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arXiv 2025年

作者： Hur, Matthew Bartol, Thomas Rangamani, Padmini Sejnowski, Terrence Mjolsness, Eric Program in Mathematical Computational and Systems Biology Univeristy of California Irvine IrvineCA United States Computational Neurobiology Laboratory Salk Institute for Biological Studies La Jolla CA United States Departments of Pharmacology and Mechanical and Aerospace Engineering University of California San Diego La Jolla CA United States Deparment of Neurobiology University of California San Diego La Jolla CA United States Departments of Computer Science and Mathematics Univeristy of California Irvine IrvineCA United States

There is a morphodynamic component to synaptic learning by which changes in dendritic (postsynaptic) spine head size are associated with the strengthening or weakening of the synaptic connection between two neurons, in response to the temporal correlation of local presynaptic and postsynaptic signals. These morphological factors are in turn sculpted by the dynamics of the actin cytoskeleton. In this paper, we use Dynamical Graph Grammars (DGGs) implemented within a computer algebra system to model how networks of actin filaments can dynamically grow or shrink, reshaping the spine head. Dynamical Graph Grammars (DGGs) provide a well-defined way to accommodate dynamically changing system structure such as active cytoskeleton represented using dynamic graphs, within nonequilibrium statistical physics under the master equation. We show that DGGs can also incorporate biophysical forces between graph-connected objects at a finer time scale, with specialized DGG kinetic rules obeying biophysical constraints of Galilean invariance, conservation of momentum, and dissipation of conserved global energy. We use graph-local energy functions for cytoskeleton networks interacting with membranes, and derive DGG rules from the specialization of dissipative stochastic dynamics - separated into dissipative and thermal noise rule types - to a mutually exclusive and exhaustive collection of graph-local neighborhood types for the rule left hand sides. The dissipative rules comprise a stochastic version of gradient descent dynamics. The thermal noise rules use a Gaussian approximation of each position coordinate to sample jitter-like displacements. For the spine head model we designed and implemented DGG grammar mathematical sub-models including actin network growth, non-equilibrium statistical mechanics, and filament-membrane mechanical interaction to regulate the re-writing of graph objects. We simulate emergent biophysics of simplified networks of actin polymers and their interactions

关键词： Stochastic models

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A Framework for Moving from Traditional to Smart University

A Framework for Moving from Traditional to Smart University

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International Conference on Computing for Sustainable Global Development (INDIACom)

作者： Adnan Ahmed Abi Sen Yaser Mohammed Aljohani Abdulelah Alhussain Hassan Hakami Nour Mahmoud Bahbouh Ahmad Alkhodre Mohammed S. Alghamdi Computing and Information Technology Islamic University Al-Madinah Saudi Arabia YasRef Program Yanbu Saudi Arabia Saudi Electronic University Al-Madinah Saudi Arabia Department of Information and Communication Sciences Granada University Granada Spain Faculty of Computer and Information Systems Islamic University Al-Madinah Saudi Arabia Faculty of the Holy Quran and Islamic Studies Islamic University Al-Madinah Saudi Arabia

The revolution of technologies and communications pushed for smarter applications and services. A smart university has become a target for educational institutions in many countries in the last few years. The smart-university provides many advantages in all aspects: academic, administrative, and research. Transformation to a smart university will save time, effort, and cost, in addition to increasing the quality of services, users' satisfaction, and sustainability. This research provided reviewing study for the most important standards, services, applications, and tools that must be present in smart universities. Then, the research proposed a framework to transform universities into smart ones. In recent years, the Kingdom of Saudi Arabia (KSA) is considered one of the leading countries in the field of digital transformation. So, in the next phase, we will try to apply the proposed framework in one of the KSA universities.

关键词： Heuristic algorithms Digital transformation Urban areas Education Transforms Quality of service Internet of Things

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Queue Management Priority-Based Traffic Engineering Method

Queue Management Priority-Based Traffic Engineering Method

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International Scientific-Practical Conference Problems of Infocommunications Science and Technology

作者： Oleksandr Lemeshko Oleksandra Yeremenko Anatoliy Persikov Maryna Yevdokymenko Amal Mersni Serhii Harkusha V.V. Popovskyy Department of Infocommunication Engineering Kharkiv National University of Radio Electronics Kharkiv Ukraine Department of Engineering Computer Sciences and Engineering Program International University of Sarajevo Sarajevo Bosnia and Herzegovina Department of Document Studies and Information Activities in Economic Systems Poltava University of Economics and Trade Poltava Ukraine

The work proposes the improvement of queue management priority-based Traffic Engineering method. It is based on the interaction prediction principle to coordinate decisions at various levels. The lower level of calculations is responsible, firstly, for the distribution and aggregation of packet flows between the macro queues and sub-queues organized on the router interface (congestion management task), and, secondly, for the balanced distribution of interface bandwidth among sub-queues, weighted relative to their priorities (resource allocation task). The upper level of the method's calculations is accountable for distributing the interface's bandwidth between macro queues by performing the iterative procedure. The numerical research results of the proposed two-level queue management method confirmed its effectiveness in ensuring high scalability, balanced priority- based distribution of packet flows and interface bandwidth between the macro queues and sub-queues organized on it. The method demonstrated high coordination procedure convergence and the final quality of centralized calculations.

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Primary Care Informatics Response to Covid-19 Pandemic: Adaptation, Progress, and Lessons from Four Countries with High ICT Development

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Yearbook of Medical Informatics 2021年第1期30卷 44-55页

作者： Liaw, Siaw-Teng Kuziemsky, Craig Schreiber, Richard Jonnagaddala, Jitendra Liyanage, Harshana Chittalia, Aliasgar Bahniwal, Ravninder He, Jennifer W. Ryan, Bridget L. Lizotte, Daniel J. Kueper, Jacqueline K. Terry, Amanda L. de Lusignan, Simon WHO Collaborating Centre on eHealth UNSW Sydney Australia MacEwan University Edmonton AB Canada Penn State Health Holy Spirit Medical Center Camp Hill PA United States Nuffield Department of Primary Care Health Sciences University of Oxford United Kingdom Family Practice Center PA United States Schulich Interfaculty Program in Public Health Western University London Canada Graduate Program in Epidemiology and Biostatistics Western University London Canada Centre for Studies in Family Medicine Department of Family Medicine Western University London Canada Department of Computer Science Western University London Canada

OBJECTIVE: Internationally, primary care practice had to transform in response to the COVID pandemic. Informatics issues included access, privacy, and security, as well as patient concerns of equity, safety, quality, and trust. This paper describes progress and lessons learned. METHODS: IMIA Primary Care Informatics Working Group members from Australia, Canada, United Kingdom and United States developed a standardised template for collection of information. The template guided a rapid literature review. We also included experiential learning from primary care and public health perspectives. RESULTS: All countries responded rapidly. Common themes included rapid reductions then transformation to virtual visits, pausing of non-COVID related informatics projects, all against a background of non-standardized digital development and disparate territory or state regulations and guidance. Common barriers in these four and in less-resourced countries included disparities in internet access and availability including bandwidth limitations when internet access was available, initial lack of coding standards, and fears of primary care clinicians that patients were delaying care despite the availability of televisits. CONCLUSIONS: Primary care clinicians were able to respond to the COVID crisis through telehealth and electronic record enabled change. However, the lack of coordinated national strategies and regulation, assurance of financial viability, and working in silos remained limitations. The potential for primary care informatics to transform current practice was highlighted. More research is needed to confirm preliminary observations and trends noted. IMIA and Thieme. This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, tran

关键词： health policy Primary Health Care public health severe acute respiratory syndrome coronavirus 2 Telemedicine

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Genie: A new, fast, and outlier-resistant hierarchical clustering algorithm

arXiv

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arXiv 2022年

作者： Gagolewski, Marek Bartoszuk, Maciej Cena, Anna Systems Research Institute Polish Academy of Sciences ul. Newelska 6 Warsaw01-447 Poland Faculty of Mathematics and Information Science Warsaw University of Technology ul. Koszykowa 75 Warsaw00-662 Poland International PhD Studies Program Institute of Computer Science Polish Academy of Sciences Poland

The time needed to apply a hierarchical clustering algorithm is most often dominated by the number of computations of a pairwise dissimilarity measure. Such a constraint, for larger data sets, puts at a disadvantage the use of all the classical linkage criteria but the single linkage one. However, it is known that the single linkage clustering algorithm is very sensitive to outliers, produces highly skewed dendrograms, and therefore usually does not reflect the true underlying data structure - unless the clusters are well-separated. To overcome its limitations, we propose a new hierarchical clustering linkage criterion called Genie. Namely, our algorithm links two clusters in such a way that a chosen economic inequity measure (e.g., the Gini- or Bonferroni-index) of the cluster sizes does not increase drastically above a given threshold. The presented benchmarks indicate a high practical usefulness of the introduced method: it most often outperforms the Ward or average linkage in terms of the clustering quality while retaining the single linkage speed. The Genie algorithm is easily parallelizable and thus may be run on multiple threads to speed up its execution further on. Its memory overhead is small: there is no need to precompute the complete distance matrix to perform the computations in order to obtain a desired clustering. It can be applied on arbitrary spaces equipped with a dissimilarity measure, e.g., on real vectors, DNA or protein sequences, images, rankings, informetric data, etc. A reference implementation of the algorithm has been included in the open source genie package for R. [See https://genieclust. gagolewski. com for a new implementation - available for both R and Python.]. © 2022, CC BY.

关键词： Clustering algorithms

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A comparative forecasting model of COVID-19 case in Indonesia 7

A comparative forecasting model of COVID-19 case in Indonesi...

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7th International Conference on Mathematics, Science, and Education 2020, ICMSE 2020

作者： Septiarini, T.W. Taufik, M.R. Prasetya, T.A.E. Department of Islamic Economics Faculty of Economics and Management University of Darussalam Gontor Ponorogo Indonesia Department of Occupational Safety and Health Faculty of Health Science University of Darussalam Gontor Ponorogo Indonesia Occupational Safety and Health Department Faculty of Vocational Studies University of Airlangga Surabaya Indonesia Research Methodology Program Department of Mathematics and Computer Science Faculty of Science and Technology Prince of Songkla University Pattani Campus Thailand

COVID-19 had been a disaster in Indonesia. Moreover, it is needed a study to analyze the trend of this case. The objectives of this study were (1) to propose the model for predicting COVID-19 using exponential smoothing, autoregressive integrated moving average (ARIMA), neural network, and fuzzy time series and (2) to compare the performance for each model by using RMSE as evaluation tool. In this study, the splitting data is implemented by 3:1 ratio on train and test data set. The results show that the neural network has the smallest error, 772.46 for RMSE. It means that neural network perform better than other forecasting model. Once, the characteristic data had big impact to building forecasting model whether in classical or modern model. © Published under licence by IOP Publishing Ltd.

关键词： COVID-19

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Implementing ASLNet V1.0: Progress and plans 11

Implementing ASLNet V1.0: Progress and plans

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11th Global Wordnet Conference, GWC 2021

作者： Lualdi, Colin P. Wright, Elaine Hudson, Jack Caselli, Naomi K. Fellbaum, Christiane SignSchool Inc. MadisonWI United States Department of Physics University of Illinois Urbana-ChampaignIL United States Department of Electrical Engineering Princeton University PrincetonNJ United States Program in Linguistics Princeton University PrincetonNJ United States Programs in Deaf Studies Boston University BostonMA United States Department of Computer Science Princeton University PrincetonNJ United States

ISBN: (纸本)9789464027310

We report on the development of ASLNet, a wordnet for American Sign Language (ASL). ASLNet V1.0 is currently under construction by mapping easy-to-translate ASL lexical nouns to Princeton WordNet synsets. We describe our data model and mapping approach, which can be extended to any sign language. Analysis of the 390 synsets processed to date indicates the success of our procedure yet also highlights the need to supplement our mapping with the "merge" method. We outline our plans for upcoming work to remedy this, which include use of ASL free-association data. © GWC 2021. All rights reserved.

关键词： Mapping

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Surrogate approximation of the grad-shafranov free boundary problem via stochastic collocation on sparse grids

arXiv

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arXiv 2021年

作者： Elman, Howard C. Liang, Jiaxing Sánchez-Vizuet, Tonatiuh Department of Computer Science Institute for Advanced Computer Studies University of Maryland College Park United States Applied Mathematics & Statistics and Scientific Computing Program University of Maryland College Park United States Courant Institute of Mathematical Sciences New York University Department of Mathematics The University of Arizona

In magnetic confinement fusion devices, the equilibrium configuration of a plasma is determined by the balance between the hydrostatic pressure in the fluid and the magnetic forces generated by an array of external coils and the plasma itself. The location of the plasma is not known a priori and must be obtained as the solution to a free boundary problem. The partial differential equation that determines the behavior of the combined magnetic field depends on a set of physical parameters (location of the coils, intensity of the electric currents going through them, magnetic permeability, etc.) that are subject to uncertainty and variability. The confinement region is in turn a function of these stochastic parameters as well. In this work, we consider variations on the current intensities running through the external coils as the dominant source of uncertainty. This leads to a parameter space of dimension equal to the number of coils in the reactor. With the aid of a surrogate function built on a sparse grid in parameter space, a Monte Carlo strategy is used to explore the effect that stochasticity in the parameters has on important features of the plasma boundary such as the location of the x-point, the strike points, and shaping attributes such as triangularity and elongation. The use of the surrogate function reduces the time required for the Monte Carlo simulations by factors that range between 7 and over *** Codes 65C30, 65C05, 65N35, 65N99, 65Z05 Copyright © 2021, The Authors. All rights reserved.

关键词： Monte Carlo methods

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Emergent dimer-model topological order and quasi-particle excitations in liquid crystals: combinatorial vortex lattices

arXiv

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arXiv 2025年

作者： Meng, Cuiling Wu, Jin-Sheng Kos, Žiga Dunkel, Jörn Nisoli, Cristiano Smalyukh, Ivan I. Department of Physics and Chemical Physics Program University of Colorado BoulderCO80309 United States Hiroshima University Hiroshima Higashihiroshima Japan Department of Mathematics Massachusetts Institute of Technology CambridgeMA02139 United States Faculty of Mathematics and Physics University of Ljubljana Ljubljana Slovenia Department of Condensed Matter Physics Jožef Stefan Institute Ljubljana Slovenia Theoretical Division Physics of Condensed Matter and Complex Systems Center For Nonlinear Studies Los Alamos National Laboratory Los AlamosNM87545 United States Department of Electrical Computer and Energy Engineering Materials Science and Engineering Program University of Colorado BoulderCO80309 United States Renewable and Sustainable Energy Institute National Renewable Energy Laboratory University of Colorado BoulderCO80309 United States

Liquid crystals have proven to provide a versatile experimental and theoretical platform for studying topological objects such as vortices, skyrmions, and hopfions. In parallel, in hard condensed matter physics, the concept of topological phases and topological order has been introduced in the context of spin liquids to investigate emergent phenomena like quantum Hall effects and high-temperature superconductivity. Here, we bridge these two seemingly disparate perspectives on topology in physics. Combining experiments and simulations, we show how topological defects in liquid crystals can be used as versatile building blocks to create complex, highly degenerate topological phases, which we refer to as ‘Combinatorial Vortex Lattices’ (CVLs). CVLs exhibit extensive residual entropy and support locally stable quasi-particle excitations in the form of charge-conserving topological monopoles, which can act as mobile information carriers and be linked via Dirac strings. CLVs can be rewritten and reconfigured on demand, endowed with various symmetries, and modified through laser-induced topological surgery — an essential capability for information storage and retrieval. We demonstrate experimentally the realization, stability, and precise optical manipulation of CVLs, thus opening new avenues for understanding and technologically exploiting higher-hierarchy topology in liquid crystals and other ordered media. Copyright © 2025, The Authors. All rights reserved.

关键词： Laser surgery

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Intrusion Detection using Deep Neural Network Algorithm on the Internet of Things

Intrusion Detection using Deep Neural Network Algorithm on t...

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IEEE International Conference on Communication, Networks and Satellite (ComNetSat)

作者： Syariful Ikhwan Adi Wibowo Budi Warsito Doctoral Program of Information System School of Postgraduate Studies Diponegoro University Semarang Indonesia D3 Telecommunication Engineering Institut Teknologi Telkom Purwokerto Banyumas Indonesia Computer Science Informatics Department of Science and Mathematics Faculty Diponegoro University Semarang Indonesia Statistics Department of Science and Mathematics Faculty Diponegoro University Semarang Indonesia

ISBN: (数字)9781665460309

ISBN: (纸本)9781665460316

The increasing use of IoT devices on future networks is very helpful for humans in their lives. However, the increase in devices connected to IoT networks also increases the potential for attacks against those networks. Vulnerabilities in Internet of Things (IoT) networks can be exposed at any time. Artificial intelligence can be used to protect the IoT network by being able to detect attacks on the network so that they can be prevented. In this study, network detection was carried out using the Deep Neural Network (DNN) algorithm. The test was carried out using the UNSW Bot-IoT dataset with a comparison of training data of 75% of the overall data. The results obtained show the ability of the algorithm to detect attacks on average with 99.999% accuracy. The validation loss and training loss look very small. In this study, there is a validation loss that still occurs in overfitting, but the difference is very small.

关键词： Deep learning Training Satellites Neural networks Intrusion detection Training data Feature extraction

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