Samreen Naeem¹, Wali Khan Mashwani^2,*, Aqib Ali^1,3, M. Irfan Uddin⁴, Marwan Mahmoud⁵, Farrukh Jamal⁶, Christophe Chesneau⁷

CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 3451-3461, 2021, DOI:10.32604/cmc.2021.015872

Abstract This study proposes an approach based on machine learning to forecast currency exchange rates by applying sentiment analysis to messages on Twitter (called tweets). A dataset of the exchange rates between the United States Dollar (USD) and the Pakistani Rupee (PKR) was formed by collecting information from a forex website as well as a collection of tweets from the business community in Pakistan containing finance-related words. The dataset was collected in raw form, and was subjected to natural language processing by way of data preprocessing. Response variable labeling was then applied to the standardized dataset, where the response variables were… More >

Machiraju Jayalakshmi^{1, *}, S. Nagaraja Rao²

CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1081-1096, 2020, DOI:10.32604/cmc.2020.011710

Abstract In recent years, the development in the field of computer-aided diagnosis (CAD) has increased rapidly. Many traditional machine learning algorithms have been proposed for identifying the pathological brain using magnetic resonance images. The existing algorithms have drawbacks with respect to their accuracy, efficiency, and limited learning processes. To address these issues, we propose a pathological brain tumour detection method that utilizes the Weiner filter to improve the image contrast, 2D- discrete wavelet transformation (2D-DWT) to extract the features, probabilistic principal component analysis (PPCA) and linear discriminant analysis (LDA) to normalize and reduce the features, and a feed-forward neural network (FNN)… More >

M. Carmel Sobia¹, A. Abudhahir²

Intelligent Automation & Soft Computing, Vol.24, No.4, pp. 869-881, 2018, DOI:10.31209/2018.100000014

Abstract In this paper, an efficient facial expression recognition system using ANFIS-MHS (Adaptive Network-based Fuzzy Inference System with Mosquito Host-Seeking) has been proposed. The features were extracted using MLDA (Modified Linear Discriminant Analysis) and then the optimized parameters are computed by using mGSO (modified Glow-worm Swarm Optimization).The proposed system recognizes the facial expressions using ANFIS-MHS. The experimental results demonstrate that the proposed technique is performed better than existing classification schemes like HAKELM (Hybridization of Adaptive Kernel based Extreme Learning Machine), Support Vector Machine (SVM) and Principal Component Analysis (PCA). The proposed approach is implemented in MATLAB. More >

Bing Wang^1,2,*, Yao Yao¹, Liting He¹, Xiangqian Pei¹

Energy Engineering, Vol.117, No.3, pp. 111-128, 2020, DOI:10.32604/EE.2020.010474

Abstract With the huge increase in natural gas consumption, the distortion of natural gas prices, especially in the residential sector, is prominently shaped into a heavy burden for public finance. Although city gate price and a price linkage mechanism have been established, the price tolerance of residential natural gas should be considered when the price of residential gas fluctuates with the upstream gas price. Determinants of the price affordability of residential natural gas consumption at different economic development levels (Beijing, Nanjing, Zhengzhou) are investigated by field survey and online investigation and analyzed by a factor analysis and discriminant analysis. The results… More >

Xinliang Tang¹, Xing Sun¹, Zhenzhou Wang¹, Pingping Yu¹, Ning Cao^{2, *}, Yunfeng Xu³

CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 1185-1198, 2020, DOI:10.32604/cmc.2020.010283

Abstract The appearance of pedestrians can vary greatly from image to image, and different pedestrians may look similar in a given image. Such similarities and variabilities in the appearance and clothing of individuals make the task of pedestrian re-identification very challenging. Here, a pedestrian re-identification method based on the fusion of local features and gait energy image (GEI) features is proposed. In this method, the human body is divided into four regions according to joint points. The color and texture of each region of the human body are extracted as local features, and GEI features of the pedestrian gait are also… More >

Villamil MB¹, NM Amiotti², N Peinemann³

Phyton-International Journal of Experimental Botany, Vol.80, pp. 193-201, 2011, DOI:10.32604/phyton.2011.80.193

Abstract Demand for greater cattle production at the El Caldenal area in central Argentina has resulted in overgrazing in a patchy grassland structure. Patches are clearly identified on the basis of dominant plant species resulting from their grazing history. Our primary objective was to examine the influence of individual plants at each patch on the local multivariate pattern of soil nutrients, assessing the magnitude of the association between the concentration of nutrients in the plant and its underlying soil. Canonical discriminant analysis highlighted the important role of soil organic matter, available P, and Zn content of soils to segregate among patches.… More >

Bonamico¹ NC, MG Balzarini², AT Arroyo², MA Ibañez¹, DG Díaz³, JC Salerno³, MA Di Renzo¹

Phyton-International Journal of Experimental Botany, Vol.79, pp. 31-38, 2010, DOI:10.32604/phyton.2010.79.031

Abstract Resistance to Mal de Río Cuarto (MRC) disease in maize (Zea mays L.) is important in Argentina because the crop area involves a wide region where the disease is endemic. Molecular marker-assisted selection could be used as an additional selection tool to enhance precision of the genotype selection for resistance. It demands the identification of informative markers. Microsatellite (SSR) markers linked to gene(s) associated with resistance to MRC have been reported from previous QTL analyses. These analyses have been made on linkage maps derived from a relatively early mapping population. In advanced populations, where highly distinct genotypes are easily classified,… More >

Xiang Wang^{1, *}, Chen Xiong¹, Qingqi Pei¹, Youyang Qu²

CMC-Computers, Materials & Continua, Vol.57, No.1, pp. 107-121, 2018, DOI:10.32604/cmc.2018.03675

Abstract Most visual privacy protection methods only hide the identity information of the face images, but the expression, behavior and some other information, which are of great significant in the live broadcast and other scenarios, are also destroyed by the privacy protection process. To this end, this paper introduces a method to remove the identity information while preserving the expression information by performing multi-mode discriminant analysis on the images normalized with AAM algorithm. The face images are decomposed into mutually orthogonal subspaces corresponding to face attributes such as gender, race and expression, each of which owns related characteristic parameters. Then, the… More >