Epidemiological, molecular, and evolutionary characteristics of G1P[8] rotavirus in China on the eve of RotaTeq application by Rui Peng, Rui Peng, Mengxuan Wang, Saleha Shahar, Guangping Xiong, Qing Zhang, Lili Pang, Hong Wang, Xiangyu Kong, Dandi Li, Zhaojun Duan

Get full text

Analysis of satellite big data requirements in numerical weather prediction by Hequn YANG, Xiaofeng WANG, Yanqing GAO, Yiwen LU, Bingxin MA, Xinyao WANG

“…Multi cooperative satellites can provide multi spectral, multi temporal, multi factor, multi scale and multi-level remote sensing data, which is rich in valuable information for numerical weather prediction (NWP).In order to support earth system seamless fine gridded forecasting service in the future, the application status of satellite observation big data was discussed for numerical weather prediction from the aspects of detection variables, time density, spatial coverage, horizontal and vertical resolution, as well as accuracy and timeliness.At the same time, in order to make satellite big data be highly tolerant with NWP, the challenges and prospects were summarized, such as multi-satellite integrated and consistent processing, all-weather, coupled data assimilation methods, deep integration with artificial intelligence, and interaction between satellite observation and prediction.…”
Get full text

An Exploration of the Viral Coverage of Mosquito Viromes Using Meta-Viromic Sequencing: A Systematic Review and Meta-Analysis by Shenglin Chen, Yuan Fang, Ryosuke Fujita, Emad I. M. Khater, Yuanyuan Li, Wenya Wang, Peijun Qian, Lulu Huang, Zhaoyu Guo, Yi Zhang, Shizhu Li

Get full text

Image reconstruction of Arctic sea ice using SWIM data at small incidence angles by Wenlong Bi, Hui Yu, Xi Zhang, Ran Yan, Ying Xu, Maohua Guo, Ning Wang, Yinghui Li, Yifan Zhang, Yanting Lu, Xinyi Bi, Meijie Liu

Get full text

SVM classifier for telecom user arrears based on boundary samples-based under-sampling approaches by Chuangchuang LI, Guangyue LU, Hanglong WANG

“…Telecom users’ arrears forecasting is a classification problem of unbalanced data set.To deal with the problem that the traditional SVM on the unbalanced date set had a low detection accuracy of minority class,a novel method was proposed.Based on the fact that the position of classification plane was determined by the boundary samples,the proposed method was implemented via removing some of samples closed to the classification plane to avoid the deficiency of the traditional SVM algorithm.Finally,the proposed method was compared with other approaches on unbalanced data sets.The simulation results show that the proposed method can not only increase the detection accuracy of minority but also improve the overall classification performance.…”
Get full text

China’s efforts on the CSEP and a retrospective case by Huaizhong Yu, Jingxue Zhang, Yue Liu, Yongxian Zhang, Chieh-Hung Chen, Rui Yan, Gang Li, Zeping Li, Yuchuan Ma, Zhengyi Yuan, Wen Yang, Donghui Jia, Binbin Zhao

Get full text

Advancing smart communities with a deep learning framework for sustainable resource management. by Yongyan Zhao

“…The models outperformed baseline methods, with LSTMs achieving an MAE of 1.8 for water demand prediction and autoencoders detecting anomalies with an F1-score of 95.5%.…”
Get full text

Malware prediction technique based on program gene by Da XIAO, Bohan LIU, Baojiang CUI, Xiaochen WANG, Suoxing ZHANG

“…With the development of Internet technology,malicious programs have risen explosively.In the face of executable files without source,the current mainstream malware detection uses feature detection based on similarity,with lack of analysis of malicious sources.To resolve this status,the definition of program gene was raised,a generic method of extracting program gene was designed,and a malicious program prediction method was proposed based on program gene.Utilizing machine learning and deep-learning algorithms,the forecasting system has good prediction ability,with the accuracy rate of 99.3% in the deep-learning model,which validates the role of program gene theory in the field of malicious program analysis.…”
Get full text

Learning to Learn Sequential Network Attacks Using Hidden Markov Models by Timothy Chadza, Konstantinos G. Kyriakopoulos, Sangarapillai Lambotharan

“…Baum-Welch (BW), Viterbi training, gradient descent, differential evolution (DE) and simulated annealing, are deployed for the detection of attack stages in the network traffic, as well as, forecasting both the next most probable attack stage and its method of manifestation. …”
Get full text

Spatiotemporal prevalence of COVID-19 and SARS-CoV-2 variants in Africa by Li-Ping Gao, Can-Jun Zheng, Ting-Ting Tian, Alie Brima Tia, Michael K. Abdulai, Kang Xiao, Cao Chen, Dong-Lin Liang, Qi Shi, Zhi-Guo Liu, Xiao-Ping Dong, Xiao-Ping Dong

Get full text

Gut microbiota and plasma metabolites in pregnant mothers and infant atopic dermatitis: A multi-omics studyKey Message by Bingqian Du, MA.Sc, Aga Shama, BA.Sc, Yi Zhang, BA.Sc, Baolan Chen, MA.Sc, Yongqi Bu, BA.Sc, Pei-an Chen, MA.Sc, Chuzhi Lin, BA.Sc, Jie Liu, MA.Sc, Juan Zheng, MA.Sc, Zhenjun Li, MD, PhD, Qingsong Chen, PhD, Yu Sun, PhD, Xi Fu, PhD

Get full text

A Systematic Literature Review of Concept Drift Mitigation in Time-Series Applications by Mujaheed Abdullahi, Hitham Alhussian, Norshakirah Aziz, Said Jadid Abdulkadir, Yahia Baashar, Abdussalam Ahmed Alashhab, Afroza Afrin

“…This is possible because of their high detection accuracy and effective memory. Moreover, this SLR presents a roadmap for detecting CDs using Artificial Intelligence (AI)-based learners, along with a comparative analysis of well-known baseline methods. …”
Get full text

A Comparative Analysis of the Effectiveness of Multiple Models for Predicting Heart Failure using Data Mining by Ahmed Sami Jaddoa, Juliet Kadum, Amaal Kadum

“…In order to preserve lives, early detection regarding such disease is essential. One of the quickest, practical, and affordable methods of disease detection is Data Mining DM, an artificial intelligence AI technology. …”
Get full text

Integrating high dimensional quadratic regression with penalties based predictive modeling for hydro power plants accurate tariff prediction by Ritesh Dash, Anupa Sinha, Abinash Mahapatro, Bhabasis Mohapatra, Binod Kumar Sahu

“…Graphical and numerical evaluations confirm the model’s accuracy and suitability for spot market forecasting within hydro-DISCOM integration. The study concludes with recommendations for real time deployment and extension into hybrid intelligent forecasting framework. …”
Get full text

Machine Learning-Based Grasshopper Species Classification using Neutrosophic Completed Local Binary Pattern by Mustafa İlçin, Nuh Alpaslan

“…However, this is a challenging process. Grasshopper detection methods are being developed using traditional forecasting methods by expert entomologists. …”
Get full text

Failure Mode and Effect Analysis on the Impact of Zakat on the Local Economy by Darmawan Darmawan, Siti Alfajriyani

“…The Failure Mode and Effect Analysis (FMEA) method was used to identify high-risk dominant factors. …”
Get full text

A crosslinked eutectogel for ultrasensitive pressure and temperature monitoring from nostril airflow by Tao Liu, Qinan Wu, Huansheng Liu, Xiyang Zhao, Xin Yi, Jing Liu, Zhenzhen Nong, Bingpu Zhou, Qingwen Wang, Zhenzhen Liu

“…However, the developed methods only rely on single stimulus sensing for nostril airflow, which is extremely susceptible to interference in the complex environment, and severely affects the accuracy of detection results. …”
Get full text

Unleashing the power of intelligence: revolutionizing malaria outbreak preparedness with an advanced warning system in Benin, West Africa by Gouvidé Jean Gbaguidi, Nikita Topanou, Walter Leal Filho, Komi Agboka, Guillaume K. Ketoh

“…SVM regression algorithm forecasts 80% prediction rate for malaria incidence. …”
Get full text

Isolation and characterization of a novel coltivirus from Haemaphysalis concinna ticks in Northeastern China by Yu-Hong Yang, Ji-Xu Li, Rui-Chen Wang, Qi-Kai Yin, Shi-Hong Fu, Kai Nie, Qian-Qian Cui, Song-Tao Xu, Qiang Wei, Fan Li, Xing-Zhou Li, Huan-Yu Wang

Get full text

Advancements in the application of artificial intelligence in the field of colorectal cancer by Mengying Zhu, Mengying Zhu, Zhenzhu Zhai, Yue Wang, Fang Chen, Ruibin Liu, Ruibin Liu, Xiaoquan Yang, Guohua Zhao

“…This poses a significant threat to global public health. Early screening methods, such as fecal occult blood tests, colonoscopies, and imaging techniques, are crucial for detecting early lesions and enabling timely intervention before cancer becomes invasive. …”
Get full text