Zeshan Faiz¹, Iftikhar Ahmed¹, Dumitru Baleanu^2,3,4, Shumaila Javeed^1,5,6,*

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.2, pp. 1217-1238, 2024, DOI:10.32604/cmes.2023.029879 - 29 January 2024

Abstract The purpose of this research work is to investigate the numerical solutions of the fractional dengue transmission model (FDTM) in the presence of Wolbachia using the stochastic-based Levenberg-Marquardt neural network (LM-NN) technique. The fractional dengue transmission model (FDTM) consists of 12 compartments. The human population is divided into four compartments; susceptible humans (S_h), exposed humans (E_h), infectious humans (I_h), and recovered humans (R_h). Wolbachia-infected and Wolbachia-uninfected mosquito population is also divided into four compartments: aquatic (eggs, larvae, pupae), susceptible, exposed, and infectious. We investigated three different cases of vertical transmission probability (η), namely when Wolbachia-free mosquitoes persist only… More >

Abdulaziz Aldaej^*, Tariq Ahamed Ahanger, Mohammed Yousuf Uddin, Imdad Ullah

CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1723-1745, 2022, DOI:10.32604/cmc.2022.027487 - 18 May 2022

Abstract Viral diseases transmitted by mosquitoes are emerging public health problems across the globe. Dengue is considered to be the most significant mosquito-oriented disease. Conspicuously, the present study provides an effective architecture for Dengue Virus Infection surveillance. The proposed system involves a 4-level architecture for the prediction and prevention of dengue infection outspread. The architectural levels including Dengue Information Acquisition level, Dengue Information Classification level, Dengue-Mining and Extraction level, and Dengue-Prediction and Decision Modeling level enable an individual to periodically monitor his/her probabilistic dengue fever measure. The prediction process is carried out so that proactive measures More >

Mukhsar^1,*, Ansari Saleh Ahmar², M. A. El Safty³, Hamed El-Khawaga^4,5, M. El Sayed⁶

Intelligent Automation & Soft Computing, Vol.34, No.2, pp. 1175-1186, 2022, DOI:10.32604/iasc.2022.025214 - 03 May 2022

Abstract Dengue Hemorrhagic Fever (DHF) is a tropical disease that always attacks densely populated urban communities. Some factors, such as environment, climate and mobility, have contributed to the spread of the disease. The Aedes aegypti mosquito is an agent of dengue virus in humans, and by inhibiting its life cycle it can reduce the spread of the dengue disease. Therefore, it is necessary to involve the dynamics of mosquito's life cycle in a model in order to obtain a reliable risk map for intervention. The aim of this study is to develop a stochastic convolution susceptible, infective,… More >

MUBASHIR HUSSAIN¹, ZEESHAN ALI¹, BIN LIU², JIANGUO DAI¹, XIAOLONG LIU¹, JUNCHEN ZHU¹, YONGJUN TANG¹

BIOCELL, Vol.46, No.1, pp. 61-74, 2022, DOI:10.32604/biocell.2022.016392 - 28 September 2021

Abstract Dengue virus infections are increasing worldwide generally and in Asia, Central and South America and Africa, particularly. It poses a serious threat to the children population. The rapid and accurate diagnostic systems are essentially required due to lack of effective vaccine against dengue virus and the progressive spread of the dengue virus infection. The recent progress in developing micro- and nano-fabrication techniques has led to low cost and scale down the biomedical point-of-care devices. Starting from the conventional and modern available methods for the diagnosis of dengue infection, this review examines several emerging rapid and More >

Norjihan Binti Abdul Ghani^1,*, Suraya Hamid¹, Muneer Ahmad¹, Younes Saadi¹, N.Z. Jhanjhi², Mohammed A. Alzain³, Mehedi Masud⁴

Computer Systems Science and Engineering, Vol.40, No.3, pp. 913-926, 2022, DOI:10.32604/csse.2022.018467 - 24 September 2021

Abstract The world health organization (WHO) terms dengue as a serious illness that impacts almost half of the world’s population and carries no specific treatment. Early and accurate detection of spread in affected regions can save precious lives. Despite the severity of the disease, a few noticeable works can be found that involve sentiment analysis to mine accurate intuitions from the social media text streams. However, the massive data explosion in recent years has led to difficulties in terms of storing and processing large amounts of data, as reliable mechanisms to gather the data and suitable… More >

Samina Amin^1,*, M. Irfan Uddin¹, M. Ali Zeb¹, Ala Abdulsalam Alarood², Marwan Mahmoud³, Monagi H. Alkinani⁴

CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 1317-1332, 2021, DOI:10.32604/cmc.2021.014733 - 12 January 2021

Abstract Social media platforms have lately emerged as a promising tool for predicting the outbreak of epidemics by analyzing information on them with the help of machine learning techniques. Many analytical and statistical models are available to infer a variety of user sentiments in posts on social media. The amount of data generated by social media platforms, such as Twitter, that can be used to track diseases is increasing rapidly. This paper proposes a method for the classification of tweets related to the outbreak of dengue using machine learning algorithms. An artificial neural network (ANN)-based method… More >

Wasfi Shatanawi^1,2,3, Ali Raza^4,5,*, Muhammad Shoaib Arif⁴, Muhammad Rafiq⁶, Mairaj Bibi⁷, Muhammad Mohsin⁸

CMES-Computer Modeling in Engineering & Sciences, Vol.126, No.1, pp. 201-215, 2021, DOI:10.32604/cmes.2021.012111 - 22 December 2020

Abstract Nonlinear stochastic modelling plays an important character in the different fields of sciences such as environmental, material, engineering, chemistry, physics, biomedical engineering, and many more. In the current study, we studied the computational dynamics of the stochastic dengue model with the real material of the model. Positivity, boundedness, and dynamical consistency are essential features of stochastic modelling. Our focus is to design the computational method which preserves essential features of the model. The stochastic non-standard finite difference technique is most efficient as compared to other techniques used in literature. Analysis and comparison were explored in More >