Ramesh Ramamoorthy¹, Himanshu Sharma², A. Akilandeswari³, Nidhi Gour², Arun Kumar^4,*, Mehedi Masud⁵

Computer Systems Science and Engineering, Vol.43, No.3, pp. 1207-1217, 2022, DOI:10.32604/csse.2022.024749

Abstract Spectrum sensing is one of the major concerns in reaching an efficient Quality of service (QOS) in the advanced mobile communication system. The advanced engineering sciences such as 5G, device 2 device communications (D2D), Internet of things (IoT), MIMO require a large spectrum for better service. Orthogonal frequency division multiplexing (OFDM) is not a choice in advanced radio due to the Cyclic Prefix (CP), wastage of the spectrum, and so on. Hence, it is important to explore the spectral efficient advanced waveform techniques and combine a cognitive radio (CR) with the 5G waveform to sense the idle spectrum, which overcomes… More >

S. Kalpana^1,*, C. Annadurai²

Computer Systems Science and Engineering, Vol.43, No.3, pp. 1027-1040, 2022, DOI:10.32604/csse.2022.024685

Abstract In Internet of Things (IoT), large amount of data are processed and communicated through different network technologies. Wireless Body Area Networks (WBAN) plays pivotal role in the health care domain with an integration of IoT and Artificial Intelligence (AI). The amalgamation of above mentioned tools has taken the new peak in terms of diagnosis and treatment process especially in the pandemic period. But the real challenges such as low latency, energy consumption high throughput still remains in the dark side of the research. This paper proposes a novel optimized cognitive learning based BAN model based on Fog-IoT technology as a… More >

S. Velmurugan^1,*, P. Ezhumalai², E. A. Mary Anita³

Intelligent Automation & Soft Computing, Vol.34, No.2, pp. 1093-1108, 2022, DOI:10.32604/iasc.2022.026308

Abstract Cognitive Radio Networks (CRN) have recently emerged as an important solution for addressing spectrum constraint and meeting the stringent criteria of future wireless communication. Collaborative spectrum sensing is incorporated in CRNs for proper channel selection since spectrum sensing is a critical capability of CRNs. According to this viewpoint, this study introduces a new Adaptive Neuro Fuzzy logic with Improved Genetic Algorithm based Channel Selection (ANFIGA-CS) technique for collaborative spectrum sensing in CRN. The suggested method’s purpose is to find the best transmission channel. To reduce spectrum sensing error, the suggested ANFIGA-CS model employs a clustering technique. The Adaptive Neuro Fuzzy… More >

Raed Alhamad^*

Computer Systems Science and Engineering, Vol.43, No.2, pp. 751-765, 2022, DOI:10.32604/csse.2022.021932

Abstract In this article, we optimize harvesting and sensing duration for Cognitive Radio Networks (CRN) using Intelligent Reflecting Surfaces (IRS). The secondary source harvests energy using the received signal from node A. Then, it performs spectrum sensing to detect Primary Source P_S activity. When P_S activity is not detected, The Secondary Source S_S transmits data to Secondary Destination S_D where all reflected signals on IRS are in phase at S_D. We show that IRS offers 14, 20, 26, 32, 38, 44, 50 dB enhancement in throughput using M = 8, 16, 32, 64, 128, 256, 512 reflectors with respect to CRN without IRS. We… More >

V. P. Ajay^1,*, M. Nesasudha²

Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 193-204, 2022, DOI:10.32604/iasc.2022.024839

Abstract Cognitive radio network (CRN) is a growing technology targeting more resourcefully exploiting the available spectrum for opportunistic network usage. By the concept of cognitive radio, the wastage of available spectrum reduced about 30% worldwide. The key operation of CRN is spectrum sensing. The sensing results about the spectrum are directly proportional to the performance of the network. In CRN, the final result about the available spectrum is decided by combing the local sensing results. The presence or participation of attackers in the network leads to false decisions and the performance of the network will be degraded. In this work, an… More >

Romany F. Mansour^1,*, Maha M. Althobaiti²

CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3945-3959, 2022, DOI:10.32604/cmc.2022.026515

Abstract Recently, the Internet of Medical Things (IoMT) has become a research hotspot due to its various applicability in medical field. However, the data analysis and management in IoMT remain challenging owing to the existence of a massive number of devices linked to the server environment, generating a massive quantity of healthcare data. In such cases, cognitive computing can be employed that uses many intelligent technologies–machine learning (ML), deep learning (DL), artificial intelligence (AI), natural language processing (NLP) and others–to comprehend data expansively. Furthermore, breast cancer (BC) has been found to be a major cause of mortality among ladies globally. Earlier… More >

Vineetha Mathai^*, P. Indumathi

Intelligent Automation & Soft Computing, Vol.33, No.3, pp. 1729-1746, 2022, DOI:10.32604/iasc.2022.024234

Abstract An identification of unfilled primary user spectrum using a novel method is presented in this paper. Cooperation among users with the utilization of machine learning methods is analyzed. Learning methods are applied to construct the classifier, which selects the suitable fusion algorithm for the considered environment so that the out of band sensing is performed efficiently. Sensing performance is looked into with the existence of fading and it is observed that sensing performance degrades with fading which coincides with earlier findings. From the simulation, it can be inferred that Weibull fading outperforms all the other fading models considered. To accomplish… More >

Araceli Cano-Estrada^1,*, Araceli Jimenez-Mendoza², Denny Contreras-Guerrero¹, Mario Hernandes-Alejandro³, Andres Salas-Casas⁴

International Journal of Mental Health Promotion, Vol.24, No.3, pp. 375-383, 2022, DOI:10.32604/ijmhp.2022.018857

Abstract Cognitive function of older adults is influenced by several factors such as age, sex, education, and physical activity so that it can impact the decrease in progressive cognitive function. It is necessary to implement cognitive training in old people’s care to prevent or delay the onset of age-related cognitive decline. Brain gym is a series of simple motion exercises and is an alternative therapy that stimulates the brain. This study aims to evaluate the effect of brain gym as a cognitive training intervention on global cognitive functioning of institutionalized older population. The study is a non-randomized quasi-experimental one using pre-and… More >

Naigong Yu^*, Hejie Yu

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

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 neurons will encode the saccade… More >

Fadhil Mukhlif^1,*, Norafida Ithnin¹, Omar B. Abdulghafoor², Faiz Alotaibi³, Nourah Saad Alotaibi⁴

CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1561-1578, 2022, DOI:10.32604/cmc.2022.026074

Abstract With the help of network densification, network coverage as well as the throughput can be improved via ultra-dense networks (UDNs). In tandem, Unmanned Aerial Vehicle (UAV) communications have recently garnered much attention because of their high agility as well as widespread applications. In this paper, a cognitive UAV is proposed for wireless nodes power pertaining to the IoT ground terminal. Further, the UAV is included in the IoT system as the source of power for the wireless nodes as well as for resource allocation. The quality of service (QoS) related to the cognitive node was considered as a utility function… More >