S. Kusuma^*, Dr. Jothi K. R

Computer Systems Science and Engineering, Vol.41, No.3, pp. 1273-1289, 2022, DOI:10.32604/csse.2022.021741 - 10 November 2021

Abstract One of the severe health problems and the most common types of heart disease (HD) is Coronary heart disease (CHD). Due to the lack of a healthy lifestyle, HD would cause frequent mortality worldwide. If the heart attack occurs without any symptoms, it cannot be cured by an intelligent detection system. An effective diagnosis and detection of CHD should prevent human casualties. Moreover, intelligent systems employ clinical-based decision support approaches to assist physicians in providing another option for diagnosing and detecting HD. This paper aims to introduce a heart disease prediction model including phases like… More >

Loan Trinh Van¹, Quang H. Nguyen^1,*, Thuy Dao Thi Le²

Computer Systems Science and Engineering, Vol.41, No.3, pp. 1083-1098, 2022, DOI:10.32604/csse.2022.021635 - 10 November 2021

Abstract For human-machine communication to be as effective as human-to-human communication, research on speech emotion recognition is essential. Among the models and the classifiers used to recognize emotions, neural networks appear to be promising due to the network’s ability to learn and the diversity in configuration. Following the convolutional neural network, a capsule neural network (CapsNet) with inputs and outputs that are not scalar quantities but vectors allows the network to determine the part-whole relationships that are specific 6 for an object. This paper performs speech emotion recognition based on CapsNet. The corpora for speech emotion… More >

Muhammad Ali Ismail^*, Maria Waqas, Farah Sadiq

Computer Systems Science and Engineering, Vol.41, No.3, pp. 1143-1155, 2022, DOI:10.32604/csse.2022.021604 - 10 November 2021

Abstract The N-body problem in classical physics, is the calculation of force of gravitational attraction of heavenly bodies towards each other. Solving this problem for many heavenly bodies has always posed a challenge to physicists and mathematicians. Large number of bodies, huge masses, long distances and exponentially increasing number of equations of motion of the bodies have been the major hurdles in solving this problem for large and complex galaxies. Advent of high performance computational machines have mitigated the problem to much extent, but still for large number of bodies it consumes huge amount of resources… More >

Anika Tahsin Meem¹, Mohammad Monirujjaman Khan^1,*, Mehedi Masud², Sultan Aljahdali²

Computer Systems Science and Engineering, Vol.41, No.3, pp. 1223-1240, 2022, DOI:10.32604/csse.2022.021563 - 10 November 2021

Abstract The COVID-19 pandemic has caused trouble in people’s daily lives and ruined several economies around the world, killing millions of people thus far. It is essential to screen the affected patients in a timely and cost-effective manner in order to fight this disease. This paper presents the prediction of COVID-19 with Chest X-Ray images, and the implementation of an image processing system operated using deep learning and neural networks. In this paper, a Deep Learning, Machine Learning, and Convolutional Neural Network-based approach for predicting Covid-19 positive and normal patients using Chest X-Ray pictures is proposed.… More >

Abolfazl Mehbodniya¹, Surbhi Bhatia², Arwa Mashat³, Mohanraj Elangovan^4,*, Sudhakar Sengan⁵

Computer Systems Science and Engineering, Vol.41, No.3, pp. 1071-1082, 2022, DOI:10.32604/csse.2022.021529 - 10 November 2021

Abstract Wireless Sensor Network (WSN) is an independent device that comprises a discrete collection of Sensor Nodes (SN) to sense environmental positions, device monitoring, and collection of information. Due to limited energy resources available at SN, the primary issue is to present an energy-efficient framework and conserve the energy while constructing a route path along with each sensor node. However, many energy-efficient techniques focused drastically on energy harvesting and reduced energy consumption but failed to support energy-efficient routing with minimal energy consumption in WSN. This paper presents an energy-efficient routing system called Energy-aware Proportional Fairness Multi-user… More >

Abhishek Kumar Pandey¹, Jehad F. Al-Amri², Ahmad F. Subahi³, Rajeev Kumar^4,*, Raees Ahmad Khan¹

Computer Systems Science and Engineering, Vol.41, No.3, pp. 959-974, 2022, DOI:10.32604/csse.2022.021443 - 10 November 2021

Abstract The outbreak of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2 virus or COVID-19) disease was declared pandemic by the World Health Organization (WHO) on March 11, 2020. COVID-19 has already affected more than 211 nations. In such a bleak scenario, it becomes imperative to analyze and identify those regions in Saudi Arabia that are at high risk. A preemptive study done in the context of predicting the possible COVID-19 hotspots would facilitate in the implementation of prompt and targeted countermeasures against SARS-CoV-2, thus saving many lives. Working towards this intent, the present study adopts a… More >

Ahed Abugabah^1,*, Atif Mehmood², Ahmad Ali AL Zubi³, Louis Sanzogni⁴

Computer Systems Science and Engineering, Vol.41, No.3, pp. 997-1008, 2022, DOI:10.32604/csse.2022.021438 - 10 November 2021

Abstract The outbreak of the novel coronavirus has spread worldwide, and millions of people are being infected. Image or detection classification is one of the first application areas of deep learning, which has a significant contribution to medical image analysis. In classification detection, one or more images (detection) are usually used as input, and diagnostic variables (such as whether there is a disease) are used as output. The novel coronavirus has spread across the world, infecting millions of people. Early-stage detection of critical cases of COVID-19 is essential. X-ray scans are used in clinical studies to… More >

Mohammad Alkhatib^*

Computer Systems Science and Engineering, Vol.41, No.3, pp. 975-995, 2022, DOI:10.32604/csse.2022.021398 - 10 November 2021

Abstract Improving the quality assurance (QA) processes and acquiring accreditation are top priorities for academic programs. The learning outcomes (LOs) assessment and continuous quality improvement represent core components of the quality assurance system (QAS). Current assessment methods suffer deficiencies related to accuracy and reliability, and they lack well-organized processes for continuous improvement planning. Moreover, the absence of automation, and integration in QA processes forms a major obstacle towards developing efficient quality system. There is a pressing need to adopt security protocols that provide required security services to safeguard the valuable information processed by QAS as well.… More >

Fuad A.M. Al-Yarimi^1,*, Sami Althahabi¹, Majdy Mohammed Eltayeb²

Computer Systems Science and Engineering, Vol.41, No.3, pp. 919-932, 2022, DOI:10.32604/csse.2022.021272 - 10 November 2021

Abstract Cloud resource scheduling is gaining prominence with the increasing trends of reliance on cloud infrastructure solutions. Numerous sets of cloud resource scheduling models were evident in the literature. Cloud resource scheduling refers to the distinct set of algorithms or programs the service providers engage to maintain the service level allocation for various resources over a virtual environment. The model proposed in this manuscript schedules resources of virtual machines under potential volatility aspects, which can be applied for any priority metric chosen by the server administrators. Also, the model can be flexible for any time frame-based More >

Zhiqiu Yu^1,*, Shuo-Yan Chou¹, Phan Nguyen Ky Phuc², Tiffany Hui-Kuang Yu³

Computer Systems Science and Engineering, Vol.41, No.3, pp. 1191-1205, 2022, DOI:10.32604/csse.2022.021239 - 10 November 2021

Abstract This research aims to study the sustainability of Taiwan power supply chain based on system dynamics forecasting. The paper tries to investigate electricity shortage effects not only on the industrial side, but also from the standpoint of society. In our model, different forecasting methods such as linear regression, time series analysis, and gray forecasting are also considered to predict the parameters. Further tests such as the structure, dimension, historical fit, and sensitivity of the model are also conducted in this paper. Through analysis forecasting result, we believe that the demand for electricity in Taiwan will More >