Sa Math¹, Prohim Tam¹, Seokhoon Kim^2,*

CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 3433-3450, 2021, DOI:10.32604/cmc.2021.015490

Abstract In the Next Generation Radio Networks (NGRN), there will be extreme massive connectivity with the Heterogeneous Internet of Things (HetIoT) devices. The millimeter-Wave (mmWave) communications will become a potential core technology to increase the capacity of Radio Networks (RN) and enable Multiple-Input and Multiple-Output (MIMO) of Radio Remote Head (RRH) technology. However, the challenging key issues in unfair radio resource handling remain unsolved when massive requests are occurring concurrently. The imbalance of resource utilization is one of the main issues occurs when there is overloaded connectivity to the closest RRH receiving exceeding requests. To handle… More >

Imran Ashraf¹, Waleed S. Alnumay², Rashid Ali³, Soojung Hur¹, Ali Kashif Bashir⁴, Yousaf Bin Zikria^1,*

CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 3009-3044, 2021, DOI:10.32604/cmc.2021.015140

Abstract The COVID-19 pandemic has caused hundreds of thousands of deaths, millions of infections worldwide, and the loss of trillions of dollars for many large economies. It poses a grave threat to the human population with an excessive number of patients constituting an unprecedented challenge with which health systems have to cope. Researchers from many domains have devised diverse approaches for the timely diagnosis of COVID-19 to facilitate medical responses. In the same vein, a wide variety of research studies have investigated underlying medical conditions for indicators suggesting the severity and mortality of, and role of… More >

Nadia Tabassum¹, Allah Ditta², Tahir Alyas³, Sagheer Abbas⁴, Hani Alquhayz⁵, Natash Ali Mian⁶, Muhammad Adnan Khan^7,*

CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 3129-3141, 2021, DOI:10.32604/cmc.2021.014729

Abstract Cloud computing is becoming popular technology due to its functional properties and variety of customer-oriented services over the Internet. The design of reliable and high-quality cloud applications requires a strong Quality of Service QoS parameter metric. In a hyperconverged cloud ecosystem environment, building high-reliability cloud applications is a challenging job. The selection of cloud services is based on the QoS parameters that play essential roles in optimizing and improving cloud rankings. The emergence of cloud computing is significantly reshaping the digital ecosystem, and the numerous services offered by cloud service providers are playing a vital… More >

Huma¹, Muhammad Khalid Sohail², Nadeem Akhtar³, Dost Muhammad³, Humaira Afzal⁴, Muhammad Rafiq Mufti⁵, Shahid Hussain^6,*, Mansoor Ahmed¹

CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 3737-3748, 2021, DOI:10.32604/cmc.2021.014398

Abstract This study aims to identify the potential association of mental health and social media forum during the outbreak of COVID-19 pandemic. COVID-19 brings a lot of challenges to government globally. Among the different strategies the most extensively adopted ones were lockdown, social distancing, and isolation among others. Most people with no mental illness history have been found with high risk of distress and psychological discomfort due to anxiety of being infected with the virus. Panic among people due to COVID-19 spread faster than the disease itself. The misinformation and excessive usage of social media in… More >

Shakeel Ahmed^*, Abdulaziz Alhumam

Computer Systems Science and Engineering, Vol.37, No.1, pp. 1-18, 2021, DOI:10.32604/csse.2021.015775

Abstract This article evaluates the security techniques that are used to maintain the healthcare devices, and proposes a mathematical model to list these in the order of priority and preference. To accomplish the stated objective, the article uses the Fuzzy Analytic Network Process (ANP) integrated with Technical for Order Preference by Similarities to Ideal Solution (TOPSIS) to find the suitable alternatives of the security techniques for securing the healthcare devices from trespassing. The methodology is enlisted to rank the alternatives/ techniques based on their weights’ satisfaction degree. Thereafter, the ranks of the alternatives determine the order More >

Zihao Shen^1,2, Hui Wang^1,*, Kun Liu¹, Peiqian Liu¹, Menglong Ba¹, MengYao Zhao³

Computer Systems Science and Engineering, Vol.37, No.1, pp. 121-133, 2021, DOI:10.32604/csse.2021.014988

Abstract The rapid progress of the Internet has exposed networks to an increased number of threats. Intrusion detection technology can effectively protect network security against malicious attacks. In this paper, we propose a ReliefF-P-Naive Bayes and softmax regression (RP-NBSR) model based on machine learning for network attack detection to improve the false detection rate and F1 score of unknown intrusion behavior. In the proposed model, the Pearson correlation coefficient is introduced to compensate for deficiencies in correlation analysis between features by the ReliefF feature selection algorithm, and a ReliefF-Pearson correlation coefficient (ReliefF-P) algorithm is proposed. Then, More >

Sinil Mubarak¹, Mohamed Hadi Habaebi^1,*, Md Rafiqul Islam¹, Farah Diyana Abdul Rahman, Mohammad Tahir²

Computer Systems Science and Engineering, Vol.37, No.1, pp. 33-46, 2021, DOI:10.32604/csse.2021.014384

Abstract An Intrusion Detection System (IDS) provides a front-line defense mechanism for the Industrial Control System (ICS) dedicated to keeping the process operations running continuously for 24 hours in a day and 7 days in a week. A well-known ICS is the Supervisory Control and Data Acquisition (SCADA) system. It supervises the physical process from sensor data and performs remote monitoring control and diagnostic functions in critical infrastructures. The ICS cyber threats are growing at an alarming rate on industrial automation applications. Detection techniques with machine learning algorithms on public datasets, suitable for intrusion detection of More >

Kaustubh Arun Bhavsar¹, Ahed Abugabah², Jimmy Singla^1,*, Ahmad Ali AlZubi³, Ali Kashif Bashir⁴, Nikita⁵

CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 1997-2014, 2021, DOI:10.32604/cmc.2021.014943

Abstract The unavailability of sufficient information for proper diagnosis, incomplete or miscommunication between patient and the clinician, or among the healthcare professionals, delay or incorrect diagnosis, the fatigue of clinician, or even the high diagnostic complexity in limited time can lead to diagnostic errors. Diagnostic errors have adverse effects on the treatment of a patient. Unnecessary treatments increase the medical bills and deteriorate the health of a patient. Such diagnostic errors that harm the patient in various ways could be minimized using machine learning. Machine learning algorithms could be used to diagnose various diseases with high… More >

Mohammed A. Aleid¹, Khaled A. Z. Alyamani², Mohieddine Rahmouni^2,3, Theyazn H. H. Aldhyani^2,*, Nizar Alsharif⁴, Mohammed Y. Alzahrani⁴

CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2029-2047, 2021, DOI:10.32604/cmc.2021.014873

Abstract This article aims to assess health habits, safety behaviors, and anxiety factors in the community during the novel coronavirus disease (COVID-19) pandemic in Saudi Arabia based on primary data collected through a questionnaire with 320 respondents. In other words, this paper aims to provide empirical insights into the correlation and the correspondence between socio-demographic factors (gender, nationality, age, citizenship factors, income, and education), and psycho-behavioral effects on individuals in response to the emergence of this new pandemic. To focus on the interaction between these variables and their effects, we suggest different methods of analysis, comprising… More >

Muhammad Kashif¹, Ayyaz Hussain², Asim Munir¹, Abdul Basit Siddiqui³, Aaqif Afzaal Abbasi⁴, Muhammad Aakif⁵, Arif Jamal Malik⁴, Fayez Eid Alazemi⁶, Oh-Young Song^7,*

CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2123-2139, 2021, DOI:10.32604/cmc.2021.014782

Abstract Expression detection plays a vital role to determine the patient’s condition in healthcare systems. It helps the monitoring teams to respond swiftly in case of emergency. Due to the lack of suitable methods, results are often compromised in an unconstrained environment because of pose, scale, occlusion and illumination variations in the image of the face of the patient. A novel patch-based multiple local binary patterns (LBP) feature extraction technique is proposed for analyzing human behavior using facial expression recognition. It consists of three-patch [TPLBP] and four-patch LBPs [FPLBP] based feature engineering respectively. Image representation is… More >