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SSRN 2023年

作者： Gu, Haoting He, Guangxin Li, Zhongliang Zhang, Ping Cheng, Yuexuan Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters Nanjing University of Information Science and Technology Nanjing210044 China Guangzhou Institute of Tropical Marine Meteorology China Meteorological Administration Guangzhou510080 China Key Laboratory of Meteorology and Ecological Environment of Hebei Province Hebei Provincial Institute of Meteorological Sciences Shijiazhuang050021 China College of Computer and Software Nanjing Vocational University of Industry Technology Nanjing210046 China School of Information Management & Engineering Shanghai University of Finance and Economics Shanghai Shanghai200433 China

This study employs ground observation data and hourly ERA5 data from 1980 to 2020, utilizing methods such as trend analysis and M-K tests, to explore the spatiotemporal evolution characteristics and difference analysis of daily-scale and hourly-scale extreme precipitation in the Middle and Lower Yangtze River Basin(MLYRB). The research finds that:(1) The daily precipitation amount and intensity are on an upward trend, while the frequency and the proportional area of occurrence of heavy rain are rapidly declining, indicating a concentration trend in daily-scale extreme precipitation. (2) The intensity of extreme hourly precipitation increases from southwest to northeast, potentially related to local topography, with more vigorous precipitation intensity in the plains than in the mountainous areas. (3) The characteristics of extreme rainstorms at different scales are heterogeneous, primarily exhibiting less frequent occurrences, dispersed occurrences, and increased intensity. The harm is most severe in summer least in winter, while frequent spring precipitation elevates the risk of spring floods. (4) The frequency and intensity of extreme hourly rainstorms show a reverse trend between 19:00~21:00, and the probability of occurrence of severe hourly rainstorms is higher in the early night. (5) The peak value trend of extreme hourly rainstorm amounts is weakly declining, and its frequency of occurrence is rapidly decreasing, but all three-time intervals, 1:00-7:00, 8:00-19:00, and 20:00-24:00, show an upward trend. (6) The basin is dominated by post-type precipitation, indicating a very high probability that the maximum value of extreme hourly precipitation occurs in the latter half of the process. This study offers new insights into understanding the spatiotemporal characteristics and possible causes of extreme precipitation in the MLYRB, providing beneficial enlightenment for related risk assessment and response strategies. © 2023, The Authors. All rights reserved.

关键词： Topography

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Fault detection capabilities of combinatorial testing and random testing for Boolean-specifications

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International Journal of Performability engineering 2019年第11期15卷 2952-2961页

作者： Wang, Ziyuan Li, Yang Gu, Xueqing Zheng, Xiaojia Yu, Min School of Computer Science and Technology Nanjing University of Posts and Telecommunications Nanjing210023 China Software Testing Engineering Laboratory of Jiangsu Province Nanjing211169 China Tongda College Nanjing University of Posts and Telecommunications Yangzhou225127 China

The problem of fault detection capability of combinatorial testing has drawn a lot of attention. People conducted many experiments on different subjects to compare fault detection capabilities of combinatorial testing and random testing. However, previous confusing results can hardly answer the question of whether combinatorial test suite detects more faults than random test suite. To answer this question more trustfully, we conducted an experiment on general-form Boolean-specifications. In our experiment, fault detection frequencies and fault detection ratios in combinatorial testing, where test suites are generated by some classic combinatorial test generation algorithms, are collected by the repeated running of combinatorial testing. Moreover, fault detection probabilities in random testing are obtained by theoretical analysis. By comparing fault detection frequencies, ratios, and probabilities, our experimental results suggest that combinatorial testing has a little advantage of fault detection capability over random testing. © 2019 Totem Publisher, Inc. All rights reserved.

关键词： Fault detection

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Conceptual Design of a Generic Nodal Abstraction (GNA) for a Human-Agent Collaboration Systems

Conceptual Design of a Generic Nodal Abstraction (GNA) for a...

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International Conference on Green engineering Technology and Applied Computing 2019, IConGETech2 019 and International Conference on Applied Computing 2019, ICAC 2019

作者： Abbas Mohammed, Khudhair Abdul Majid, Mazlina Sharifuddin Ahmad, Mohd Faculty of Computer Systems and Software Engineering University Malaysia Pahang Pahang Kuantan Malaysia College of Computer Science and Information Technology Universiti Tenaga Nasional Selangor Kajang43000 Malaysia

The issues of modelling software agents in collaborative systems present some problems and difficulties caused by the diversity of tasks and the procedures attached to them. Consequently, such diversity poses a critical challenge to implement scheduled tasks. In this paper, we propose collaborative human-agent system in which a software agent collaborates and cooperates with its human counterpart in several job positions of an organization. The goal of the GNA approach is to improve collaboration between humans when performing tasks within a workflow process. The GNA is built based on the concept of a node which comprises of a human, agents, and their shared functions. This concept espouses the notion that agents could be deployed to assist humans in many common workflow processes and to handle mundane tasks. Furthermore, a multi-agent system is advocated as an application or platform for managing distributed data. Specifically, this paper describes a conceptual design of a generic approach based on the notion of nodes to construct a Generic Nodal Abstraction (GNA) approach that is deployable as a modeling and simulation platform for organizational processes. © 2019 Published under licence by IOP Publishing Ltd.

关键词： Multi agent systems

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A hybrid steganography framework using DCT and GAN for secure data communication in the big data era

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Scientific reports 2025年第1期15卷 19630页

作者： Kaleem Razzaq Malik Muhammad Sajid Ahmad Almogren Tauqeer Safdar Malik Ali Haider Khan Ayman Altameem Ateeq Ur Rehman Seada Hussen Department of Computer Science Air University Islamabad 44230 Pakistan. Chair of Cyber Security Department of Computer Science College of Computer and Information Sciences King Saud University Riyadh 11633 Saudi Arabia. ahalmogren@ksu.edu.sa. Department of Information and Communication Technology Bahauddin Zakariya University Multan 60800 Punjab Pakistan. Department of Software Engineering Faculty of Computer Science Lahore Garrison University Lahore 54000 Punjab Pakistan. College of Computer Science Beijing University of Technology Beijing 100124 China. Chair of Cyber Security Department of Computer Science College of Computer and Information Sciences King Saud University Riyadh 11633 Saudi Arabia. School of Computing Gachon University Seongnam-si 13120 Republic of Korea. 202411144@gachon.ac.kr. Department of Electrical Power Adama Science and Technology University Adama 1888 Ethiopia. seada.hussen@aastu.edu.et.

The growth of the internet and big data has spurred the demand for more extensive information hoarding to store and distribute information. In today's digital era, ensuring the security of data transmission is paramount. Advancements in digital technology have facilitated the proliferation of high-resolution graphics over the Internet, raising security concerns and enabling unauthorized access to sensitive data. Researchers have increasingly explored steganography as a reliable method for secure communication because it plays a crucial role in concealing and safeguarding sensitive information. This study introduces a novel and comprehensive steganography framework using the discrete cosine transform (DCT) and the deep learning algorithm, generative adversarial network. By leveraging deep learning techniques in both spatial and frequency domains, the proposed hybrid architecture offers a robust solution for applications requiring high levels of data integrity and security. While conventional steganography methods are typically classified into spatial and transform domains, extensive research and analysis demonstrate that the hybrid approach surpasses individual techniques in performance. The experimental results validate the effectiveness of the proposed steganography approach, showcasing superior visual image quality with a mean square error (MSE) of 93.30%, peak signal-to-noise ratio (PSNR) of 58.27%, root mean squared error (RMSE) of 96.10%, and structural similarity index measure (SSIM) of 94.20%, in comparison to existing leading methodologies. The proposed model achieved reconstruction accuracies of 96.2% using Xu Net and 95.7% with SR Net. By combining DCT with deep learning algorithms, the proposed approach overcomes the limitations of spatial domain methods, offering a more flexible and effective steganography solution. Furthermore, simulation results confirm that the proposed technique outperforms state-of-the-art methods across key performance metrics, inc

关键词： DCT Deep learning GAN Spatial domain Steganography

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Approximate Cartesian Tree Matching with One Difference

arXiv

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arXiv 2025年

作者： Auvray, Bastien David, Julien Ghazawi, Samah Groult, Richard Landau, Gad M. Lecroq, Thierry Univ Rouen Normandie INSA Rouen Normandie Université Le Havre Normandie Normandie Univ LITIS UR 4108 Rouen76000 France Normandie University UNICAEN ENSICAEN CNRS GREYC Caen France CNRS NormaSTIC FR 3638 Caen Le Havre Rouen France Department of Software Engineering Braude College of Engineering Karmiel Israel Department of Computer Science University of Haifa Haifa Israel Department of Computer Science and Engineering NYU Tandon New York United States

Cartesian tree pattern matching consists of finding all the factors of a text that have the same Cartesian tree than a given pattern. There already exist theoretical and practical solutions for the exact case. In this paper, we propose the first algorithms for solving approximate Cartesian tree pattern matching with one difference given a pattern of length m and a text of length n. We present a generic algorithm that find all the factors of the text that have the same Cartesian tree of the pattern with one difference, using different notions of differences. We show that this algorithm has a O(nm) worst-case complexity and that, for several random models, the algorithm has a linear average-case complexity. We also present an automaton based algorithm, adapting [22], that can be generalized to deal with more than one difference. © 2025, CC BY.

关键词： Approximation algorithms

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Dense networks with scale-free feature

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Physical Review E 2020年第5期101卷 052317-052317页

作者： Fei Ma Xiaomin Wang Ping Wang Xudong Luo School of Electronics Engineering and Computer Science Peking University Beijing 100871 China National Engineering Research Center for Software Engineering Peking University Beijing 100871 China School of Software and Microelectronics Peking University Beijing 102600 China and Key Laboratory of High Confidence Software Technologies (PKU) Ministry of Education Beijing 100871 China College of Mathematics and Statistics Northwest Normal University Lanzhou 730070 China

While previous works have shown that an overwhelming number of scale-free networks are sparse, there still exist some real-world networks including social networks, urban networks, information networks, which are by observation dense. In this paper, we propose a framework for generating scale-free graphs with a dense feature using two simple yet helpful operations: first-order subdivision and line operation. From the theoretical point of view, our method can be used not only to produce desired scale-free graphs with a density feature, i.e., a power-law exponent γ falling into the interval 1<γ≤2, but also to establish many other unexpected networked models, for instance, power-law models having a large diameter. In addition, the networked models generated upon our framework show an especially assortative structure. That is, their own Pearson correlation coefficients are able to achieve the theoretical upper bound. Last but not the least, we find the sizes of community in the proposed models to follow the power law in a form with respect to modularity maximization.

关键词： Network structure Networks & random structures Scale free & inhomogeneous networks

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Employing derivatives for creating texture masks for digital images

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AIP Conference Proceedings 2024年第1期2898卷

作者： Taha Basheer Taha Ruzelita Ngadiran Dujan B. Taha IT Department Faculty of Applied Science Tishk International University Erbil Kurdistan Region Iraq Faculty of Electronic Engineering Technology Universiti Malaysia Perlis 02600 Arau Perlis Malaysia Centre of Excellence Advanced Computing (AdvComp) Universiti Malaysia Perlis 02600 Arau Perlis Malaysia Software Engineering Department College of Computer Science and Mathematics Mosul University Mosul Iraq

Texture masking has been used as a significant factor in creating perceptual maps that simulates human vision system in observing noise in digital images. In this paper, the possibility of creating texture masks using first and second derivatives is investigated and tested. Results shows that after applying the derivatives, areas of higher texture were highlighted and recognized, which will lead to simple implementation of texture masks using numerical analysis.

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RETRACTED: Emerging research trends in artificial intelligence for cancer diagnostic systems: A comprehensive review

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Heliyon 2024年第17期10卷

作者： Sagheer Abbas Muhammad Asif Abdur Rehman Meshal Alharbi Muhammad Adnan Khan Nouh Elmitwally Department of Computer Science Prince Mohammad Bin Fahd University Al-Khobar KSA Department of Computer Science Education University Lahore Attock Campus Pakistan School of Computer Science National College of Business Administration and Economics Lahore 54000 Pakistan Department of Computer Science College of Computer Engineering and Sciences Prince Sattam Bin Abdulaziz University 11942 Alkharj Saudi Arabia Riphah School of Computing & Innovation Faculty of Computing Riphah International University Lahore Campus Lahore 54000 Pakistan School of Computing Skyline University College University City Sharjah 1797 Sharjah United Arab Emirates Department of Software Faculty of Artificial Intelligence and Software Gachon University Seongnam-si 13120 Republic of Korea Department of Computer Science Faculty of Computers and Artificial Intelligence Cairo University Giza 12613 Egypt School of Computing and Digital Technology Birmingham City University Birmingham B4 7XG UK

This article has been retracted: please see Elsevier policy on article withdrawal (https://***/about/policies-and-standards/article-withdrawal).This article has been retracted at the request of the ***-publication, an investigation conducted by Elsevier's Research Integrity & Publishing Ethics team on behalf of the journal identified references that are irrelevant to the article. The authors were asked to comment upon the presence of these references in their work but were unable to satisfactorily address the reason for the references. Among the irrelevant references, 12 citations were added to this paper which are not relevant to the topic of the paper and benefit authors, Sagheer Abbas and Muhammad Adnan Khan and Abdur Rehman. Consequently, the Editor no longer has confidence in the integrity and the findings of the article and has decided to retract *** scientific community takes a very strong view on this matter and apologies are offered to readers of the journal that this was not detected during the submission *** authors disagree with retraction and dispute the grounds for it.

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Adversarial Learning with Cost-Sensitive Classes

arXiv

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arXiv 2021年

作者： Shen, Haojing Chen, Sihong Wang, Ran Wang, Xizhao Big Data Institute College of Computer Science and Software Engineering Guangdong Key Lab. of Intelligent Information Processing Shenzhen University Guangdong Shenzhen518060 China The College of Mathematics and Statistics Shenzhen University Shenzhen518060 China The Shenzhen Key Laboratory of Advanced Machine Learning and Applications Shenzhen University Shenzhen518060 China

It is necessary to improve the performance of some special classes or to particularly protect them from attacks in adversarial learning. This paper proposes a framework combining cost-sensitive classification and adversarial learning together to train a model that can distinguish between protected and unprotected classes, such that the protected classes are less vulnerable to adversarial examples. We find in this framework an interesting phenomenon during the training of deep neural networks, called Min-Max property, that is, the absolute values of most parameters in the convolutional layer approach zero while the absolute values of a few parameters are significantly larger becoming bigger. Based on this Min-Max property which is formulated and analyzed in a view of random distribution, we further build a new defense model against adversarial examples for adversarial robustness improvement. An advantage of the built model is that it performs better than the standard one and can combine with adversarial training to achieve an improved performance. It is experimentally confirmed that, regarding the average accuracy of all classes, our model is almost as same as the existing models when an attack does not occur and is better than the existing models when an attack occurs. Specifically, regarding the accuracy of protected classes, the proposed model is much better than the existing models when an attack occurs. © 2021, CC BY.

关键词： Deep neural networks

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Improving Data Utility Through Game Theory in Personalized Differential Privacy

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Journal of computer science & Technology 2019年第2期34卷 272-286页

作者： Lei Cui Youyang Qu Mohammad Reza Nosouhi Shui Yu Jian-Wei Niu Gang Xie College of Information and Computer Taiyuan University of Technology Taiyuan 030024 China School of Information Technology Deakin University Melbourne VIC 3125 Australia School of Software University of Technology Sydney Sydney NSW 2007 Australia School of Computer Science and Engineering Beihang University Beijing 100191 China Shanxi Key Laboratory of Advanced Control and Intelligent Information System Taiyuan University of Science and Technology Taiyuan 030024 China

Due to dramatically increasing information published in social networks,privacy issues have given rise to public *** the presence of differential privacy provides privacy protection with theoretical foundations,the trade-off between privacy and data utility still demands further ***,most existing studies do not consider the quantitative impact of the adversary when measuring data *** this paper,we firstly propose a personalized differential privacy method based on social ***,we analyze the maximum data utility when users and adversaries are blind to the strategy sets of each *** formalize all the payoff functions in the differential privacy sense,which is followed by the establishment of a static Bayesian *** trade-off is calculated by deriving the Bayesian Nash equilibrium with a modified reinforcement learning *** proposed method achieves fast convergence by reducing the cardinality from n to *** addition,the in-place trade-off can maximize the user's data utility if the action sets of the user and the adversary are public while the strategy sets are *** extensive experiments on the real-world dataset prove the proposed model is effective and feasible.

关键词： personalized privacy protection game theory trade-off reinforcement learning

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