We establish a pointwise property for homogeneous fractional Sobolev spaces in domains with non-empty boundary,extending a similar result of Koskela–Yang–*** use this to show that a conformal map from the unit disk ...
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We establish a pointwise property for homogeneous fractional Sobolev spaces in domains with non-empty boundary,extending a similar result of Koskela–Yang–*** use this to show that a conformal map from the unit disk onto a simply connected planar domain induces a bounded composition operator from the borderline homogeneous fractional Sobolev space of the domain into the corresponding space of the unit disk.
Purpose: This systematic literature review aims to identify the pattern of data mining (DM) research by looking at the levels and aspects of education. Design/methodology/approach: This paper reviews 113 conference an...
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Purpose: This systematic literature review aims to identify the pattern of data mining (DM) research by looking at the levels and aspects of education. Design/methodology/approach: This paper reviews 113 conference and research papers from well-known publishers of educational data mining (EDM) and learning analytics-related research using a recognized literature review in computerscience by Carrera-Rivera et al. (2022a). Two major stages, planning and conducting the review, were used. The databases of Elsevier, Springer, IEEE, SAI, Hindawi, MDPI, Wiley, Emerald and Sage were searched to retrieve EDM papers from the period 2017 to 2023. The papers retrieved were then filtered based on the application of DM to the three educational levels – basic, pre-tertiary and tertiary education. Findings: EDM is concentrated on higher education. Basic education is not given the needed attention in EDM. This does not enhance inclusivity and equity. Learner performance is given much attention. Resource availability and teaching and learning are not given the needed attention. Research limitations/implications: This review is limited to only EDM. Literature from the year 2017 to 2023 is covered. Other aspects of DM and other relevant literature published in EDM outside the research period are not considered. Practical implications: As the current trend of EDM shows an increase in zeal, future research in EDM should concentrate on the lower levels of education to identify the challenges of basic education which serves as the core of education. This will enable addressing the challenges of education at an early stage and facilitate getting a quality education at all levels of education. Appropriate EDM techniques for mining the data at this level should be the focus of the research. Specifically, techniques that can cater for the variation in learner abilities and the appropriate identification of learner needs should be considered. Social implications: Content sequencing is necessar
With the increasing prevalence of Android software,protecting it against malicious threats has become a critical *** malware detection methods,tailored for static environments,often fail to adapt to evolving threats i...
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With the increasing prevalence of Android software,protecting it against malicious threats has become a critical *** malware detection methods,tailored for static environments,often fail to adapt to evolving threats in dynamic *** address the challenge of detecting evolving malware,we introduce DMDroid,a novel multi-modal fusion-based framework for malware analysis and *** leverages an array of feature extraction technologies and advanced deep learning models to analyze data,enhanced by a multi-head attention *** mechanism optimizes the integration of diverse static features from graphbased and image-based modalities,including permissions,API calls,opcodes,and bytecode sequences,prioritizing critical features to effectively detect new and evolving malware *** evaluate DMDroid in various realistic *** show that compared to Bai,Drebin,and MaMa-pkg detector,DMDroid can improve the detection accuracy by 117.56%,122.11%,and 119.47%,*** to an unimodal approach,DMDroid can enhance the accuracy,macro-averaged F1 score,and weighted-averaged F1 score by 143.25%,75.84%and 279.22%.The prototype can help to improve the quality and security of Android malware analysis and detection.
Monogamy and polygamy relations characterize the distributions of entanglement in multipartite *** provide a characterization of multiqubit entanglement constraints in terms of unified-(q,s)entropy.A class of tighter ...
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Monogamy and polygamy relations characterize the distributions of entanglement in multipartite *** provide a characterization of multiqubit entanglement constraints in terms of unified-(q,s)entropy.A class of tighter monogamy inequalities of multiqubit entanglement based on theα-th power of unified-(q,s)entanglement forα≥1 and a class of polygamy inequalities in terms of theβ-th power of unified-(q,s)entanglement of assistance are established in this *** results present a general class of the monogamy and polygamy relations for bipartite entanglement measures based on unified-(q,s)entropy,which are tighter than the existing *** is more,some usual monogamy and polygamy relations,such as monogamy and polygamy relations based on entanglement of formation,Renyi-q entanglement of assistance and Tsallis-q entanglement of assistance,can be obtained from these results by choosing appropriate parameters(q,s)in unified-(q,s)entropy *** examples are also presented for illustration.
In this paper, we propose a novel warm restart technique using a new logarithmic step size for the stochastic gradient descent (SGD) approach. For smooth and non-convex functions, we establish an O(1/√T) convergence ...
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In this paper, we propose a novel warm restart technique using a new logarithmic step size for the stochastic gradient descent (SGD) approach. For smooth and non-convex functions, we establish an O(1/√T) convergence rate for the SGD. We conduct a comprehensive implementation to demonstrate the efficiency of the newly proposed step size on the FashionMinst, CIFAR10, and CIFAR100 datasets. Moreover, we compare our results with nine other existing approaches and demonstrate that the new logarithmic step size improves test accuracy by 0.9% for the CIFAR100 dataset when we utilize a convolutional neural network (CNN) model.
The Bank Credit Decision-Making Problem (BCDMP) is one of the main issues that bank operations need to face. To obtain the maximum profit value and optimal loan plan of the bank as much as possible, this article sugge...
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Courier delivery is the end of the supply chain and affects the final delivery of products. Due to the promulgation of new courier delivery regulations, home delivery services have become the main choice for consumers...
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We present results of numerical simulations of the tensor-valued elliptic-parabolic PDE model for biological network *** numerical method is based on a nonlinear finite difference scheme on a uniform Cartesian grid in...
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We present results of numerical simulations of the tensor-valued elliptic-parabolic PDE model for biological network *** numerical method is based on a nonlinear finite difference scheme on a uniform Cartesian grid in a two-dimensional(2D)*** focus is on the impact of different discretization methods and choices of regularization parameters on the symmetry of the numerical *** particular,we show that using the symmetric alternating direction implicit(ADI)method for time discretization helps preserve the symmetry of the solution,compared to the(non-symmetric)ADI ***,we study the effect of the regularization by the isotropic background perme-ability r＞0,showing that the increased condition number of the elliptic problem due to decreasing value of r leads to loss of *** show that in this case,neither the use of the symmetric ADI method preserves the symmetry of the ***,we perform the numerical error analysis of our method making use of the Wasserstein distance.
Alignments are a well-established conformance checking technique that serve to reconcile system logs with normative process models. For processes involving multiple entities, such as objects and resources performing d...
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The development of emerging consumer technologies such as the Internet of Things (IoT), artificial intelligence (AI), and cloud computing brings convenience but also raises critical concerns about securing communicati...
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