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SEM for Predicting in Determining Factor of Social Customer Relationship Management Adoption in SMEs 6

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SEM for Predicting in Determining Factor of Social Customer ...

6th IEEE International Conference on Cybernetics and Computational Intelligence, CyberneticsCom 2022

作者： Purwanti, Hani Rochim, Adian Fatchur Warsito, Budi Diponegoro University Master of Information System Semarang Indonesia Diponegoro University Department of Computer Engineering Semarang Indonesia Diponegoro University Faculty of Science and Mathematics Department of Statistics Semarang Indonesia

ISBN: (数字)9781665497428

ISBN: (纸本)9781665497428

The increasing use of social media is challenging the old concept of customer relationship management (CRM). Social CRM strategy is a new model of CRM that applies social technology by presenting a new way to manage customer relationships. Compared to traditional CRM, social media is an affordable tool for SMEs to compete in the global market. Although the application of social CRM can increase business in SMEs, the implementation of social CRM still requires various conditions, especially for SMEs with limited resources. So for the adoption of social CRM, it is necessary to determine the factors that influence the adoption of social CRM in SMEs. This study aims to predict the adoption of social CRM by proposing a TOEP application model and developing several hypotheses that test the function of technology factors, Organizational factors, Environment factors, and Information Process factors. The proposed hypothesis model was tested using the SEM method on data taken from SMEs in the Banyumas area with a sample of 115 SMEs. This study finds that Relative Advantage, Complexity, Compatibility CRMS, Employee IT/SI Knowledge, Government Support, Information Use, Information Retrieval are the most important factors influencing the adoption of social CRM. This study differs from previous studies because it proposes a new model, namely the TOE adoption model and the information process factor as an additional factor to determine the factors that affect social CRM in SMEs. © 2022 IEEE.

关键词： Scanning electron microscopy

Modeling, simulation, and prediction of global energy indices: a differential approach

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Frontiers in Energy 2022年第2期16卷 375-392页

作者： Stephen Ndubuisi NNAMCHI Onyinyechi Adanma NNAMCHI Janice Desire BUSINGYE Maxwell Azubuike IJOMAH Philip Ikechi OBASI Department of Mechanical Engineering Kampala International University20000 KampalaUganda Department of Agricultural Engineering and Bio Resources Michael Okpara University of AgricultureUmudikeUmuahiaNigeria Directorate of Human Resource/Finance Kampala International University20000 KampalaUganda Department of Mathematics and Statistics Faculty of SciencesUniversity of Port HarcourtPMB 5323 Choba Port HarcourtNigeria Department of Macroeconomic Analysis(Ministry of Finance) Budget and National PlanningAbujaNigeria

Modeling, simulation, and prediction of global energy indices remain veritable tools for econometric, engineering, analysis, and prediction of energy indices. Thus, this paper differentially modeled, simulated, and non-differentially predicated the global energy indices. The state-of-the-art of the research includes normalization of energy indices, generation of differential rate terms, and regression of rate terms against energy indices to generate coefficients and unexplained terms. On imposition of initial conditions, the solution to the system of linear differential equations was realized in a Matlab environment. There was a strong agreement between the simulated and the field data. The exact solutions are ideal for interpolative prediction of historic data. Furthermore, the simulated data were upgraded for extrapolative prediction of energy indices by introducing an innovative model, which is the synergy of deflated and inflated prediction factors. The innovative model yielded a trendy prediction data for energy consumption, gross domestic product, carbon dioxide emission and human development index. However, the oil price was untrendy, which could be attributed to odd circumstances. Moreover, the sensitivity of the differential rate terms was instrumental in discovering the overwhelming effect of independent indices on the dependent index. Clearly, this paper has accomplished interpolative and extrapolative prediction of energy indices and equally recommends for further investigation of the untrendy nature of oil price.

关键词： energy indices differential model normalization simulation inflation deflation predictive factor and prediction rate

Deep models for stroke segmentation: do complex architectures always perform better?

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arXiv 2024年

作者： Zafari-Ghadim, Yalda Soliman, Ahmed Yousif, Yousif Ibrahim, Ahmed Rashed, Essam A. Mabrok, Mohamed Mathematics Program Department of Mathematics Statistics and Physics College of Arts and Sciences Qatar University P.O.Box 2713 Doha Qatar Graduate School of Information Science University of Hyogo Kobe650-0047 Japan

Stroke segmentation plays a crucial role in the diagnosis and treatment of stroke patients by providing spatial information about affected brain regions and the extent of damage. Segmenting stroke lesions accurately is a challenging task, given that conventional manual techniques are time-consuming and prone to errors. Recently, advanced deep models have been introduced for general medical image segmentation, demonstrating promising results that surpass many state-of-the-art networks when evaluated on specific datasets. With the advent of the vision Transformers, several models have been introduced based on them, while others have aimed to design better modules based on traditional convolutional layers to extract long-range dependencies like Transformers. The question of whether such high-level designs are necessary for all segmentation cases to achieve the best results remains unanswered. In this study, we selected four types of deep models that were recently proposed and evaluated their performance for stroke segmentation: (1) a pure Transformer-based architecture (DAE-Former), (2) two advanced CNN-based models (LKA and DLKA) with attention mechanisms in their design, (3) an advanced hybrid model that incorporates CNNs with Transformers (FCT), and (4) the well-known self-adaptive nnU-Net framework with its configuration based on given data. We examined their performance on two publicly available datasets, ISLES 2022 and ATLAS v2.0, and found that the nnU-Net achieved the best results with the simplest design among all. Additionally, we investigated the impact of an imbalanced distribution of the number of unconnected components in each slice, as a representation of common variabilities in stroke segmentation. Revealing the robustness issue of Transformers to such variabilities serves as a potential reason for their weaker performance. Furthermore, nnU-Net’s success underscores the significant impact of preprocessing and postprocessing techniques in enhancing segme

关键词： Convolutional neural networks

ON THE ROTATIONAL INVARIANCE AND HYPERBOLICITY OF SHALLOW WATER MOMENT EQUATIONS IN TWO DIMENSIONS

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arXiv 2023年

作者： Bauerle, Matthew Christlieb, Andrew J. Ding, Mingchang Huang, Juntao Department of Mathematics Department of Computational Mathematics Science and Engineering Michigan State University East LansingMI48824 United States Department of Mathematics Department of Computational Mathematics Science and Engineering Michigan State University East LansingMI48824 United States Department of Computational Mathematics Science and Engineering Michigan State University East LansingMI48824 United States Department of Mathematics and Statistics Texas Tech University LubbockTX79409 United States

In this paper, we investigate the two-dimensional extension of a recently introduced set of shallow water models based on a regularized moment expansion of the incompressible Navier-Stokes equations [21, 20]. We show the rotational invariance of the proposed moment models with two different approaches. The first proof involves the split of the coefficient matrix into the conservative and non-conservative parts and proves the rotational invariance for each part, while the second one relies on the special block structure of the coefficient matrices. With the aid of rotational invariance, the analysis of the hyperbolicity for the moment model in 2D is reduced to the real diagonalizability of the coefficient matrix in 1D. Then we analyze the real diagonalizability by deriving the analytical form of the characteristic polynomial. We find that the moment model in 2D is hyperbolic in most cases and weakly hyperbolic in a degenerate edge case. With a simple modification to the coefficient matrices, we fix this weakly hyperbolicity and propose a new global hyperbolic model. Furthermore, we extend the model to include a more general class of closure relations than the original model and establish that this set of general closure relations retains both rotational invariance and hyperbolicity. © 2023, CC BY.

关键词： Navier Stokes equations

Differentially Private Synthetic Data with Private Density Estimation

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Differentially Private Synthetic Data with Private Density E...

IEEE International Symposium on Information Theory

作者： Nikolija Bojkovic Po-Ling Loh School of Electrical Engineering University of Belgrade Belgrade Serbia Department of Pure Mathematics and Mathematical Statistics University of Cambridge Cambridge United Kingdom

ISBN: (数字)9798350382846

ISBN: (纸本)9798350382853

The need to analyze sensitive data, such as medical records or financial data, has created a critical research challenge in recent years. In this paper, we adopt the framework of differential privacy, and explore mechanisms for generating an entire dataset which accurately captures characteristics of the original data. We build upon the work of Boedihardjo et al. [1], which laid the foundations for a new optimization-based algorithm for generating private synthetic data. Importantly, we adapt their algorithm by replacing a uniform sampling step with a private distribution estimator; this allows us to obtain better computational guarantees for discrete distributions, and develop a novel algorithm suitable for continuous distributions. We also explore applications of our work to several statistical tasks. A full version of the paper, containing appendices, can be found at https://***/abs/2405.04554.

关键词： Privacy Histograms Accuracy Upper bound Risk minimization Noise Task analysis

Federated Reinforcement Learning for Resource Allocation in V2X Networks

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Federated Reinforcement Learning for Resource Allocation in ...

IEEE Conference on Vehicular Technology (VTC)

作者： Kaidi Xu Shenglong Zhou Geoffrey Ye Li Department of Electrical and Electronic Engineering Imperial College London London UK The School of Mathematics and Statistics Beijing Jiaotong University Beijing China

ISBN: (数字)9798350387414

ISBN: (纸本)9798350387421

Resource allocation significantly impacts the performance of vehicle-to-everything (V2X) networks. Most existing algorithms for resource allocation are based on optimization or machine learning (e.g., reinforcement learning). In this paper, we explore resource allocation in a V2X network under the framework of federated reinforcement learning (FRL). On one hand, the usage of RL overcomes many challenges from the model-based optimization schemes. On the other hand, federated learning (FL) enables agents to deal with a number of practical issues, such as privacy, communication overhead, and exploration efficiency. The framework of FRL is then implemented by the in-exact alternative direction method of multipliers (ADMM), where subproblems are solved approximately using policy gradients and their second moments. The developed algorithm, FRLPGiA, has a nice numerical performance compared with some baseline methods for solving the resource allocation problem in a V2X network.

关键词： Training Vehicular and wireless technologies Privacy Machine learning algorithms Federated learning Reinforcement learning Approximation algorithms

Rician Channel Modelling for Super Wideband MIMO Communications

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arXiv 2024年

作者： Bandara, Sachitha C. Smith, Peter J. Khordad, Erfan Evans, Robin Senanayake, Rajitha Department of Electrical and Electronic Engineering University of Melbourne Melbourne Australia School of Mathematics and Statistics Victoria University of Wellington Wellington New Zealand

Recent developments in Multiple-Input-Multiple-Output (MIMO) technology include packing a large number of antenna elements in a compact array to access the bandwidth benefits provided by higher mutual coupling (MC). The resulting super-wideband (SW) systems require a circuit-theoretic framework to handle the MC and channel models which span extremely large bands. Hence, in this paper, we make two key contributions. First, we develop a physically-consistent Rician channel model for use with SW systems. Secondly, we express the circuit-theoretic models in terms of a standard MIMO model, so that insights into the effects of antenna layouts, MC, and bandwidth can be made using standard communication theory. For example, we show the bandwidth widening resulting from the new channel model. In addition, we show that MC distorts line-of-sight paths which has beamforming implications. We also highlight the interaction between spatial correlation and MC and show that tight coupling reduces spatial correlations at low frequencies. Copyright © 2024, The Authors. All rights reserved.

关键词： Bandwidth

Weak Closed-loop Solvability for Discrete-time Stochastic Linear-Quadratic Optimal Control

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arXiv 2025年

作者： Sun, Yue Wu, Xianping Li, Xun School of Control Science and Engineering Shandong University Shandong Jinan250061 China School of Mathematics and Statistics Guangdong University of Technology Guangzhou China Department of Applied Mathematics The Hong Kong Polytechnic University Hong Kong

In this paper, the solvability of discrete-time stochastic linear-quadratic (LQ) optimal control problem in finite horizon is considered. Firstly, it shows that the closed-loop solvability for the LQ control problem is optimal if and only if the generalized Riccati equation admits a regular solution by solving the forward and backward difference equations iteratively. To this ends, it finds that the open-loop solvability is strictly weaker than closed-loop solvability, that is, the LQ control problem is always open-loop optimal solvable if it is closed-loop optimal solvable but not vice versa. Secondly, by the perturbation method, it proves that the weak-closed loop strategy which is a feedback form of a state feedback representation is equivalent to the open-loop solvability of the LQ control problem. Finally, an example sheds light on the theoretical results *** Codes org © 2025, CC BY.

关键词： Riccati equations

Inference for a constant-partially accelerated life tests with competing risks for failure from Burr distribution under progressively type-I interval censoring

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Inference for a constant-partially accelerated life tests wi...

2021 International Conference on statistics, Applied mathematics, and Computing Science, CSAMCS 2021

作者： Wang, Ruibing Shi, Yimin School of Mathematics and Statistics Northwestern Polytechnical University Xi'an710072 China Department of Information Engineering and Big Data Science Shanxi Institute of Technology Yangquan045000 China

ISBN: (纸本)9781510652026

In this paper, the constant-partially accelerated life tests under progressively type-I interval censoring is considered when the competing risks product follow Burr (c,k) distributions. The estimates of the unknown parameters of the different causes are obtained through a maximum likelihood method, and the Fisher information matrix is derived too. The asymptotic and bootstrap confidence intervals are given by using the asymptotic normality theory and parametric bootstrap method. Based on the Fisher information matrix, we also discuss the problem of optimal sample size allocation at each stress level. Finally, a simulation study is carried out to illustrate the performance of the proposed methods. © COPYRIGHT SPIE.

关键词： Fisher information matrix