HAIZHENG LIU¹, SHAOFEI CHANG^2,*

BIOCELL, Vol.46, No.2, pp. 453-462, 2022, DOI:10.32604/biocell.2021.015340 - 20 October 2021

Abstract Lysophosphatidylcholine acyltransferase 1 (LPCAT1) is a phospholipid acyltransferase that promotes phospholipid synthesis and plasma membrane reconstruction. Exosomes play an important role in tumor metastasis. The release and uptake of exosomes are key steps of their functions and depend on plasma membrane fusion and plasma membrane receptors, respectively. The purpose of this study was to explore whether LPCAT1-induced plasma membrane remodeling would change the secretion and uptake behavior of exosomes in tumor cells. We first confirmed the abnormally high expression of LPCAT1 in colorectal cancer cells by quantitative real-time PCR (qPCR) and Western blot analysis. Then,… More >

Yu Xue^1,2,*, Chen Chen¹, ChiShe Wang², Linguo Li³, Romany F. Mansour⁴

Intelligent Automation & Soft Computing, Vol.30, No.3, pp. 973-982, 2021, DOI:10.32604/iasc.2021.017607 - 20 August 2021

Abstract Face recognition technology has many usages in the real-world applications, and it has generated extensive interest in recent years. However, the amount of data in a digital image is growing explosively, taking up a lot of storage and transmission resources. There is a lot of redundancy in an image data representation. Thus, image compression has become a hot topic. The principal component analysis (PCA) can effectively remove the correlation of an image and condense the image information into a characteristic image with several main components. At the same time, it can restore different data images… More >

Huizhi Gou^1,2,*, Yuncai Ning¹

CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.2, pp. 803-822, 2021, DOI:10.32604/cmes.2021.015922 - 22 July 2021

Abstract Accurate photovoltaic (PV) power prediction can effectively help the power sector to make rational energy planning and dispatching decisions, promote PV consumption, make full use of renewable energy and alleviate energy problems. To address this research objective, this paper proposes a prediction model based on kernel principal component analysis (KPCA), modified cuckoo search algorithm (MCS) and deep convolutional neural networks (DCNN). Firstly, KPCA is utilized to reduce the dimension of the feature, which aims to reduce the redundant input vectors. Then using MCS to optimize the parameters of DCNN. Finally, the photovoltaic power forecasting method More >

Sunil Kr. Jha^1,*, Ivan Uzunov², Xiaorui Zhang¹

CMES-Computer Modeling in Engineering & Sciences, Vol.126, No.3, pp. 991-1009, 2021, DOI:10.32604/cmes.2021.011821 - 19 February 2021

Abstract Ohrid trout (Salamo letnica) is an endemic species of fish found in Lake Ohrid in the Former Yugoslav Republic of Macedonia (FYROM). The growth of Ohrid trout was examined in a controlled environment for a certain period, thereafter released into the lake to grow their natural population. The external features of the fish were measured regularly during the cultivation period in the laboratory to monitor their growth. The data mining methods-based computational model can be used for fast, accurate, reliable, automatic, and improved growth monitoring procedures and classification of Ohrid trout. With this motivation, a combined… More >

Shichao Wang, Yu Xue^*, Weiwei Jia

Journal on Big Data, Vol.3, No.1, pp. 1-9, 2021, DOI:10.32604/jbd.2021.010364 - 25 January 2021

Abstract In many fields such as signal processing, machine learning, pattern recognition and data mining, it is common practice to process datasets containing huge numbers of features. In such cases, Feature Selection (FS) is often involved. Meanwhile, owing to their excellent global search ability, evolutionary computation techniques have been widely employed to the FS. So, as a powerful global search method and calculation fast than other EC algorithms, PSO can solve features selection problems well. However, when facing a large number of feature selection, the efficiency of PSO drops significantly. Therefore, plenty of works have been… More >

Xueqing Wang¹, Shuang Liu^1,*, Lejun Zhang²

Computer Systems Science and Engineering, Vol.36, No.1, pp. 259-269, 2021, DOI:10.32604/csse.2021.014343 - 23 December 2020

Abstract The cost of highway is affected by many factors. Its composition and calculation are complicated and have great ambiguity. Calculating the cost of highway according to the traditional highway engineering estimation method is a completely tedious task. Constructing a highway cost prediction model can forecast the value promptly and improve the accuracy of highway engineering cost. This work sorts out and collects 60 sets of measured data of highway engineering; establishes an expressway cost index system based on 10 factors, including main route mileage, roadbed width, roadbed earthwork, and number of bridges; and processes the More >

Chang Li^*, Shuohui Gao^*, Xiaoping Li^†, Chang Li^‡, Lianjun Ma^§

Oncology Research, Vol.28, No.6, pp. 675-679, 2020, DOI:10.3727/096504021X16137463165406

Abstract Colon cancer is one of the most lethal varieties of cancer. Chemotherapy remains as one of the principal treatment approaches for colon cancer. The anticancer activity of procaine (PCA), which is a local anesthetic drug, has been explored in different studies. In our study, we aimed to explore the anticancer effect of PCA on colon cancer and its underlying mechanism. The results showed that PCA significantly inhibited cell viability, increased the percentage of apoptotic cells, and decreased the expression level of RhoA in HCT116 cells in a dose-dependent manner (p < 0.05 or p < 0.01).… More >

Rongyu Chen, Lili Pan^*, Yan Zhou, Qianhui Lei

Journal of Information Hiding and Privacy Protection, Vol.2, No.2, pp. 67-76, 2020, DOI:10.32604/jihpp.2020.010472 - 11 November 2020

Abstract With the rapid development of information technology, the speed and efficiency of image retrieval are increasingly required in many fields, and a compelling image retrieval method is critical for the development of information. Feature extraction based on deep learning has become dominant in image retrieval due to their discrimination more complete, information more complementary and higher precision. However, the high-dimension deep features extracted by CNNs (convolutional neural networks) limits the retrieval efficiency and makes it difficult to satisfy the requirements of existing image retrieval. To solving this problem, the high-dimension feature reduction technology is… More >

Wu Zeng¹, Zhanxiong Huo^{1, *}, Yuxuan Xie², Yingxiang Jiang¹, Kun Hu¹

CMC-Computers, Materials & Continua, Vol.64, No.3, pp. 1869-1883, 2020, DOI:10.32604/cmc.2020.010139 - 30 June 2020

Abstract Applying computer technology to the field of food safety, and how to identify liquor quickly and accurately, is of vital importance and has become a research focus. In this paper, sparse principal component analysis (SPCA) was applied to seek sparse factors of the mid-infrared (MIR) spectra of five famous vintage year Chinese spirits. The results showed while meeting the maximum explained variance, 23 sparse principal components (PCs) were selected as features in a support vector machine (SVM) model, which obtained a 97% classification accuracy. By comparison principal component analysis (PCA) selected 10 PCs as features More >

Nana Zhang¹, Kun Zhu¹, Shi Ying^{1, *}, Xu Wang²

CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 471-499, 2020, DOI:10.32604/cmc.2020.010117 - 20 May 2020

Abstract Software defect prediction is a research hotspot in the field of software engineering. However, due to the limitations of current machine learning algorithms, we can’t achieve good effect for defect prediction by only using machine learning algorithms. In previous studies, some researchers used extreme learning machine (ELM) to conduct defect prediction. However, the initial weights and biases of the ELM are determined randomly, which reduces the prediction performance of ELM. Motivated by the idea of search based software engineering, we propose a novel software defect prediction model named KAEA based on kernel principal component analysis… More >