022

Abstract Prevention of cervical cancer becomes essential and is carried out by the use of Pap smear images. Pap smear test analysis is laborious and tiresome work performed visually using a cytopathologist. Therefore, automated cervical cancer diagnosis using automated methods are necessary. This paper designs an optimal deep learning based Inception model for cervical cancer diagnosis (ODLIM-CCD) using pap smear images. The proposed ODLIM-CCD technique incorporates median filtering (MF) based pre-processing to discard the noise and Otsu model based segmentation process. Besides, deep convolutional neural network (DCNN) based Inception with Residual Network (ResNet) v2 model is More >