Yanjun Yan, Kai Chen^*, Hang Geng, Wenqian Fan, Xinrui Zhou

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.2, pp. 1345-1379, 2023, DOI:10.32604/cmes.2023.027252

Abstract With increasing global concerns about clean energy in smart grids, the detection of power quality disturbances (PQDs) caused by energy instability is becoming more and more prominent. It is well acknowledged that the PQD effects on power grid equipment are destructive and hazardous, which causes irreversible damage to underlying electrical/electronic equipment of the concerned intelligent grids. In order to ensure safe and reliable equipment implementation, appropriate PQD detection technologies must be adopted to avoid such adverse effects. This paper summarizes the newly proposed and traditional PQD detection techniques in order to give a quick start to new researchers in the… More > Graphic Abstract

Siti Nurul Aqmariah Mohd Kanafiah^1,*, Mohd Yusoff Mashor¹, Zeehaida Mohamed², Yap Chun Way¹, Shazmin Aniza Abdul Shukor¹, Yessi Jusman³

Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 687-697, 2022, DOI:10.32604/iasc.2022.024361

Abstract Malaria is categorised as a dangerous disease that can cause fatal in many countries. Therefore, early detection of malaria is essential to get rapid treatment. The malaria detection process is usually carried out with a 100x magnification of thin blood smear using microscope observation. However, the microbiologist required a long time to identify malaria types before applying any proper treatment to the patient. It also has difficulty to differentiate the species in trophozoite stages because of similar characteristics between species. To overcome these problems, a computer-aided diagnosis system is proposed to classify trophozoite stages of Plasmodium Knowlesi (PK), Plasmodium Falciparum… More >

CSS Anupama¹, T. J. Benedict Jose², Heba F. Eid³, Nojood O Aljehane⁴, Fahd N. Al-Wesabi^5,*, Marwa Obayya⁶, Anwer Mustafa Hilal⁷

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3969-3983, 2022, DOI:10.32604/cmc.2022.022701

Abstract Biomedical images are used for capturing the images for diagnosis process and to examine the present condition of organs or tissues. Biomedical image processing concepts are identical to biomedical signal processing, which includes the investigation, improvement, and exhibition of images gathered using x-ray, ultrasound, MRI, etc. At the same time, cervical cancer becomes a major reason for increased women's mortality rate. But cervical cancer is an identified at an earlier stage using regular pap smear images. In this aspect, this paper devises a new biomedical pap smear image classification using cascaded deep forest (BPSIC-CDF) model on Internet of Things (IoT)… More >