R. Bhaskaran¹, P. S. Sujith Kumar², G. Shanthi³, L. Raja⁴, Gyanendra Prasad Joshi⁵, Woong Cho^6,*

Computer Systems Science and Engineering, Vol.44, No.1, pp. 1-17, 2023, DOI:10.32604/csse.2023.024973

Abstract In recent times, real time wireless networks have found their applicability in several practical applications such as smart city, healthcare, surveillance, environmental monitoring, etc. At the same time, proper localization of nodes in real time wireless networks helps to improve the overall functioning of networks. This study presents an Improved Metaheuristics based Energy Efficient Clustering with Node Localization (IM-EECNL) approach for real-time wireless networks. The proposed IM-EECNL technique involves two major processes namely node localization and clustering. Firstly, Chaotic Water Strider Algorithm based Node Localization (CWSANL) technique to determine the unknown position of the nodes. Secondly, an Oppositional Archimedes Optimization… More >

Joddat Fatima^1,*, Amina Jameel², Muhammad Usman Akram³, Adeel Muzaffar Syed¹, Malaika Mushtaq³

Intelligent Automation & Soft Computing, Vol.34, No.3, pp. 1489-1504, 2022, DOI:10.32604/iasc.2022.025935

Abstract The long twisted fragile tube, termed as spinal cord, can be named as the second vital organ of Central Nervous System (CNS), after brain. In human anatomy, all crucial life activities are controlled by CNS. The spinal cord does not only control the flow of information from the brain to rest of the body, but also takes charge of our reflexes control and the mobility of body. It keeps the body upright and acts as the main support for the flesh and bones. Spine deformity can occur by birth, due to aging, injury or spine surgery. In this research article,… More >

Abdulaziz Alhumam^*

CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1463-1482, 2022, DOI:10.32604/cmc.2022.029473

Abstract The most resource-intensive and laborious part of debugging is finding the exact location of the fault from the more significant number of code snippets. Plenty of machine intelligence models has offered the effective localization of defects. Some models can precisely locate the faulty with more than 95% accuracy, resulting in demand for trustworthy models in fault localization. Confidence and trustworthiness within machine intelligence-based software models can only be achieved via explainable artificial intelligence in Fault Localization (XFL). The current study presents a model for generating counterfactual interpretations for the fault localization model's decisions. Neural system approximations and disseminated presentation of… More >

Hanan Abdullah Mengash¹, Radwa Marzouk¹, Siwar Ben Haj Hassine², Anwer Mustafa Hilal^3,*, Ishfaq Yaseen³, Abdelwahed Motwakel³

CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 327-342, 2022, DOI:10.32604/cmc.2022.026464

Abstract Artificial intelligence (AI) techniques have received significant attention among research communities in the field of networking, image processing, natural language processing, robotics, etc. At the same time, a major problem in wireless sensor networks (WSN) is node localization, which aims to identify the exact position of the sensor nodes (SN) using the known position of several anchor nodes. WSN comprises a massive number of SNs and records the position of the nodes, which becomes a tedious process. Besides, the SNs might be subjected to node mobility and the position alters with time. So, a precise node localization (NL) manner is… More >

Imran Ashraf¹, Muhammad Usman Ali², Soojung Hur¹, Gunzung Kim¹, Yongwan Park^1,*

CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1747-1768, 2022, DOI:10.32604/cmc.2022.020610

Abstract Indoor positioning and localization have emerged as a potential research area during the last few years owing to the wide proliferation of smartphones and the inception of location-attached services for the consumer industry. Due to the importance of precise location information, several positioning technologies are adopted such as Wi-Fi, ultrawideband, infrared, radio frequency identification, Bluetooth beacons, pedestrian dead reckoning, and magnetic field, etc. Although Wi-Fi and magnetic field-based positioning are more attractive concerning the deployment of Wi-Fi access points and ubiquity of magnetic field data, the latter is preferred as it does not require any additional infrastructure as other approaches… More >

DANILA BOBKOV^1,2,3,*, ANASTASIA POLYANSKAYA¹, ANASTASIA MUSORINA¹, GALINA POLJANSKAYA¹

BIOCELL, Vol.46, No.9, pp. 2053-2058, 2022, DOI:10.32604/biocell.2022.019469

Abstract All non-immortalized mesenchymal stem cells have a limited proliferative potential, that is, replicative senescence (RS) is an integral characteristic of the life of all mesenchymal stem cells (MSCs). It is known that one of the important signs of RS is a decrease of cell motility, and that violations of migration processes contribute to the deterioration of tissue regeneration. Therefore, the characterization of the properties of the cell line associated with RS is a prerequisite for the effective use of MSCs in restorative medicine. One of the key proteins regulating cell motility is the small GTPase RhoA. The main purpose of… More >

Yongshuai Sun^1,*, Guihe Wang², Yixuan li²

Journal of Renewable Materials, Vol.10, No.8, pp. 2287-2302, 2022, DOI:10.32604/jrm.2022.019660

Abstract To study the relationship between acoustic emission characteristic parameters of self-compacting concrete(SCC) and its destruction evolution, under uniaxial compression, acoustic emission(AE) tests are performed on C30 selfcompacting concrete test blocks that are preserved for 7 days and 28 days, the corresponding relationship among energy, amplitude, ring count and different failure stages of the specimens are analyzed by AE experiment, and the spatial distribution of AE in each stage is described by introducing location map. The test shows that there are two rules for the failure of SCC specimens cured for 7 days and 28 days: (1) The first failure law… More >

Worakamol Wisetsri¹, Shamimul Qamar², Gaurav Verma^3,*, Deval Verma⁴, Varun Kumar Kakar⁵, Thanyanant Chansongpol⁶, Chanyanan Somtawinpongsai⁶, Chai Ching Tan⁷

Intelligent Automation & Soft Computing, Vol.33, No.3, pp. 1473-1483, 2022, DOI:10.32604/iasc.2022.024610

Abstract Industry 4.0 is considered as the fourth revolution in industrial sector that represents the digitization of production process in a smarter way. Industry 4.0 refers to the intelligent networking of machines, their processes, and infrastructure, as well as the use of information and computer technology to transform industry. The technologies like industrial internet of things (IIoT), big data analytics, cloud computing, augmented reality and cyber security are the main pillars of industry 4.0. Industry 4.0, in particular, is strongly reliant on the IIoT that refers to the application of internet of things (IoT) in industrial sector like smart grids (SG).… More >

Farman Ali¹, Sadia Khan², Arbab Waseem Abbas², Babar Shah³, Tariq Hussain², Dongho Song^4,*, Shaker EI-Sappagh^5,6, Jaiteg Singh⁷

CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 73-92, 2022, DOI:10.32604/cmc.2022.024103

Abstract Medical Image Analysis (MIA) is one of the active research areas in computer vision, where brain tumor detection is the most investigated domain among researchers due to its deadly nature. Brain tumor detection in magnetic resonance imaging (MRI) assists radiologists for better analysis about the exact size and location of the tumor. However, the existing systems may not efficiently classify the human brain tumors with significantly higher accuracies. In addition, smart and easily implementable approaches are unavailable in 2D and 3D medical images, which is the main problem in detecting the tumor. In this paper, we investigate various deep learning… 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 >