News Release

Latest artificial intelligence research from China in Big Data

Peer-Reviewed Publication

Mary Ann Liebert, Inc./Genetic Engineering News

Big Data

image: Big Data, published quarterly online with open access options and in print, facilitates and supports the efforts of researchers, analysts, statisticians, business leaders, and policymakers to improve operations, profitability, and communications within their organizations. view more 

Credit: (c) 2019 Mary Ann Liebert, Inc., publishers

New Rochelle, June 18, 2019--China is among the leaders in the rapidly advancing artificial intelligence field, and its broad range of cutting-edge research expertise is on display in this special issue on "Artificial Intelligence in China" of Big Data, a peer-reviewed journal from Mary Ann Liebert, Inc., publishers. Click here to read the special issue free on the Big Data website through July 18, 2019.

Co-Guest Editors Weiping Zhang, PhD, Zheijiang University (China) and Mohit Kumar, PhD, Rostock University (Germany) organized the unique and timely collection of articles in this special issue.

Featured in the special issue is the article entitled "Abnormal Data Region Discrimination and Cross-Monitoring Points Historical Correlation Repair of Water Intake Data," coauthored by Huifeng Xue, Xi'an University of Technology and China Academy of Aerospace System Scientific and Engineering (Beijing), Qiaoyun Liu, Xi'an University of Technology, Junjie Hou, China Academy of Aerospace System Scientific and Engineering, and Yi Wan, Ministry of Water Resources (Beijing). The researchers analyze the characteristics of abnormal data distribution and show how the data from current monitoring points do not maximally correlate with historical data from corresponding points. They use sample data from recent years to demonstrate that application of the Abnormal Data Region Discrimination algorithm and the Cross Monitoring-Points Historical Correlation Repair method can correctly identify the abnormal data region and repair the abnormal data.

Yao Yu and Junhui Zhao, East China Jiaotong University (Nanchang) and Wu Lenan, Southeast University (Nanjing) collaborated on the article entitled "Multiple Targets Tracking with Big Data-Based Measurement for Extended Binary Phase Shift Keying Transceiver". The researchers proposed using Doppler measurements of target velocity in combination with target range information to improve the ability to detect multiple targets accurately in a noisy environment with an extended-binary phase shift keying (EBSPK) transmit-receive system - a high-resolution radar tracking system. In a simulated experiment, they showed significant enhancement in the tracking performance of the big Doppler data association method. The target velocity measurements support the likelihood of the EBPSK transceiver-generated information, helping to distinguish actual targets from phony targets or clutter measurements.

Big Data Editor-in-Chief Zoran Obradovic, PhD, Carnell Professor of Data Analytics, Temple University, (Philadelphia, PA) states: "China's spending on research has increased 8-fold since 2000. The overall results of this increased research activity are evident in many fields and are particularly impressive in the area of Artificial Intelligence and Big Data. This special issue provides an excellent opportunity to read about a range of ongoing AI-related developments across multiple big data-related fields in China."

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About the Journal

Big Data, published quarterly online with open access options and in print, facilitates and supports the efforts of researchers, analysts, statisticians, business leaders, and policymakers to improve operations, profitability, and communications within their organizations. Spanning a broad array of disciplines focusing on novel big data technologies, policies, and innovations, the peer-reviewed journal brings together the community to address the challenges and discover new breakthroughs and trends living within this information. Complete tables of content and a sample issue may be viewed on the Big Data website.

About the Publisher

Mary Ann Liebert, Inc., publishers is a privately held, fully integrated media company known for establishing authoritative medical and biomedical peer-reviewed journals, including OMICS: A Journal of Integrative Biology, Journal of Computational Biology, New Space, and 3D Printing and Additive Manufacturing. Its biotechnology trade magazine, GEN (Genetic Engineering & Biotechnology News), was the first in its field and is today the industry's most widely read publication worldwide. A complete list of the firm's more than 80 journals, newsmagazines, and books is available on the Mary Ann Liebert, Inc., publishers website.


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