Taher M. Ghazal^1,2, Sagheer Abbas³, Sundus Munir^3,4, M. A. Khan⁵, Munir Ahmad³, Ghassan F. Issa², Syeda Binish Zahra⁴, Muhammad Adnan Khan^6,*, Mohammad Kamrul Hasan¹

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5005-5019, 2022, DOI:10.32604/cmc.2022.020866 - 11 October 2021

Abstract Alzheimer's disease is a severe neuron disease that damages brain cells which leads to permanent loss of memory also called dementia. Many people die due to this disease every year because this is not curable but early detection of this disease can help restrain the spread. Alzheimer's is most common in elderly people in the age bracket of 65 and above. An automated system is required for early detection of disease that can detect and classify the disease into multiple Alzheimer classes. Deep learning and machine learning techniques are used to solve many medical problems More >

Dah-Jing Jwo^*, Sheng-Feng Chiu

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 6159-6176, 2022, DOI:10.32604/cmc.2022.020793 - 11 October 2021

Abstract In this paper, the data wipe-off (DWO) algorithm is incorporated into the vector tracking loop of the Global Positioning System (GPS) receiver for improving signal tracking performance. The navigation data, which contains information that is necessary to perform navigation computations, are binary phase-shift keying (BPSK) modulated onto the GPS carrier phase with the bit duration of 20 ms (i.e., 50 bits per second). To continuously track the satellite’s signal in weak signal environment, the DWO algorithm on the basis of pre-detection method is adopted to detect data bit sign reversal every 20 ms. Tracking accuracy… More >

Samir Salem Al-Bawri^1,*, Mohammad Tariqul Islam², Mandeep Jit Singh^1,2, Mohd Faizal Jamlos³, Adam Narbudowicz⁴, Max J. Ammann⁴, Dominique M. M. P. Schreurs⁵

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5437-5452, 2022, DOI:10.32604/cmc.2022.020781 - 11 October 2021

Abstract The paper proposes an Indoor Localization System (ILS) which uses only one fixed Base Station (BS) with simple non-reconfigurable antennas. The proposed algorithm measures Received Signal Strength (RSS) and maps it to the location in the room by estimating signal strength of a direct line of sight (LOS) signal and signal of the first order reflection from the wall. The algorithm is evaluated through both simulations and empirical measurements in a furnished open space office, sampling 21 different locations in the room. It is demonstrated the system can identify user’s real-time location with a maximum More >

K. S. Bhuvaneshwari¹, K. Venkatachalam², S. Hubálovský^3,*, P. Trojovský⁴, P. Prabu⁵

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5949-5965, 2022, DOI:10.32604/cmc.2022.020769 - 11 October 2021

Abstract With the rapid growth of internet based services and the data generated on these services are attracted by the attackers to intrude the networking services and information. Based on the characteristics of these intruders, many researchers attempted to aim to detect the intrusion with the help of automating process. Since, the large volume of data is generated and transferred through network, the security and performance are remained an issue. IDS (Intrusion Detection System) was developed to detect and prevent the intruders and secure the network systems. The performance and loss are still an issue because… More >

Kamaledin Abodayeh¹, Ali Raza^2,3,*, Muhammad Rafiq⁴, Muhammad Shoaib Arif⁵, Muhammad Naveed⁵, Zunir Zeb³, Syed Zaheer Abbas³, Kiran Shahzadi³, Sana Sarwar³, Qasim Naveed³, Badar Ul Zaman³, Muhammad Mohsin⁶

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 6073-6088, 2022, DOI:10.32604/cmc.2022.020732 - 11 October 2021

Abstract Pneumonia is a highly transmissible disease in children. According to the World Health Organization (WHO), the most affected regions include south Asia and sub-Saharan Africa. Worldwide, 15% of pediatric deaths can be attributed to pneumonia. Computing techniques have a significant role in science, engineering, and many other fields. In this study, we focused on the efficiency of numerical techniques via computer programs. We studied the dynamics of the pneumonia-like infections of epidemic models using numerical techniques. We discuss two types of analysis: dynamical and numerical. The dynamical analysis included positivity, boundedness, local stability, reproduction number, More >

Abrar M. Alajlan^*

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4241-4259, 2022, DOI:10.32604/cmc.2022.020585 - 11 October 2021

Abstract Detection of the wormhole attacks is a cumbersome process, particularly simplex and duplex over the wireless sensor networks (WSNs). Wormhole attacks are characterized as distributed passive attacks that can destabilize or disable WSNs. The distributed passive nature of these attacks makes them enormously challenging to detect. The main objective is to find all the possible ways in which how the wireless sensor network’s broadcasting character and transmission medium allows the attacker to interrupt network within the distributed environment. And further to detect the serious routing-disruption attack “Wormhole Attack” step by step through the different network More >

Mohamed Yacin Sikkandar^1,*, S. Sabarunisha Begum², Abdulaziz A. Alkathiry³, Mashhor Shlwan N. Alotaibi¹, Md Dilsad Manzar⁴

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4279-4291, 2022, DOI:10.32604/cmc.2022.020571 - 11 October 2021

Abstract Knee Osteoarthritis (KOA) is a degenerative knee joint disease caused by ‘wear and tear’ of ligaments between the femur and tibial bones. Clinically, KOA is classified into four grades ranging from 1 to 4 based on the degradation of the ligament in between these two bones and causes suffering from impaired movement. Identifying this space between bones through the anterior view of a knee X-ray image is solely subjective and challenging. Automatic classification of this process helps in the selection of suitable treatment processes and customized knee implants. In this research, a new automatic classification More >

Muhammad Aasim Qureshi^1,*, Muhammad Asif¹, Mohd Fadzil Hassan², Ghulam Mustafa¹, Muhammad Khurram Ehsan¹, Aasim Ali¹, Unaza Sajid¹

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4987-5004, 2022, DOI:10.32604/cmc.2022.020544 - 11 October 2021

Abstract In machine learning, sentiment analysis is a technique to find and analyze the sentiments hidden in the text. For sentiment analysis, annotated data is a basic requirement. Generally, this data is manually annotated. Manual annotation is time consuming, costly and laborious process. To overcome these resource constraints this research has proposed a fully automated annotation technique for aspect level sentiment analysis. Dataset is created from the reviews of ten most popular songs on YouTube. Reviews of five aspects—voice, video, music, lyrics and song, are extracted. An N-Gram based technique is proposed. Complete dataset consists of… More >

Syed Rizwan Hassan¹, Ishtiaq Ahmad¹, Jamel Nebhen², Ateeq Ur Rehman³, Muhammad Shafiq⁴, Jin-Ghoo Choi^4,*

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 6057-6072, 2022, DOI:10.32604/cmc.2022.020428 - 11 October 2021

Abstract The modern paradigm of the Internet of Things (IoT) has led to a significant increase in demand for latency-sensitive applications in Fog-based cloud computing. However, such applications cannot meet strict quality of service (QoS) requirements. The large-scale deployment of IoT requires more effective use of network infrastructure to ensure QoS when processing big data. Generally, cloud-centric IoT application deployment involves different modules running on terminal devices and cloud servers. Fog devices with different computing capabilities must process the data generated by the end device, so deploying latency-sensitive applications in a heterogeneous fog computing environment is… More >

Aayesha¹, Muhammad Bilal Qureshi², Muhammad Afzaal³, Muhammad Shuaib Qureshi⁴, Jeonghwan Gwak^5,6,7,8,*

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5601-5630, 2022, DOI:10.32604/cmc.2022.020348 - 11 October 2021

Abstract Detection of epileptic seizures on the basis of Electroencephalogram (EEG) recordings is a challenging task due to the complex, non-stationary and non-linear nature of these biomedical signals. In the existing literature, a number of automatic epileptic seizure detection methods have been proposed that extract useful features from EEG segments and classify them using machine learning algorithms. Some characterizing features of epileptic and non-epileptic EEG signals overlap; therefore, it requires that analysis of signals must be performed from diverse perspectives. Few studies analyzed these signals in diverse domains to identify distinguishing characteristics of epileptic EEG signals.… More >