Bo Liu^*, Wei Xie, Jiahao Zhang, Cong Chen

International Journal of Mental Health Promotion, Vol.23, No.4, pp. 589-604, 2021, DOI:10.32604/IJMHP.2021.015045

Abstract At present, the academic researches on moral choices focus mainly on the individuals’ external behaviors, without fully considering the influences of the individuals’ internal psychological factors. Based on the model of complete information static games in the Non-cooperative Game theory, the present research has designed a “Red and Blue Experiment” to explore the psychological influencing factors of the new generation employees’ moral choices. The research has conducted psychoanalysis on the new generation employees through experiments and interviews with 118 data sources, and concluded the characteristics in relation to the different stages of psychological processes and moral choices of the experimental… More >

Zilong Jin^1,2, Chengbo Zhang¹ , Kan Yao³ , Dun Cao⁴ , Seokhoon Kim⁵, Yuanfeng Jin^6,*

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5991-6005, 2022, DOI:10.32604/cmc.2022.021498

Abstract

Cognitive radio devices can utilize the licensed channels in an opportunistic manner to solve the spectrum scarcity issue occurring in the unlicensed spectrum. However, these cognitive radio devices (secondary users) are greatly affected by the original users (primary users) of licensed channels. Cognitive users have to adjust operation parameters frequently to adapt to the dynamic network environment, which causes extra energy consumption. Energy consumption can be reduced by predicting the future activity of primary users. However, the traditional prediction-based algorithms require large historical data to achieve a satisfying precision accuracy which will consume a lot of time and memory space.… More >

Nouh Sabri Elmitwally^1,2, Asma Kanwal^3,4, Sagheer Abbas³, Muhammad A. Khan⁵, Muhammad Adnan Khan^6,*, Munir Ahmad³, Saad Alanazi¹

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4947-4964, 2022, DOI:10.32604/cmc.2022.021104

Abstract Detection of personality using emotions is a research domain in artificial intelligence. At present, some agents can keep the human’s profile for interaction and adapts themselves according to their preferences. However, the effective method for interaction is to detect the person’s personality by understanding the emotions and context of the subject. The idea behind adding personality in cognitive agents begins an attempt to maximize adaptability on the basis of behavior. In our daily life, humans socially interact with each other by analyzing the emotions and context of interaction from audio or visual input. This paper presents a conceptual personality model… More >

Nitin Mittal¹, Harbinder Singh¹, Vikas Mittal², Shubham Mahajan³, Amit Kant Pandit³, Mehedi Masud⁴, Mohammed Baz⁵, Mohamed Abouhawwash^6,7,*

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3821-3835, 2022, DOI:10.32604/cmc.2022.020592

Abstract Cognitive Radio (CR) has been developed as an enabling technology that allows the unused or underused spectrum to be used dynamically to increase spectral efficiency. To improve the overall performance of the CR system it is extremely important to adapt or reconfigure the system parameters. The Decision Engine is a major module in the CR-based system that not only includes radio monitoring and cognition functions but also responsible for parameter adaptation. As meta-heuristic algorithms offer numerous advantages compared to traditional mathematical approaches, the performance of these algorithms is investigated in order to design an efficient CR system that is able… More >

Haithem Ben Chikha, Ahmad Almadhor^*

CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 1799-1814, 2022, DOI:10.32604/cmc.2022.018819

Abstract To promote reliable and secure communications in the cognitive radio network, the automatic modulation classification algorithms have been mainly proposed to estimate a single modulation. In this paper, we address the classification of superimposed modulations dedicated to 5G multiple-input multiple-output (MIMO) two-way cognitive relay network in realistic channels modeled with Nakagami- distribution. Our purpose consists of classifying pairs of users modulations from superimposed signals. To achieve this goal, we apply the higher-order statistics in conjunction with the MultiBoostAB classifier. We use several efficiency metrics including the true positive (TP) rate, false positive (FP) rate, precision, recall, F-Measure and receiver operating… More >

Xiaoli He¹, Yu Song^2,3,*, Yu Xue⁴, Muhammad Owais⁵, Weijian Yang¹, Xinwen Cheng¹

CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 195-212, 2022, DOI:10.32604/cmc.2022.017105

Abstract Spectrum resources are the precious and limited natural resources. In order to improve the utilization of spectrum resources and maximize the network throughput, this paper studies the resource allocation of the downlink cognitive radio network with non-orthogonal multiple access (CRN-NOMA). NOMA, as the key technology of the fifth-generation communication (5G), can effectively increase the capacity of 5G networks. The optimization problem proposed in this paper aims to maximize the number of secondary users (SUs) accessing the system and the total throughput in the CRN-NOMA. Under the constraints of total power, minimum rate, interference and SINR, CRN-NOMA throughput is maximized by… More >

Nora Shoaip¹, Amira Rezk¹, Shaker EL-Sappagh^2,3, Tamer Abuhmed^4,*, Sherif Barakat¹, Mohammed Elmogy⁵

CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 3531-3548, 2021, DOI:10.32604/cmc.2021.019069

Abstract Alzheimer’s disease (AD) is a very complex disease that causes brain failure, then eventually, dementia ensues. It is a global health problem. 99% of clinical trials have failed to limit the progression of this disease. The risks and barriers to detecting AD are huge as pathological events begin decades before appearing clinical symptoms. Therapies for AD are likely to be more helpful if the diagnosis is determined early before the final stage of neurological dysfunction. In this regard, the need becomes more urgent for biomarker-based detection. A key issue in understanding AD is the need to solve complex and high-dimensional… More >

Fatmah Abdulrahman Baothman^*, Osama Ahmed Abulnaja, Fatima Jafar Muhdher

CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 3337-3363, 2021, DOI:10.32604/cmc.2021.017637

Abstract Existing literature shows cultural crowd management has unforeseen issues due to four dynamic elements; time, capacity, speed, and culture. Cross-cultural variations are increasing the complexity level because each mass and event have different characteristics and challenges. However, no prior study has employed the six Hofstede Cultural Dimensions (HCD) for predicting crowd behaviors. This study aims to develop the Cultural Crowd-Artificial Neural Network (CC-ANN) learning model that considers crowd’s HCD to predict their physical (distance and speed) and social (collectivity and cohesion) characteristics. The model was developed towards a cognitive intelligent decision support tool where the predicted characteristics affect the estimated… More >

Yujie Zhou¹, Jin Liu^1,*, Yurong Xie¹, Y. Ken Wang²

Intelligent Automation & Soft Computing, Vol.30, No.2, pp. 715-733, 2021, DOI:10.32604/iasc.2021.020184

Abstract Text recognition is a crucial and challenging task, which aims at translating a cropped text instance image into a target string sequence. Recently, Convolutional neural networks (CNN) have been widely used in text recognition tasks as it can effectively capture semantic and structural information in text. However, most existing methods are usually based on contextual clues. If only recognize a single character, the accuracy of these approaches can be reduced. For example, it is difficult to distinguish 0 and O in the traditional CNN network because they are very similar in composition and structure. To solve this problem, we propose… More >

Abhinav Adarsh¹, Basant Kumar¹, Manoj Gupta², Arun Kumar², Aman Singh^3,*, Mehedi Masud⁴, Fahad A. Alraddady⁵

CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 35-49, 2021, DOI:10.32604/cmc.2021.017647

Abstract This paper presents a new low delay centralized cooperative spectrum sensing method based on dynamic voting rule using multiple threshold level, for indoor hospital environment, where fading and direct path loss both are together responsible for variation in signal strength. In the proposed algorithm, weights of Cognitive Radios (CRs) in terms of assigned vote-count are estimated based on the sensed energy values with respect to multiple fixed threshold levels, so that the direct path loss can be dealt without further increasing the error, which occurs due to fading. For indoor hospital like environment, Rician fading model is more appropriate. Therefore,… More >