Shabana R. Ziyad^1,*, Liyakathunisa², Eman Aljohani², I. A. Saeed³

CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 1515-1534, 2023, DOI:10.32604/cmc.2023.040874

Abstract Autism spectrum disorder (ASD), classified as a developmental disability, is now more common in children than ever. A drastic increase in the rate of autism spectrum disorder in children worldwide demands early detection of autism in children. Parents can seek professional help for a better prognosis of the child’s therapy when ASD is diagnosed under five years. This research study aims to develop an automated tool for diagnosing autism in children. The computer-aided diagnosis tool for ASD detection is designed and developed by a novel methodology that includes data acquisition, feature selection, and classification phases. The most deterministic features are… More >

Ollo Roland Somé^1,*, Abdoul Halim Bagué², Damien Konkobo¹, Dieudonné Hien³, Adama Dembélé³, GL Hermann Bélemlilga¹, Valentin Konségré⁴, Nayi Zongo⁵

Oncologie, Vol.24, No.2, pp. 173-184, 2022, DOI:10.32604/oncologie.2022.021250

Abstract Introduction: Breast cancer management in Sub-Saharian Africa, is faced with diagnosis and treatment challenges. This study aims to describe, breast cancers epidemiology in Bobo-Dioulasso, Burkina Faso. Patients and method: A retrospective cohort study was performed from July 01, 2015 to December 31, 2021 in the Souro Sanou university teaching hospital. Histologically confirmed breast cancer patients were included. Clinical aspect, treatment features and outcome data were collected and analyzed. Results: In study time, eight male’s cases (2%) 360 female’s cases among 368 breast cancers cases were included. The mean age was 46.6 ± 12.1 years, ranging from 15 to 90. The… More >

Hatice Jenkins¹, Siamand Hesami^1,*, Fulden Yesiltepe²

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 6167-6184, 2022, DOI:10.32604/cmc.2022.027293

Abstract This research investigates a broad range of possible factors affecting the adoption of new technology in the banking industry using adaptive LASSO and a standard logit model. The research integrated the adoption of the innovation framework and the technology acceptance theory to develop a conceptual framework for the analysis. Primary data was collected from 400 bank customers in North Cyprus. Risk perception and other customer-specific factors such as perceived risk index and negative attitude toward new technologies index were formulated for the proposed conceptual model. The findings indicated that individuals with a negative attitude toward new technology are least likely… More >

MENG FANG¹, JING GUO¹, HAIPING WANG¹, ZICHANG YANG², HAN ZHAO^1,*, QINGJIA CHI²

BIOCELL, Vol.46, No.2, pp. 401-415, 2022, DOI:10.32604/biocell.2022.016989

Abstract Hepatocellular carcinoma (HCC) is a common immunogenic malignant tumor. Although the new strategies of immunotherapy and targeted therapy have made considerable progress in the treatment of HCC, the 5-year survival rate of patients is still very low. The identification of new prognostic signatures and the exploration of the immune microenvironment are crucial to the optimization and improvement of molecular therapy strategies. We studied the potential clinical benefits of the inflammation regulator miR-93-3p and mined its target genes. Weighted gene co-expression network analysis (WGCNA), univariate and multivariate COX regression and the LASSO COX algorithm are employed to identify prognostic-related genes and… More >

Yifu Sheng¹, Jianjun Zhang^1,*, Wenwu Tan¹, Jiang Wu¹, Haijun Lin¹, Guang Sun², Peng Guo³

CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 4043-4059, 2021, DOI:10.32604/cmc.2021.019900

Abstract There are many influencing factors of fiscal revenue, and traditional forecasting methods cannot handle the feature dimensions well, which leads to serious over-fitting of the forecast results and unable to make a good estimate of the true future trend. The grey neural network model fused with Lasso regression is a comprehensive prediction model that combines the grey prediction model and the BP neural network model after dimensionality reduction using Lasso. It can reduce the dimensionality of the original data, make separate predictions for each explanatory variable, and then use neural networks to make multivariate predictions, thereby making up for the… More >

Juan Huang¹, Bifang Zhou¹, Huajun Huang^2,*, Dingwen Qing¹, Neal N. Xiong³

Intelligent Automation & Soft Computing, Vol.30, No.1, pp. 303-318, 2021, DOI:10.32604/iasc.2021.016953

Abstract There are various influencing factors in regional FDI (foreign direct investment) and it is difficult to identify the main influencing factors. For this reason, a main factor selection algorithm is proposed in this article for the main factors affecting regional FDI statistics by analyzing the regional economic characteristics and the possible influencing factors in the regional FDI. Then, an example is used to illustrate its effectiveness and its stability. Firstly, the characteristics of regional economy and the regional FDI data are introduced to develop the main factor selection algorithm based on the adaptive Lasso problem for the regional FDI and… More >

Juan Huang¹, Bifang Zhou¹, Huajun Huang^2,*, Jianjiang Liu¹, Neal N. Xiong³

CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2111-2121, 2021, DOI:10.32604/cmc.2021.016770

Abstract To overcome the deficiency of traditional mathematical statistics methods, an adaptive Lasso grey model algorithm for regional FDI (foreign direct investment) prediction is proposed in this paper, and its validity is analyzed. Firstly, the characteristics of the FDI data in six provinces of Central China are generalized, and the mixture model's constituent variables of the Lasso grey problem as well as the grey model are defined. Next, based on the influencing factors of regional FDI statistics (mean values of regional FDI and median values of regional FDI), an adaptive Lasso grey model algorithm for regional FDI was established. Then, an… More >

Mashile SP^1,2, MP Tshisikhawe¹

Phyton-International Journal of Experimental Botany, Vol.84, No.2, pp. 473-477, 2015, DOI:10.32604/phyton.2015.84.473

Abstract This paper looked at the leaf architecture characteristics of Vachellia tortilis to determine if either there is or not an effect of the tropic line on plants. Vachellia tortilis leaves were sampled along a national road (N1) in Limpopo province. Sampling points were set 10 km apart away from the Tropic of Capricon in opposite directions. Leaf morphology revealed that leaves of V. tortilis are bipinnately compound with alternate arrangement. The venation pattern of the pinnules was eucamptodromus and brochidodromous with imperfect reticulation. Areoles were imperfect and pentagonal or irregular in shape. More >

Yangyang Li¹, Xue Wang², Weiwei Fang^2,*, Feng Xue², Hao Jin¹, Yi Zhang¹, Xianwei Li³

CMC-Computers, Materials & Continua, Vol.59, No.2, pp. 493-508, 2019, DOI:10.32604/cmc.2019.05178

Abstract With the recent proliferation of Internet-of-Things (IoT), enormous amount of data are produced by wireless sensors and connected devices at the edge of network. Conventional cloud computing raises serious concerns on communication latency, bandwidth cost, and data privacy. To address these issues, edge computing has been introduced as a new paradigm that allows computation and analysis to be performed in close proximity with data sources. In this paper, we study how to conduct regression analysis when the training samples are kept private at source devices. Specifically, we consider the lasso regression model that has been widely adopted for prediction and… More >