Xiaoyan Jiang^1,2, Zuojin Hu¹, Shuihua Wang², Yudong Zhang^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.1, pp. 35-82, 2023, DOI:10.32604/cmes.2023.027676

Abstract Over the years, the continuous development of new technology has promoted research in the field of posture recognition and also made the application field of posture recognition have been greatly expanded. The purpose of this paper is to introduce the latest methods of posture recognition and review the various techniques and algorithms of posture recognition in recent years, such as scale-invariant feature transform, histogram of oriented gradients, support vector machine (SVM), Gaussian mixture model, dynamic time warping, hidden Markov model (HMM), lightweight network, convolutional neural network (CNN). We also investigate improved methods of CNN, such as stacked hourglass networks, multi-stage… More >

Sana Zahir¹, Rafi Ullah Khan¹, Mohib Ullah¹, Muhammad Ishaq¹, Naqqash Dilshad², Amin Ullah^3,*, Mi Young Lee^4,*

Computer Systems Science and Engineering, Vol.46, No.3, pp. 2741-2754, 2023, DOI:10.32604/csse.2023.037706

Abstract The analysis of overcrowded areas is essential for flow monitoring, assembly control, and security. Crowd counting’s primary goal is to calculate the population in a given region, which requires real-time analysis of congested scenes for prompt reactionary actions. The crowd is always unexpected, and the benchmarked available datasets have a lot of variation, which limits the trained models’ performance on unseen test data. In this paper, we proposed an end-to-end deep neural network that takes an input image and generates a density map of a crowd scene. The proposed model consists of encoder and decoder networks comprising batch-free normalization layers… More >

Reda Salama¹, Mahmoud Ragab^1,2,*

Computer Systems Science and Engineering, Vol.46, No.3, pp. 2917-2932, 2023, DOI:10.32604/csse.2023.037016

Abstract In the Internet of Things (IoT) based system, the multi-level client’s requirements can be fulfilled by incorporating communication technologies with distributed homogeneous networks called ubiquitous computing systems (UCS). The UCS necessitates heterogeneity, management level, and data transmission for distributed users. Simultaneously, security remains a major issue in the IoT-driven UCS. Besides, energy-limited IoT devices need an effective clustering strategy for optimal energy utilization. The recent developments of explainable artificial intelligence (XAI) concepts can be employed to effectively design intrusion detection systems (IDS) for accomplishing security in UCS. In this view, this study designs a novel Blockchain with Explainable Artificial Intelligence… More >

Po-Yuan Yang^1,*, Yu-Cheng Liao², Fu-I Chou²

Computer Systems Science and Engineering, Vol.46, No.3, pp. 2861-2880, 2023, DOI:10.32604/csse.2023.036810

Abstract Aquaculture has long been a critical economic sector in Taiwan. Since a key factor in aquaculture production efficiency is water quality, an effective means of monitoring the dissolved oxygen content (DOC) of aquaculture water is essential. This study developed an internet of things system for monitoring DOC by collecting essential data related to water quality. Artificial intelligence technology was used to construct a water quality prediction model for use in a complete system for managing water quality. Since aquaculture water quality depends on a continuous interaction among multiple factors, and the current state is correlated with the previous state, a… More >

Iyad Katib¹, Mahmoud Ragab^2,*

Computer Systems Science and Engineering, Vol.46, No.3, pp. 3749-3765, 2023, DOI:10.32604/csse.2023.036796

Abstract The concept of smart healthcare has seen a gradual increase with the expansion of information technology. Smart healthcare will use a new generation of information technologies, like artificial intelligence, the Internet of Things (IoT), cloud computing, and big data, to transform the conventional medical system in an all-around way, making healthcare highly effective, more personalized, and more convenient. This work designs a new Heap Based Optimization with Deep Quantum Neural Network (HBO-DQNN) model for decision-making in smart healthcare applications. The presented HBO-DQNN model majorly focuses on identifying and classifying healthcare data. In the presented HBO-DQNN model, three stages of operations… More >

Tamim Alkhalifah^1,*, Jimmy Singla², Fahad Alurise¹

Computer Systems Science and Engineering, Vol.46, No.3, pp. 3559-3582, 2023, DOI:10.32604/csse.2023.036534

Abstract The diagnosis of liver fibrosis (LF) is crucial as it is a deadly and life-threatening disease. Artificial intelligence techniques aid doctors by using the previous data on health and making a diagnostic system, which helps to take decisions about patients’ health as experts can. The historical data of a patient’s health can have vagueness, inaccurate, and can also have missing values. The fuzzy logic theory can deal with these issues in the dataset. In this paper, a multilayer fuzzy expert system is developed to diagnose LF. The model is created by using multiple layers of the fuzzy logic approach. This… More >

Saeed Ali Alsareii¹, Muhammad Awais^2,*, Abdulrahman Manaa Alamri¹, Mansour Yousef AlAsmari¹, Muhammad Irfan³, Mohsin Raza², Umer Manzoor⁴

Computer Systems Science and Engineering, Vol.46, No.3, pp. 3715-3728, 2023, DOI:10.32604/csse.2023.035687

Abstract Obesity is a critical health condition that severely affects an individual’s quality of life and well-being. The occurrence of obesity is strongly associated with extreme health conditions, such as cardiac diseases, diabetes, hypertension, and some types of cancer. Therefore, it is vital to avoid obesity and or reverse its occurrence. Incorporating healthy food habits and an active lifestyle can help to prevent obesity. In this regard, artificial intelligence (AI) can play an important role in estimating health conditions and detecting obesity and its types. This study aims to see obesity levels in adults by implementing AI-enabled machine learning on a… More >

Manar Ahmed Hamza^1,*, Hala J. Alshahrani², Khaled Tarmissi³, Ayman Yafoz⁴, Amal S. Mehanna⁵, Ishfaq Yaseen¹, Amgad Atta Abdelmageed¹, Mohamed I. Eldesouki⁶

Computer Systems Science and Engineering, Vol.46, No.3, pp. 3303-3319, 2023, DOI:10.32604/csse.2023.034823

Abstract The term ‘corpus’ refers to a huge volume of structured datasets containing machine-readable texts. Such texts are generated in a natural communicative setting. The explosion of social media permitted individuals to spread data with minimal examination and filters freely. Due to this, the old problem of fake news has resurfaced. It has become an important concern due to its negative impact on the community. To manage the spread of fake news, automatic recognition approaches have been investigated earlier using Artificial Intelligence (AI) and Machine Learning (ML) techniques. To perform the medicinal text classification tasks, the ML approaches were applied, and… More >

A. L. Amutha¹, R. Annie Uthra^1,*, J. Preetha Roselyn², R. Golda Brunet³

Computer Systems Science and Engineering, Vol.46, No.3, pp. 3387-3401, 2023, DOI:10.32604/csse.2023.029904

Abstract The invention of Phasor Measurement Units (PMUs) produce synchronized phasor measurements with high resolution real time monitoring and control of power system in smart grids that make possible. PMUs are used in transmitting data to Phasor Data Concentrators (PDC) placed in control centers for monitoring purpose. A primary concern of system operators in control centers is maintaining safe and efficient operation of the power grid. This can be achieved by continuous monitoring of the PMU data that contains both normal and abnormal data. The normal data indicates the normal behavior of the grid whereas the abnormal data indicates fault or… More >

Ali Akbar Siddique¹, S. M. Umar Talha¹, M. Aamir¹, Abeer D. Algarni², Naglaa F. Soliman^2,*, Walid El-Shafai^3,4

CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3883-3901, 2023, DOI:10.32604/cmc.2023.037413

Abstract The COVID-19 pandemic has devastated our daily lives, leaving horrific repercussions in its aftermath. Due to its rapid spread, it was quite difficult for medical personnel to diagnose it in such a big quantity. Patients who test positive for Covid-19 are diagnosed via a nasal PCR test. In comparison, polymerase chain reaction (PCR) findings take a few hours to a few days. The PCR test is expensive, although the government may bear expenses in certain places. Furthermore, subsets of the population resist invasive testing like swabs. Therefore, chest X-rays or Computerized Vomography (CT) scans are preferred in most cases, and… More >