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International Conference on Cyber Security Intelligence and Analytics, CSIA 2021

作者： Zhang, Jian Jin, Rui School of Information Engineering Liaoning Institute of Science and Engineering Jinzhou Liaoning China Computer Teaching and Research Office Jinzhou School of Modern Service Jinzhou Liaoning China

ISBN: (纸本)9783030700416

The advent of the era of big data requires high efficiency of data algorithm execution. In the data structure, the traditional bubble sort execution efficiency is low, by studying an improved bubble sort-mark bubble sort method, the number of executions can be reduced from 8 to 3, which greatly improves the execution efficiency of the algorithm. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Efficiency

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In-Situ Merge Sort Using Hand-Shaking Algorithm 2nd

In-Situ Merge Sort Using Hand-Shaking Algorithm

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2nd Big Data Analytics for Cyber-Physical System in Smart City, BDCPS 2020

作者： Zhang, Jian Jin, Rui School of Information Engineering Liaoning Institute of Science and Engineering LiaoninJinzhou China Computer Teaching and Research Office Jinzhou School of Modern Service LiaoninJinzhou China

ISBN: (纸本)9789813345737

In the present computer system, the data processing aspect, occupies the enormous processing frequency, approximately has the nearly 50% above CPU processing time is USES in the sort data. It can be seen that the data sorting algorithm has a high requirement on its own execution speed, so it is particularly important to implement a fast and good sorting algorithm. In this paper. The traditional merge sort algorithm uses two-way merge sort, which needs the same size of auxiliary space and data to be sorted, so it is necessary to improve it. The traditional merge sort method and an improved in-situ merge algorithm based on hand method are introduced, which is devoted to providing theoretical basis for improving the traditional data sort method. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Sorting

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Covid severity prediction: Who cares about the data quality?

Covid severity prediction: Who cares about the data quality?

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Frontiers of Information Technology (FIT)

作者： Teodora Nae Johannes Krabbe Faiza Allah Bukhsh Jeewanie Jayasinghe Arachchige Faizan Ahmed Mathematics and Computer Science Faculty of Electrical Engineering University of Twente Enschede The Netherlands Medische Spectrum Twente Enschede The Netherlands Department of Computer Science University of Ruhuna Matara Sri Lanka Formal Methods and Tools Group University of Twente Enschede The Netherlands

ISBN: (纸本)9798350345940

COVID-19 is an ongoing pandemic disrupting daily life and overwhelming the healthcare infrastructure. Since the outburst of the pandemic, researchers have used various techniques to predict many aspects of the disease, including mortality rate and severity. The reproducibility of this research is challenging due to varying methodologies used to collect data, data quality, vague description of methodological approach to training prediction models, over-relying on data imputation, and over-fitting. This paper focuses on these challenges and provides a short yet comprehensive review of research on COVID mortality and severity prediction. The emphasis is on the reproducibility of the results and data quality issues. To further elaborate on the issue, we report the development of severity prediction models using two data sets. CRISP-DM is used as a methodological approach. We analyze and criticize the quality of the used data sets and how they affect the performance and limitations of the trained models. We conclude this paper with comments on data quality issues, the importance of reproducibility, and suggestions to improve reproducibility.

关键词： COVID-19 Training Support vector machines Pandemics Data integrity Biological system modeling Medical services

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Contrastive Balancing Representation Learning for Heterogeneous Dose-Response Curves Estimation

arXiv

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arXiv 2024年

作者： Zhu, Minqin Wu, Anpeng Li, Haoxuan Xiong, Ruoxuan Li, Bo Yang, Xiaoqing Qin, Xuan Zhen, Peng Guo, Jiecheng Wu, Fei Kuang, Kun Department of Computer Science and Technology Zhejiang University China Mohamed bin Zayed University of Artificial Intelligence United Arab Emirates Center for Data Science Peking University China Department of Quantitative Theory and Methods Emory University United States School of Economics and Management Tsinghua University China Didi Chuxing China

Estimating the individuals' potential response to varying treatment doses is crucial for decision-making in areas such as precision medicine and management science. Most recent studies predict counterfactual outcomes by learning a covariate representation that is independent of the treatment variable. However, such independence constraints neglect much of the covariate information that is useful for counterfactual prediction, especially when the treatment variables are continuous. To tackle the above issue, in this paper, we first theoretically demonstrate the importance of the balancing and prognostic representations for unbiased estimation of the heterogeneous dose-response curves, that is, the learned representations are constrained to satisfy the conditional independence between the covariates and both of the treatment variables and the potential responses. Based on this, we propose a novel Contrastive balancing Representation learning Network using a partial distance measure, called CRNet, for estimating the heterogeneous dose-response curves without losing the continuity of treatments. Extensive experiments are conducted on synthetic and real-world datasets demonstrating that our proposal significantly outperforms previous methods. Copyright © 2024, The Authors. All rights reserved.

关键词： Decision making

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Satellite-to-aircraft quantum key distribution performance estimation with boundary layer effects

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Chinese Optics Letters 2023年第4期21卷 120-128页

作者：于惠存唐帮盈李佳豪曹跃翔周涵李斯晨熊浩西刘博石磊 Information and Navigation College Air Force Engineering UniversityXi’an 710077China College of Advanced Interdisciplinary Studies National University of Defense TechnologyChangsha 410073China College of Computer and Science National University of Defense TechnologyChangsha 410073China Teaching and Research Support Center National University of Defense TechnologyChangsha 410073China

Remarkable progress has been made in satellite-based quantum key distribution [QKD],which can effectively provide QKD service even at the intercontinental scale and construct an ultralong-distance global quantum *** there are still some places where terrestrial fiber and ground stations cannot be constructed,like harsh mountainous areas and air space above the *** the airborne platform is expected to replace the ground station and provide flexible and relay links for the large-scale integrated communication ***,the photon transmission rate would be randomly reduced,owing to the randomly distributed boundary layer that surrounds the surface of the aircraft when the flight speed is larger than0.3 *** research of airborne QKD with boundary layer effects is mainly under the air-to-ground scenario in which the aircraft is a transmitter,while the satellite-to-aircraft scenario is rarely *** this article,we propose a performance evaluation scheme of satellite-to-aircraft QKD with boundary layer effects in which the aircraft is the *** common experimental settings,the boundary layer would introduce a ~31 dB loss to the transmitted photons,decrease ~47% of the quantum communication time,and decrease ~51% of the secure key rate,which shows that the aero-optical effects caused by the boundary layer cannot be *** study can be performed in future airborne quantum communication designs.

关键词： satellite-to-aircraft quantum key distribution boundary layer aero-optical effects

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Post-processing of Graph Regularized Non-negative Matrix Factorization Algorithm for Cancer Gene Clustering

Post-processing of Graph Regularized Non-negative Matrix Fac...

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Intelligent Manufacturing, Advanced Sensing and Big Data (IMASBD), International Conference on

作者： Yong Wang Rong Zhu Experimental Teaching Center Qufu Normal University Rizhao China School of Computer Science Qufu Normal University Rizhao China

With the rapid development of DNA microarray technology, the application of informatics research methods in oncology is becoming more and more popular. Because the gene expression data extraction experiment has the characteristics of a large number of genes and complex and changeable experimental conditions, clustering technology has been introduced into the field of molecular biology to assist research and analyze gene expression data. Currently, many clustering algorithms are applied in gene expression analysis. Nevertheless, owing to the high dimensionality of gene expression data, many algorithms face the problem of low computational efficiency. The method based on the graph theory thinks of the sample of gene expression data as the point in high-dimensional space. Its low sample performance determines that the constructed matrix is small in size. Therefore, it has lower computational complexity. Therefore, the graph regularized non-negative matrices factorization (GNMF) proposed by Cai et al. has been widely used for gene clustering. However, the deficiency of the GNMF algorithm is unstable with data variation for gene clustering. In this paper, we propose post-processing of Graph Regularized Nonnegative Matrix Factorization Algorithm for Gene Clustering, called pGNMF. In the pGNMF method, we first normalize the solution of GNMF, thereby reducing the sensitivity of the traditional GNMF method to the prior selection of genes or initial conditions, and effectively improving the robustness of the algorithm. Experimental results show that the proposed algorithms outperform existing GNMF algorithms for gene clustering.

关键词：

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An intelligent hybrid approach for hepatitis disease diagnosis: Combining enhanced k-means clustering and improved ensemble learning

An intelligent hybrid approach for hepatitis disease diagnos...

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作者： Singh, Aman Mehta, Jaydip Chandrakant Anand, Divya Nath, Pinku Pandey, Babita Khamparia, Aditya Department of Computer Science and Engineering Lovely Professional University JalandharPunjab India Master in International Teaching Department Namseoul University Korea Republic of Department of Chemistry Lovely Professional University Jalandhar India Department of Computer Science and Information Technology BabaSaheb Bhimrao Ambedkar University Satellite Campus AmethiLucknow India

In real world, the automatic detection of liver disease is a challenging problem among medical practitioners. The intent of this work is to propose an intelligent hybrid approach for the diagnosis of hepatitis disease. The diagnosis is performed with the combination of k-means clustering and improved ensemble-driven learning. To avoid clinical experience and to reduce the evaluation time, ensemble learning is deployed, which constructs a set of hypotheses by using multiple learners to solve a liver disease problem. The performance analysis of the proposed integrated hybrid system is compared in terms of accuracy, true positive rate, precision, f-measure, kappa statistic, mean absolute error, and root mean squared error. Simulation results showed that the enhanced k-means clustering and improved ensemble learning with enhanced adaptive boosting, bagged decision tree, and J48 decision tree-based intelligent hybrid approach achieved better prediction outcomes than other existing individual and integrated methods. © 2020 John Wiley & Sons, Ltd

关键词： Diagnosis

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Simulation and Analysis of Back Siltation in a Navigation Channel Using MIKE 21

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Journal of Ocean University of China 2022年第4期21卷 893-902页

作者： ZHANG Kuncheng LI Qingjie ZHANG Jing SHI Hongyuan YU Jing GUO Xinchang DU Yonggang School of Marxism/Institute of Marine Development Ocean University of ChinaQingdao 266100China Guangxi Key Laboratory of Marine Environmental Science Guangxi Academy of SciencesGuangxi 530007China Yantai Marine Environment Monitoring Center Station State Oceanic AdministrationYantai 264006China Qingdao Ocean Shipping Mariners College Teaching and Research Department of Mathematics and Computer ScienceQingdao 266100China Civil Engineering College Ludong UniversityYantai 264025China College of Oceanic and Atmospheric Sciences/Institute of Marine Development Ocean University of ChinaQingdao266100China

The channel back-siltation problem has been restricting the development of channels,and its monitoring is limited by funds and natural ***,predicting the channel back-siltation situation in a timely and accurate manner is ***,a numerical simulation of the back-siltation problem in the sea area near the channel is of great significance to the maintenance of a *** this study,the back siltation of a deep-water channel in the Lanshan Port area of the Port of Rizhao after dredging is *** paper relies on the MIKE 21 software to establish the wave,tidal current,and sediment numerical models and uses measured data from two observation stations in the study area for *** this basis,taking one month as an example,the entire project channel was divided into five sections,and three observation points were set on each *** results show that the area with offshore siltation is located in the northerly direction of the artificial anti-wave *** occurred on the northern seabed in the sea a little farther from the *** occurred on the seabed surface far away from the shoreline,and with the increase in the distance from the shoreline,the amount of siltation in the south,center,and north became gradually closed,and the results can be used to guide actual engineering *** study will play a positive role in promoting the dredging project of Rizhao Lanshan Port.

关键词： channel back siltation numerical simulation back silting analysis and prediction

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Learning about Student Performance from Moodle logs in a Higher Education Context 12

Learning about Student Performance from Moodle logs in a Hig...

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12th International Conference on Virtual Campus, JICV 2022

作者： Suay, Adrian Perez Vaerenbergh, Steven Van Piles, Maria Laparra, Valero Pascual-Venteo, Ana B. Ruescas, Ana B. Fernandez-Moran, Roberto Martinez-Garcia, Marina Adsuara, Jose E. Amoros, Julia Munoz-Mari, Jordi Epifanio, Irene Fernandez-Torres, Miguel-Angel Universitat de València Dept. of Mathematics Teaching València Spain Universidad de Cantabria Dept. of Mathematics Statistics and Computer Science Santander Spain Image Processing Laboratory Universitat de València València Spain Universitat Jaume I Dept. of Mathematics Castelló Spain Universitat de València Dept. of Computer Science València Spain Universitat de València Dept. of Electronical Engineering Valencia Spain

ISBN: (数字)9781665451062

ISBN: (纸本)9781665451062

Learning Management Systems (LMS) are educational tools used to plan, implement and assess the learning-teaching procedure. LMS are continuously acquiring data from students in their learning progress when they interact with the platform. In this work, we use statistically-based approaches to learn about student performance solely using data from Moodle LMS, which is widely used along the educational institutions around the world. Using logged data from several subjects and degrees, our results indicate that the number of interactions with the LMS is a good indicator of student performance and can potentially be used as a measure to track students' learning progress. © 2022 IEEE.

关键词： Students

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Research on Brightness Compensation Algorithm for GF-3 SAR Images 7th

Research on Brightness Compensation Algorithm for GF-3 SAR I...

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7th China High-resolution Earth Observation Conference, CHREOC 2020

作者： Sun, Zengguo Yan, Xiaopeng Chen, Qianfu Chen, Weirong Key Laboratory of Modern Teaching Technology Ministry of Education Xi’an China School of Computer Science Shaanxi Normal University Xi’an China Land Satellite Remote Sensing Application Center MNR Beijing China China Centre for Resources Satellite Data and Application Beijing China

ISBN: (纸本)9789811657344

GF-3, the first C-Band full-polarimetric synthetic aperture radar (SAR) satellite with a space resolution up to 1 m, has multiple strip and scan imaging modes. In this paper, a brightness compensation model is proposed to correct the unbalanced radiation image of GF-3 satellite in some areas based on mathematical morphology principle, SAR imaging model, and histogram mapping model, so that the image radiation is relatively consistent and has moderate contrast. The proposed algorithm is tested on the GF-3 SAR image with radiation difference in Taklimakan desert area of Xinjiang, and is compared with the MASK dodging algorithm in terms of brightness mean, standard deviation, information entropy, and average gradient. Results of brightness compensation show that, the proposed algorithm makes the radiation differences within images smaller, and the image quality is obviously improved, which provides a non-radiation difference image for subsequent applications. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Mathematical morphology

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