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International Conference on Nonlinear Applied Analysis and Optimization, ICNAAO-2021

作者： Ganguly, Sanchari Das, Pritha Maiti, Manoranjan Department of Mathematics Indian Institute of Engineering Science and Technology Shibpur WB Howrah711103 India Department of Applied Mathematics Oceanology and Computer Programming Vidyasagar University WB Midnapore721102 India

ISBN: (纸本)9789819905966

Fairness concern behavior, a well-known cognitive bias, refers to a person’s attitude of dissatisfaction for unequal pay-offs in someone’s favor. Against environmental pollution, many firms are focused on green manufacturing to maintain sustainable development. The adoption of online shopping by customers around the globe has altered the dynamics of competitiveness in the retail supply chain (SC). Considering the above facts, the effect of fairness concern on optimal prices and channel members’ profits in a two-level dual channel SC is investigated. Here, we consider an SC comprising a green manufacturer and a fair-minded retailer where the manufacturer produces and sells the green product through both offline and online channels to consumers. Due to uncertainty in the real world, the fuzziness is associated with market demand, price elasticity, and the coefficient of greenness. The fuzzy objectives and constraints are reduced to crisp ones using expectation and possibility measures, respectively. Both centralized and decentralized models (with and without cognitive bias) are formulated and solved by the Stackelberg game for the optimal prices and product greenness level. The models’ optimal solutions are analyzed and compared with the deterministic models numerically. The effects of the fairness concern coefficient on the optimal prices, product greenness level, and channel members’ profits are investigated. The sensitivity analyses are presented to study the effects of the fuzzy degree of customers’ sensitivity toward greenness on channel members’ profits. Retailer’s fairness is harmful to the manufacturer but beneficial for her own profit. Finally, some conclusions and managerial insights are presented. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Game theory

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Research of colorde image digital watermark

Research of colorde image digital watermark

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computer science and Information Engineering, CSIE 2012

作者： Shang, Cun Yang, Peng Service Computer Technology and Graphics Lab. Department of Computer Science and Technology Xinyang Agricultural College Xinyang Henan 464000 China

ISBN: (纸本)9783642302220

Digital watermarking is one of the effective technology which can protect the copyright of digital product and data security. For the encoding technology of color image, this paper proposed a method for embedding the watermarking using HSI color model. this paper propose an algorithm based on wavelet analysis, a colored watermark is embedded in a carrier, It embedded the image, which is disordered through ARNOLD transformation into the I space of the carrier image transformed. The results indicate that the watermarking technology proposed by this paper is secure and robust at resistance to compression and resistance to filtering. © 2012 Springer-Verlag GmbH.

关键词： Digital watermarking

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AsyReC: A Multimodal Graph-based Framework for Spatio-Temporal Asymmetric Dyadic Relationship Classification

arXiv

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arXiv 2025年

作者： Tang, Wang Dogan, Fethiye Irmak Qing, Linbo Gunes, Hatice AFAR Lab Department of Computer Science and Technology University of Cambridge CambridgeCB3 0FT United Kingdom College of Electronics and Information Engineering Sichuan University Chengdu610065 China

Dyadic social relationships, which refer to relationships between two individuals who know each other through repeated interactions (or not), are shaped by shared spatial and temporal experiences. Current computational methods for modeling these relationships face three major challenges: (1) the failure to model asymmetric relationships, e.g., one individual may perceive the other as a friend while the other perceives them as an acquaintance, (2) the disruption of continuous interactions by discrete frame sampling, which segments the temporal continuity of interaction in real-world scenarios, and (3) the limitation to consider periodic behavioral cues, such as rhythmic vocalizations or recurrent gestures, which are crucial for inferring the evolution of dyadic relationships. To address these challenges, we propose AsyReC, a multimodal graph-based framework for asymmetric dyadic relationship classification, with three core innovations: (i) a triplet graph neural network with node-edge dual attention that dynamically weights multimodal cues to capture interaction asymmetries (addressing challenge 1);(ii) a clip-level relationship learning architecture that preserves temporal continuity, enabling fine-grained modeling of real-world interaction dynamics (addressing challenge 2);and (iii) a periodic temporal encoder that projects time indices onto sine/cosine waveforms to model recurrent behavioral patterns (addressing challenge 3). Extensive experiments on two public datasets demonstrate state-of-the-art performance, while ablation studies validate the critical role of asymmetric interaction modeling and periodic temporal encoding in improving the robustness of dyadic relationship classification in real-world scenarios. Our code is publicly available at: https://***/tw-repository/AsyReC. © 2025, CC BY.

关键词： Graph neural networks

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Research on buffer overflow test based on invariant

Research on buffer overflow test based on invariant

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IEEE 9th International Conference on computer and Information technology, CIT 2009

作者： Zeng, Fanping Chen, Minghui Yin, Kaitao Wang, Xufa Department of Computer University of Science and Technology of China Anhui Province Key Lab. of Software in Computer and Communication Hefei Anhui China Department of Computer University of Science and Technology of China Hefei Anhui China

ISBN: (纸本)9780769538365

Buffer overflow (BOF) is one of the major vulnerabilities that lead to non-secure software. Testing an implementation for BOF vulnerabilities is challenging as the underlying reasons of buffer overflow vary widely. This paper presents a novel method for BOF test for ANSI C language, which uses program instrumentation and mutation test technology to test the BOF vulnerabilities, on the basis of analyzing the invariants for BOF vulnerabilities. The implementation shows that it can check the attack of BOF vulnerabilities adequately and accurately, in the circumstances of no large losses in performance. © 2009 IEEE.

关键词： Testing

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Study on the unified and formalized description of the component using the category theory

Study on the unified and formalized description of the compo...

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International Forum on Information technology and Applications

作者： Haitao, Wang Xing, Chen Ying, Jiang Computer Technology Application Key Lab. of Yunnan Province Kunming University of Science and Technology Kunming 650051 China Department of Computer Science Kunming University of Science and Technology Kunming 650051 China

ISBN: (纸本)9780769541150

The focus of the software development technology based on components is the identification and assembly of components. The formalized descriptions of the component, including data and computing descriptions, are studied using the theory and method of category. The focus is the unified description of component computing (i.e. component function). The unified description of the component in a certain domain is studied by many different methods: (1) The model of the component data is constructed using the partial order category theory. (2) The component computing is presented by the morphism. (3) The component computing is described using category theories (e.g. limit, nature transformation). The goal is to establish the unified description system of components based on the category theory. Discussions are also presented to stress its importance in the automatic identification and assembly of the component. © 2010 IEEE.

关键词： Software design

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Adaptive difference method and singular treatment approach for fast parameters extraction of interconnects in MEI system

Adaptive difference method and singular treatment approach f...

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2005 International Conference on Communications, Circuits and Systems

作者： Zhang, Ying Wang, Janet M. Xiao, Liang Wu, Huizhong 603 Lab Department of Computer Science and Technology Nanjing University of Science and Technology China University of Arizona College of Engineering and Mines Department of Electrical and Computer Engineering Tucson AZ 85721

ISBN: (纸本)0780390156

At present accurate evaluation of the capacitances of transmission lines is desired. Most TEM mode transmission lines have cross-sections with reentrant corners where the potential gradient is singular. In this paper MEI is used with nonuniform grids to extract the capacitance parameter in the presence of reentrant corners. The mathematical model of electric field near the reentrant is given and its analytical solution formation is derived. Finite series expansion is used to approximate the analytical solution, and a novel method is proposed to calculate the charge of conductor. Compared with Duncan correction the technique avoids the choice of the integral length of normal derivative near the reentrant and it can be used with nonuniform grids more conveniently. The error analysis of asymptotic approximation of finite series expansion is also given. Numerical experiments are presented for analysis. © 2005 IEEE.

关键词： Electric lines

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Novel Ransomware Hiding Model Using HEVC Steganography Approach

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computers, Materials & Continua 2022年第1期70卷 1209-1228页

作者： Iman Almomani Aala AlKhayer Walid El-Shafai Security Engineering Lab Computer Science DepartmentPrince Sultan UniversityRiyadh11586Saudi Arabia Computer Science Department King Abdullah II School for Information TechnologyThe University of Jordan11942Jordan Department of Electronics and Electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt

Ransomware is considered one of the most threatening *** solutions have focused mainly on discriminating ransomware by analyzing the apps themselves,but they have overlooked possible ways of hiding ransomware apps and making them difficult to be detected and then ***,this paper proposes a novel ransomware hiding model by utilizing a block-based High-Efficiency Video Coding(HEVC)steganography *** main idea of the proposed steganography approach is the division of the secret ransomware data and cover HEVC frames into different *** that,the Least Significant Bit(LSB)based Hamming Distance(HD)calculation is performed amongst the secret data’s divided blocks and cover ***,the secret data bits are hidden into the marked bits of the cover HEVC frame-blocks based on the calculated HD *** main advantage of the suggested steganography approach is the minor impact on the cover HEVC frames after embedding the ransomware while preserving the histogram attributes of the cover video frame with a high *** is due to the utilization of an adaptive steganography cost function during the embedding *** proposed ransomware hiding approach was heavily examined using subjective and objective tests and applying different HEVC streams with diverse resolutions and different secret ransomware apps of various *** obtained results prove the efficiency of the proposed steganography approach by achieving high capacity and successful embedding process while ensuring the hidden ransomware’s undetectability within the video *** example,in terms of embedding quality,the proposed model achieved a high peak signal-to-noise ratio that reached 59.3 dB and a low mean-square-error of 0.07 for the examined HEVC ***,out of 65 antivirus engines,no engine could detect the existence of the embedded ransomware app.

关键词： Ransomware embedding steganography HEVC LSB hamming distance applications apk stego security confidentiality

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Improved Bayesian logistic supervised topic models with data augmentation

Improved Bayesian logistic supervised topic models with data...

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51st Annual Meeting of the Association for Computational Linguistics, ACL 2013

作者： Zhu, Jun Zheng, Xun Zhang, Bo Department of Computer Science and Technology TNLIST Lab and State Key Lab of Intelligent Technology and Systems Tsinghua University Beijing China

ISBN: (纸本)9781937284503

Supervised topic models with a logistic likelihood have two issues that potentially limit their practical use: 1) response variables are usually over-weighted by document word counts;and 2) existing variational inference methods make strict mean-field assumptions. We address these issues by: 1) introducing a regularization constant to better balance the two parts based on an optimization formulation of Bayesian inference;and 2) developing a simple Gibbs sampling algorithm by introducing auxiliary Polya-Gamma variables and collapsing out Dirichlet variables. Our augment-and-collapse sampling algorithm has analytical forms of each conditional distribution without making any restricting assumptions and can be easily parallelized. Empirical results demonstrate significant improvements on prediction performance and time efficiency. © 2013 Association for Computational Linguistics.

关键词： Bayesian networks

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DROPEDGE: TOWARDS DEEP GRAPH CONVOLUTIONAL NETWORKS ON NODE CLASSIFICATION 8

DROPEDGE: TOWARDS DEEP GRAPH CONVOLUTIONAL NETWORKS ON NODE ...

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8th International Conference on Learning Representations, ICLR 2020

作者： Rong, Yu Huang, Wenbing Xu, Tingyang Huang, Junzhou Tencent AI Lab State Key Lab on Intelligent Technology and Systems Department of Computer Science and Technology Tsinghua University China

Over-fitting and over-smoothing are two main obstacles of developing deep Graph Convolutional Networks (GCNs) for node classification. In particular, over-fitting weakens the generalization ability on small dataset, while over-smoothing impedes model training by isolating output representations from the input features with the increase in network depth. This paper proposes DropEdge, a novel and flexible technique to alleviate both issues. At its core, DropEdge randomly removes a certain number of edges from the input graph at each training epoch, acting like a data augmenter and also a message passing reducer. Furthermore, we theoretically demonstrate that DropEdge either reduces the convergence speed of over-smoothing or relieves the information loss caused by it. More importantly, our DropEdge is a general skill that can be equipped with many other backbone models (e.g. GCN, ResGCN, GraphSAGE, and JKNet) for enhanced performance. Extensive experiments on several benchmarks verify that DropEdge consistently improves the performance on a variety of both shallow and deep GCNs. The effect of DropEdge on preventing over-smoothing is empirically visualized and validated as well. Codes are released on https://***/DropEdge/DropEdge. © 2020 8th International Conference on Learning Representations, ICLR 2020. All rights reserved.

关键词： Message passing

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An Efficient Detection Approach of Content Aware Image Resizing

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computers, Materials & Continua 2020年第8期64卷 887-907页

作者： Ming Lu Shaozhang Niu Zhenguang Gao Beijing Key Lab of Intelligent Telecommunication Software and Multimedia Beijing University of Posts and TelecommunicationsBeijing100876China School of Computer Science and Software Engineering University of Science and Technology LiaoningAnshan114051China Department of Computer Science Framingham State UniversityMassachusettsMA 01772USA

Content aware image resizing(CAIR)is an excellent technology used widely for image *** can also be used to tamper with images and bring the trust crisis of image content to the *** an image is processed by CAIR,the correlation of local neighborhood pixels will be *** local binary patterns(LBP)can effectively describe the local texture,it however cannot describe the magnitude information of local neighborhood pixels and is also vulnerable to ***,to deal with the detection of CAIR,a novel forensic method based on improved local ternary patterns(ILTP)feature and gradient energy feature(GEF)is proposed in this ***,the adaptive threshold of the original local ternary patterns(LTP)operator is improved,and the ILTP operator is used to describe the change of correlation among local neighborhood pixels caused by ***,the histogram features of ILTP and the gradient energy features are extracted from the candidate image for CAIR forgery ***,the ILTP features and the gradient energy features are concatenated into the combined features,and the combined features are used to train *** support vector machine(SVM)is exploited as a classifier to be trained and tested by the above features in order to distinguish whether an image is subjected to CAIR or *** candidate images are extracted from uncompressed color image database(UCID),then the training and testing sets are *** experimental results with many test images show that the proposed method can detect CAIR tampering effectively,and that its performance is improved compared with other *** can achieve a better performance than the state-of-the-art approaches.

关键词： Digital image forensics content aware image resizing local ternary patterns gradient energy feature

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