Ling-Jing Kao¹, Chih-Chou Chiu^1,*, Yu-Fan Lin², Heong Kam Weng¹

Computer Systems Science and Engineering, Vol.42, No.2, pp. 493-508, 2022, DOI:10.32604/csse.2022.022166 - 04 January 2022

Abstract Inter-purchase time is a critical factor for predicting customer churn. Improving the prediction accuracy can exploit consumer’s preference and allow businesses to learn about product or pricing plan weak points, operation issues, as well as customer expectations to proactively reduce reasons for churn. Although remarkable progress has been made, classic statistical models are difficult to capture behavioral characteristics in transaction data because transaction data are dependent and short-, medium-, and long-term data are likely to interfere with each other sequentially. Different from literature, this study proposed a hybrid inter-purchase time prediction model for customers of… More >

M. T. Mastura^1,*, R. Nadlene², R. Jumaidin¹, S. I. Abdul Kudus¹, M. R. Mansor², H. M. S. Firdaus¹

Journal of Renewable Materials, Vol.10, No.5, pp. 1221-1238, 2022, DOI:10.32604/jrm.2022.018082 - 22 December 2021

Abstract The employment of natural fibres in fused deposition modeling has raised much attention from researchers in finding a suitable formulation for the natural fibre composite filaments. Moreover, selection of suitable natural fibres for fused deposition modeling should be performed before the development of the composites. It could not be performed without identifying selection criteria that comprehend both materials and fused deposition modeling process requirements. Therefore, in this study, integration of the Analytic Hierarchy Process (AHP)/Analytic Network Process (ANP) has been introduced in selecting the natural fibres based in different clusters of selection concurrently. The selection… More >

M. CAROLINA DI SANTO^1,2,#, AGUSTINA ALAIMO^1,2,#, ANA PAULA DOMÍNGUEZ RUBIO^1,2, OSCAR E. PÉREZ^1,2,*

BIOCELL, Vol.46, No.4, pp. 885-891, 2022, DOI:10.32604/biocell.2022.018391 - 15 December 2021

Abstract Chitosan-based nanocarriers (CS-NCs) show a promising role in improving drugs and bioactive compounds delivery for therapy. However, the effects exerted by CS-NCs at the cellular level, including their recognition and uptake, have not been fully investigated yet. Many factors, including size, shape, concentration, and surface chemistry of CS-NCs, play an important role in determining the types of intracellular signals triggered. The mechanism of uptake and the involvement of the cytoskeleton during the CS-NCs endocytosis variates among the different cell types as well as further effects observed inside cells. In the present work, we discuss the… More >

JIABAO WU^1,2,#, XIAOHUA LIU^1,2,#, LU HAN^1,2, HUA NIE^1,2, YUAN TANG^1,2, YUNGE TANG^1,3, GE SONG^1,5, LIXIN ZHENG^1,4, WEIBING QIN^1,2,*

BIOCELL, Vol.46, No.4, pp. 1013-1023, 2022, DOI:10.32604/biocell.2022.016744 - 15 December 2021

Abstract Piwi-interacting RNAs (piRNAs) is a novel class of non-coding RNAs. However, changes in piRNA expression profiles in recurrent spontaneous abortion (RSA) have not yet been investigated. The aim of this study was to identify differentially expressed piRNAs in deciduas of RSA patients. Decidua tissues were collected by curettage from recruited RSA patients and normal early pregnant (NEP) women with their informed consent. Small RNA sequencing was used to evaluate the differences in piRNA expression profiles between RSA and NEP. The present results demonstrated that the counts of total piRNA reads in RSA samples were increased… More >

Gautham Praveen Ramalingam¹, R. Arockia Xavier Annie¹, Shobana Gopalakrishnan^2,*

Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1479-1492, 2022, DOI:10.32604/iasc.2022.022211 - 09 December 2021

Abstract Detection of intrusion plays an important part in data protection. Intruders will carry out attacks from a compromised user account without being identified. The key technology is the effective detection of sundry threats inside the network. However, process automation is experiencing expanded use of information communication systems, due to high versatility of interoperability and ease off 34 administration. Traditional knowledge technology intrusion detection systems are not completely tailored to process automation. The combined use of fuzziness-based and RNN-IDS is therefore highly suited to high-precision classification, and its efficiency is better compared to that of conventional More >

Mohammad Saidur Rhaman^1,*, Tahjib-Ul-Arif², Mohammad Golam Kibria³, Anamul Hoque³

Phyton-International Journal of Experimental Botany, Vol.91, No.4, pp. 695-711, 2022, DOI:10.32604/phyton.2022.018898 - 09 December 2021

Abstract Socioeconomic development, adaptive capacity of the population, and demographic conditions across the states of South Asia make it more vulnerable to climate change. South Asia is daily going to be more vulnerable to climate change and climatic variability. This region is facing multiple challenges in terms of climate change, dilapidation of ecosystems, and food insecurity. Climate is the primary determining factor for agricultural output, which unswervingly influences food production across the globe. South Asia is mainly an agricultural foundation based region and thus the economy of these regions directly depends on agriculture and agricultural production.… More >

Muhammad Zulqarnain¹, Rozaida Ghazali^1,*, Habib Shah², Lokman Hakim Ismail¹, Abdullah Alsheddy³, Maqsood Mahmud⁴

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3051-3068, 2022, DOI:10.32604/cmc.2022.021629 - 07 December 2021

Abstract Air pollution is a significant problem in modern societies since it has a serious impact on human health and the environment. Particulate Matter (PM_2.5) is a type of air pollution that contains of interrupted elements with a diameter less than or equal to 2.5 m. For risk assessment and epidemiological investigations, a better knowledge of the spatiotemporal variation of PM_2.5 concentration in a constant space-time area is essential. Conventional spatiotemporal interpolation approaches commonly relying on robust presumption by limiting interpolation algorithms to those with explicit and basic mathematical expression, ignoring a plethora of hidden but crucial… More >

Ashraf Ahmed¹, Yousef AbuHour^2,*, Ammar El-Hassan¹

Intelligent Automation & Soft Computing, Vol.32, No.2, pp. 979-990, 2022, DOI:10.32604/iasc.2022.020726 - 17 November 2021

Abstract The Corona (COVID-19) epidemic has triggered interest in many fields of technology, medicine, science, and politics. Most of the mathematical research in this area focused on analyzing the dynamics of the spread of the virus. In this article, after a review of some current methodologies, a non-linear system of differential equations is developed to model the spread of COVID-19. In order to consider a wide spectrum of scenarios, we propose a susceptible-exposed-infected-quarantined-recovered (SEIQRS)-model which was analyzed to determine threshold conditions for its stability, and the number of infected cases that is an infected person will… More >

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 >

Qaisar Abbas^1,*, Mostafa E.A. Ibrahim^1,2, Shakir Khan¹, Abdul Rauf Baig¹

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1999-2007, 2022, DOI:10.32604/cmc.2022.022553 - 03 November 2021

Abstract Traffic accidents are caused by driver fatigue or distraction in many cases. To prevent accidents, several low-cost hypovigilance (hypo-V) systems were developed in the past based on a multimodal-hybrid (physiological and behavioral) feature set. Similarly in this paper, real-time driver inattention and fatigue (Hypo-Driver) detection system is proposed through multi-view cameras and biosignal sensors to extract hybrid features. The considered features are derived from non-intrusive sensors that are related to the changes in driving behavior and visual facial expressions. To get enhanced visual facial features in uncontrolled environment, three cameras are deployed on multiview points… More >