SliceScore: A Network Function Sharing Aware and Slice-Oriented DDoS Filtering Approach by Omer Zekvan Yilmaz, Kubra Kalkan, Fatih Alagoz

“…Recently, network function (NF) sharing has been proposed in the literature in order to further exploit unused resources and lower the costs for network operators. …”
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Meromorphic functions sharing the zeros of lower degree symmetric polynomials in weighted wider sense by J. Banerjee, A. Banerjee

Subjects: “…meromorphic functions…”
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Enhancing the secrecy of a cryptographic key generated using synchronized artificial neural networks1 by M. L. Radziukevich, V. F. Golikov

“…To solve the problem of increasing the    confidentiality of the generated shared secret, if it is used as a cryptographic key, it is proposed to use the  mixing a certain number of results of individual synchronizations (convolution). …”
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Analytical Characterization of Self-Similarity in <i>k</i>-Cullen Sequences Through Generating Functions and Fibonacci Scaling by Hakan Akkuş, Bahar Kuloğlu, Engin Özkan

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Clinical functioning information tool – coronavirus disease 2019 (ClinFIT COVID-19): psychometric evaluation and development of an interval-scaled functioning score across the care... by Masahiko Mukaino, Catarina Aguiar Branco, Alia Alghwiri, Sonia Amato, Antonios Kontaxakis, Mihai Berteanu, Hüma Bölük Şenlikci, Pinar Borman, Salmane Diouane, Maryam Fourtassi, Francesca Gimigliano, Abderrazak Hajjioui, Xiaolei Hu, Sinforian Kambou, Cho-I Lin, Mohamed I. Mabrouk, Evanthia Mitsiokapa, Remus Iulian Nica, Christina-Anastasia Rapidi, Gabriella Serlenga, Arianna Silvestri, Sinikka Tarvonen-Schröder, Clara Ursescu, Arja Viinanen, Panagiotis Vorniotakis, Melissa Selb

“…Objective: to report on the development and global testing of the COVID-19 version of the International Classification of Functioning, Disability and Health-based Clinical Functioning Information Tool called “ClinFIT COVID-19” to collect functioning data of rehabilitation patients across the care continuum to establish an interval-scaled functioning score. …”
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Image super-resolution reconstruction based on multi-scale dual-attention by Hong-an Li, Diao Wang, Jing Zhang, Zhanli Li, Tian Ma

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Effects of Interfacial Charges On Doped and Undoped HFOX Stack Layer with Tin Metal Gate Electrode For Nano-Scaled CMOS Generation by S. Chatterjee, Y. Kuo

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Searching for Functional Simplicity of Stormflow Generation by Hamed Sharif, Ali A. Ameli

“…Abstract Our study proposes a data‐driven framework that identifies the level of functional simplicity of catchment's stormflow generation during dormant/growing seasons, using daily scale observations of streamflow and precipitation. …”
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Reservoir Stochastic Simulation Based on Octave Convolution and Multistage Generative Adversarial Network by Xuechao Wu, Wenyao Fan, Shijie Peng, Bing Qin, Qing Wang, Mingjie Li, Yang Li

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Scale symmetry breaking and generation of mass at quantum critical points by Charlie Cresswell-Hogg, Daniel F. Litim

“…Exactly at the endpoint, scale symmetry is broken spontaneously, leading to the generation of fermion mass. …”
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Joint Cognition: Thought Contagion and the Consequences of Cooperation when Sharing the Task of Random Sequence Generation. by John Nicholas Towse, Andrea Sarah Towse, Satoru Saito, Yukio Maehara, Akira Miyake

“…Generating random number sequences is a popular psychological task often used to measure executive functioning. …”
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Research on privacy data security sharing scheme based on blockchain and function encryption by Yi LI, Jinsong WANG, Hongwei ZHANG

“…Blockchain technology has provided new ideas for data validation, data traceability, data trustworthiness, and data availability in data sharing, but privacy data security in data sharing still faces many challenges.Firstly, the current status of blockchain-based data sharing research was reviewed.Then a secure sharing model of privacy data was proposed.By encrypting the privacy data through function cryptography, and generating the proof of computational correctness through zero-knowledge proof technology, a secure and reliable data sharing with “data available but not visible” was realized.The experimental results show that the sharing delay and economic overhead of the model are within the acceptable range, which demonstrates the security and feasibility of the model.…”
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Developing generative AI functionalities in a social LMS by Mengyuan Zhao, Puja Kumari, Eashwar Madhavan Perumal, Zhen Hou

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Subjective Evaluation of Generative AI-Driven Dialogues in Paired Dyadic and Topic-Sharing Triadic Interaction Structures by Kaori Abe, Changqin Quan, Sheng Cao, Zhiwei Luo

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Blockchain-Based Modified AES with Chaotic Random Key Generation for Secured E-Medical Data Sharing by Vinothkumar.M, R. Saravana Ram

“…Though traditional methods have used algorithms based on these concepts for secured EMD sharing, they lacked with regard for privacy and security. …”
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Superfield twist-2 operators in N $$ \mathcal{N} $$ = 1 SCFTs and their renormalization-group improved generating functional in N $$ \mathcal{N} $$ = 1 SYM theory by Giacomo Santoni, Francesco Scardino

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Integrating surveying, photogrammetric, and remote sensing data to generate large-scale maps by Przemysław Klapa, Pelagia Gawronek, Tadeusz Gargula, Agnieszka Sokołowska, Kamil Sajdak

“…Information acquired this way, supplemented with spatial data from official (state-controlled) surveying and cartographic resources, paves the way for generating large-scale maps, including the master map, in line with applicable legal and technical requirements. …”
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Large-Scale Periodic Gust Generation and Spectral Analysis Approach for Characterization and Evaluation by Berk Zaloglu, Oksan Cetiner

“… Generating a periodic continuous gust in a controlled manner and at sufficiently large scales for the gust encounter studies on MAV applications is a challenge. …”
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Direct Conditional Score Modeling for Accelerated MRI Reconstruction by Hongki Lim

“…This paper presents a novel approach called Direct Conditional Score (DCS) modeling that directly models the conditional score function, eliminating the need for separate likelihood terms. …”
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Time series generation model based on multi-discriminator generative adversarial network by Yanhui LU, Han LIU, Hang LI, Guangxu ZHU

“…Aiming at the problems of expensive collection cost and missing data due to the privacy and continuity of time series data set, a multi-discriminator generative adversarial network model based on recurrent neural network was proposed, which could synthesize time series dataset that were approximately distributed with real data of a small scale dataset.Multi-discriminator included four discriminators in time domain, frequency domain, time-frequency domain and autocorrelation.Different discriminators could effectively recognize the features of the time series in different domains.In the experiment, the convergence of loss function, principal component analysis and error analysis were performed to evaluate the performance of the model from qualitative and quantitative perspectives.The experimental results show that the proposed model has better performance than other reference models.…”
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