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Yong Shi 0002
Person information
- affiliation: Kennesaw State University, Department of Computer Science, Kennesaw, GA, USA
- affiliation (PhD 2006): State University of New York at Buffalo, Department of Computer Science and Engineering, Buffalo, NY, USA
Other persons with the same name
- Yong Shi — disambiguation page
- Yong Shi 0001
— University of Chinese Academy of Sciences, School of Economics and Management, Beijing, China (and 3 more)
- Yong Shi 0003
— Shaanxi University of Science & Technology, School of Electrical and Control Engineering, Xi'an, China
- Yong Shi 0004
— Huainan Normal University, School of Computer Science, Huainan, China
- Yong Shi 0005
— China University of Geosciences, School of Economics and Management, Wuhan, China (and 1 more)
- Yong Shi 0006
— Heilongjiang University, School of Mechanical and Electrical Engineering, Harbin, China
- Yong Shi 0007
— Shanghai University of Sport, Department of Economics and Management, Shanghai, China (and 1 more)
- Yong Shi 0008
— Changzhou Institute of Technology, School of Computer Information and Engineering, Changzhou, China (and 1 more)
- Yong Shi 0009 — Shanghai Jiao Tong University, Department of Electronic Engineering, Shanghai, China
- Yong Shi 0010 — Huawei Technologies, Trustworthiness Theory, Technology & Engineering Lab, Shenzhen, China
- Yong Shi 0011 — Xi'an Jiaotong University, Electronic and Information Engineering Department, Shaanxi, China
- Yong Shi 0012
— Microsoft Bing, Beijing, China
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Journal Articles
- 2021
- [j4]P. Karuppusmay, Fuqian Shi, Yong Shi:
Special Issue: Capsule Networks and Imaging Science (CNIS). Neural Process. Lett. 53(4): 2381-2383 (2021) - 2011
- [j3]Yong Shi:
Finding Clusters and Outliers for Data Sets with Constraints. J. Intell. Syst. 20(1): 3-14 (2011) - [j2]Yong Shi, Li Zhang:
COID: A cluster-outlier iterative detection approach to multi-dimensional data analysis. Knowl. Inf. Syst. 28(3): 709-733 (2011) - 2010
- [j1]Yong Shi:
A Dimension Reduction Approach Using Shrinking for Multi-Dimensional Data Analysis. Int. J. Intell. Inf. Process. 1(2): 86-98 (2010)
Conference and Workshop Papers
- 2024
- [c56]Long Vu
, Kun Suo
, Md. Romyull Islam
, Nobel Dhar
, Tu N. Nguyen
, Selena He
, Yong Shi
:
Living on the Electric Vehicle and Cloud Era: A Study of Cyber Vulnerabilities, Potential Impacts, and Possible Strategies. ACM Southeast Regional Conference 2024: 18-26 - [c55]Chunlan Gao
, Yong Shi
:
Prediction Performance Analysis for ML Models Based on Impacts of Data Imbalance and Bias. ACM Southeast Regional Conference 2024: 235-240 - 2023
- [c54]Tarun Potluri, Yong Shi, Hossain Shahriar, Dan Chia-Tien Lo, Reza M. Parizi, Hongmei Chi
, Kai Qian:
Secure Software Development in Google Colab. AIIoT 2023: 398-402 - [c53]Dhanunjai Bandi, Yong Shi, Hossain Shahriar, Dan C. Lo, Kun Suo, Hongmei Chi
, Kai Qian:
Quantum Machine Learning for Security Data Analysis. AIIoT 2023: 460-465 - [c52]Joshua Priest, Cameron Cooper, Savvy Lovell, Yong Shi, Dan Lo:
Design and Implementation of an ERC-20 Smart Contract on the Ethereum Blockchain. IEEE Big Data 2023: 2334-2338 - [c51]Dan Chia-Tien Lo, Bobin Deng, Yong Shi:
Deep Machine Learning on Segmenting and Classifying Crop Images Taken by Unmanned Aerial Vehicle. IEEE Big Data 2023: 3470-3478 - [c50]William Downing, Dalton Harvey, Dennis Wagura, Yong Shi:
Blockchain Development in Colab: An Ethereum-Based Bicycle Registry System. CCWC 2023: 134-139 - [c49]Horatiu Lupsan, Remaz Ahmed, Yong Shi:
Cybersecurity in Malware Research. CCWC 2023: 593-597 - [c48]Yong Shi, Nazmus Sakib, Hossain Shahriar, Dan Lo, Hongmei Chi, Kai Qian:
AI-Assisted Security: A Step towards Reimagining Software Development for a Safer Future. COMPSAC 2023: 991-992 - [c47]Eric Cooper, Eric Weese, Alex Fortson, Dan Lo, Yong Shi:
Cyber Security in Blockchain. DSC 2023: 1-11 - [c46]Yong Shi, Hossain Shahriar, Dan C. Lo, Kai Qian, Hongmei Chi:
Collaborative and Active Learning with Portable Online Hands-on Labware for Blockchain Development. SIGCSE (2) 2023: 1307 - 2022
- [c45]Chunlan Gao, Yanqing Zhang, Dan Lo, Yong Shi, Jian Huang:
Improving the Machine Learning Prediction Accuracy with Clustering Discretization. CCWC 2022: 513-517 - [c44]Chulan Gao, Hossain Shahriar, Dan Lo, Yong Shi, Kai Qian:
Improving the Prediction Accuracy with Feature Selection for Ransomware Detection. COMPSAC 2022: 424-425 - [c43]Dan Chia-Tien Lo, Kai Qian, Yong Shi, Hossain Shahriar, Chung Ng:
Broaden Multidisciplinary Data Science Research by an Innovative Cyberinfrastructure Platform. COMPSAC 2022: 428-429 - [c42]Tyler Holmes, Charlie McLarty, Yong Shi, Patrick Bobbie, Kun Suo:
Energy Efficiency on Edge Computing: Challenges and Vision. IPCCC 2022: 1-6 - [c41]Kun Suo, Tu N. Nguyen, Yong Shi, Jing Selena He, Chih-Cheng Hung:
Keep Clear of the Edges : An Empirical Study of Artificial Intelligence Workload Performance and Resource Footprint on Edge Devices. IPCCC 2022: 7-16 - 2021
- [c40]Kun Suo, Yong Shi, Ahyoung Lee, Sabur Baidya
:
Characterizing networking performance and interrupt overhead of container overlay networks. ACM Southeast Conference 2021: 93-99 - [c39]Justin Duchatellier, Tyler Holmes, Kun Suo, Yong Shi:
An empirical study of thermal attacks on edge platforms. ACM Southeast Conference 2021: 175-179 - [c38]Kousalya Banka, Kun Suo, Yong Shi, Sabur Baidya
:
A study of state-of-the-art energy saving on edges. ACM Southeast Conference 2021: 224-228 - [c37]Divya Pramasani Mohandoss, Yong Shi, Kun Suo:
Outlier Prediction Using Random Forest Classifier. CCWC 2021: 27-33 - [c36]Yong Shi, Kun Suo, Jameson Hodge, Divya Pramasani Mohandoss, Steven Kemp:
Towards Optimizing Task Scheduling Process in Cloud Environment. CCWC 2021: 81-87 - [c35]Kun Suo, Yong Shi, Chih-Cheng Hung, Patrick Bobbie:
Quantifying context switch overhead of artificial intelligence workloads on the cloud and edges. SAC 2021: 1182-1189 - 2020
- [c34]Nusrat Asrafi, Dan Chia-Tien Lo, Reza M. Parizi, Yong Shi, Yu-Wen Chen:
Comparing Performance of Malware Classification on Automated Stacking. ACM Southeast Regional Conference 2020: 307-308 - [c33]Daniel Brown, Yong Shi:
A Distributed Density-Grid Clustering Algorithm for Multi-Dimensional Data. CCWC 2020: 1-8 - [c32]Arialdis Japa, Yong Shi:
Parallelizing the Bounded K-Nearest Neighbors Algorithm for Distributed Computing Systems. CCWC 2020: 38-45 - [c31]Kun Suo, Yong Shi, Xiaohua Xu, Dazhao Cheng, Wei Chen:
Tackling Cold Start in Serverless Computing with Container Runtime Reusing. NAI@SIGCOMM 2020: 54-55 - [c30]Madhuri Gurunathrao Desai, Yong Shi, Kun Suo:
IoT Bonet and Network Intrusion Detection using Dimensionality Reduction and Supervised Machine Learning. UEMCON 2020: 316-322 - 2019
- [c29]Daniel Brown, Arialdis Japa, Yong Shi:
An Attempt at Improving Density-based Clustering Algorithms. ACM Southeast Regional Conference 2019: 172-175 - [c28]Zhengwu Sun, Dan Chia-Tien Lo, Yong Shi:
Big Data Analysis on Social Networking. IEEE BigData 2019: 6220-6222 - [c27]Daniel Brown, Arialdis Japa, Yong Shi:
A Fast Density-Grid Based Clustering Method. CCWC 2019: 48-54 - 2018
- [c26]Yong Shi:
An attempt to analyze data distribution for abnormal behaviors. CCWC 2018: 275-280 - 2017
- [c25]Boyu Hou, Yong Shi, Kai Qian, Lixin Tao:
Towards Analyzing MongoDB NoSQL Security and Designing Injection Defense Solution. BigDataSecurity/HPSC/IDS 2017: 90-95 - [c24]Kai Qian, Yong Shi, Lixin Tao, Ying Qian:
Hands-On Learning for Computer Network Security with Mobile Devices. ICCCN 2017: 1-6 - 2016
- [c23]Tianda Yang, Kai Qian, Dan Chia-Tien Lo, Ying Xie, Yong Shi, Lixin Tao:
Improve the Prediction Accuracy of Naïve Bayes Classifier with Association Rule Mining. BigDataSecurity/HPSC/IDS 2016: 129-133 - [c22]Yong Shi, Dan Chia-Tien Lo, Kai Qian:
Teaching Secure Cloud Computing Concepts with Open Source CloudSim Environment. COMPSAC Workshops 2016: 247-252 - [c21]Boyu Hou, Kai Qian, Lei Li, Yong Shi, Lixin Tao, Jigang Liu:
MongoDB NoSQL Injection Analysis and Detection. CSCloud 2016: 75-78 - [c20]Lei Li, Kai Qian, Ragib Hasan
, Qian Chen, Dalei Wu
, Yong Shi:
An Open and Portable Platform for Learning Data Security in Mobile Cloud Computing. SIGITE 2016: 108 - [c19]Yong Shi, Wanqing You, Kai Qian, Prabir Bhattacharya, Ying Qian:
A hybrid analysis for mobile security threat detection. UEMCON 2016: 1-7 - 2015
- [c18]Yong Shi, Sunpil Kim:
An Attempt to Find Information for Multi-dimensional Data Sets. ITNG 2015: 763-764 - 2013
- [c17]Yong Shi, Brian Graham:
Similarity Search Problem Research on Multi-dimensional Data Sets. ITNG 2013: 573-577 - 2012
- [c16]Yong Shi, Brian Graham:
A Similarity Search Approach to Solving the Multi-query Problems. ACIS-ICIS 2012: 237-242 - [c15]Yong Shi, Brian Graham:
An Approach to Reshaping Clusters for Nearest Neighbor Search. IDEAL 2012: 60-67 - 2010
- [c14]Yong Shi:
Towards improving a similarity search approach. ACM Southeast Regional Conference 2010: 49 - [c13]Yong Shi:
Towards improving subspace data analysis. ACM Southeast Regional Conference 2010: 63 - [c12]Yong Shi:
Obstacle clustering and outlier detection. ACM Southeast Regional Conference 2010: 88 - [c11]Yong Shi:
Inter-dimensional fuzzy clustering. ACM Southeast Regional Conference 2010: 89 - [c10]Yong Shi, Tyler Kling:
Improving the Ability of Mining for Multi-dimensional Data. FGIT-DTA/BSBT 2010: 291-298 - 2009
- [c9]Yong Shi:
Towards solving similarity search problems using fuzzy concept for multi-dimensional data. ACM Southeast Regional Conference 2009 - [c8]Yong Shi:
A dynamic insertion approach for multi-dimensional data using index structures. ACM Southeast Regional Conference 2009 - 2008
- [c7]Yong Shi:
SubCOID: an attempt to explore cluster-outlier iterative detection approach to multi-dimensional data analysis in subspace. ACM Southeast Regional Conference 2008: 132-135 - [c6]Yong Shi:
FuzzyShrinking: improving shrinking-based data mining algorithms using fuzzy concept for multi-dimensional data. ACM Southeast Regional Conference 2008: 260-263 - [c5]Yong Shi:
Detecting Clusters and Outliers for Multi-dimensional Data. MUE 2008: 429-432 - 2005
- [c4]Yong Shi, Aidong Zhang:
Towards Exploring Interactive Relationship between Clusters and Outliers in Multi-Dimensional Data Analysis. ICDE 2005: 518-519 - 2004
- [c3]Yong Shi, Aidong Zhang:
A Shrinking-Based Dimension Reduction Approach for Multi-Dimensional Data Analysis. SSDBM 2004: 427-428 - 2003
- [c2]Yong Shi, Yuqing Song, Aidong Zhang:
A Shrinking-Based Approach for Multi-Dimensional Data Analysis. VLDB 2003: 440-451 - 2002
- [c1]Li Zhang, Chun Tang, Yong Shi, Yuqing Song, Aidong Zhang, Murali Ramanathan:
VizCluster: An Interactive Visualization Approach to Cluster Analysis and Its Application on Microarray Data. SDM 2002: 19-40
Coauthor Index
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