cometadata/datacite-rtg-text-other-reclassification-records huggingface dataset:
A_Comparison_of_SVM_and_RVM_for_Human_Ac.pdf
Creators: name: Fanany, Mohamad Ivan
Publisher: name: figshare
Year: 2016
Subjects: subject: 170203 Knowledge Representation and Machine Learning
subject: FOS: Psychology
subject: Artificial Intelligence and Image Processing
subject: FOS: Computer and information sciences

description: Human action recognition is a task of analyzing
human action that occurs in a video. This paper investigates
action recognition by using two classification techniques, namely Relevance Vector Machine (RVM) and Support Vector Machine (SVM). SVM is a technique for supervised classification that used in statistics and machine learning. By separating the distinct class with a maximum possible wide gap, SVM tries to predict the respective class given a set of input data. On the other hand, RVM is a Bayesian model of Generalized Linear Model (GLM) that have an identical function with SVM. RVM uses significantly fewer basis functions as it uses Bayesian inference with a prior distribution on weight thus makes solution sparse. Experimental studies on a human action dataset show that RVM is better as compared to SVM on action recognition. Although RVM takes more training time, however, it requires fewer testing time than SVM. RVM model is more generalized because it contains minimum basis function, therefore, it more robust. RVM performs good classification on action recognition that contains large dataset.
Reconfiguring Graph Homomorphisms on the Sphere
Creators: name: Lee, Jae-Baek
name: Noel, Jonathan A.
name: Siggers, Mark
Publisher: name: arXiv
Year: 2018
Subjects: subject: Combinatorics (math.CO)
subject: Computational Complexity (cs.CC)
subject: Discrete Mathematics (cs.DM)
subject: FOS: Mathematics
subject: FOS: Computer and information sciences

description: Given a loop-free graph $H$, the reconfiguration problem for homomorphisms to $H$ (also called $H$-colourings) asks: given two $H$-colourings $f$ of $g$ of a graph $G$, is it possible to transform $f$ into $g$ by a sequence of single-vertex colour changes such that every intermediate mapping is an $H$-colouring? This problem is known to be polynomial-time solvable for a wide variety of graphs $H$ (e.g. all $C_4$-free graphs) but only a handful of hard cases are known. We prove that this problem is PSPACE-complete whenever $H$ is a $K_{2,3}$-free quadrangulation of the $2$-sphere (equivalently, the plane) which is not a $4$-cycle. From this result, we deduce an analogous statement for non-bipartite $K_{2,3}$-free quadrangulations of the projective plane. This include several interesting classes of graphs, such as odd wheels, for which the complexity was known, and $4$-chromatic generalized Mycielski graphs, for which it was not.
 If we instead consider graphs $G$ and $H$ with loops on every vertex (i.e. reflexive graphs), then the reconfiguration problem is defined in a similar way except that a vertex can only change its colour to a neighbour of its current colour. In this setting, we use similar ideas to show that the reconfiguration problem for $H$-colourings is PSPACE-complete whenever $H$ is a reflexive $K_{4}$-free triangulation of the $2$-sphere which is not a reflexive triangle. This proof applies more generally to reflexive graphs which, roughly speaking, resemble a triangulation locally around a particular vertex. This provides the first graphs for which $H$-Recolouring is known to be PSPACE-complete for reflexive instances.
description: 22 pages, 9 figures
Stacked Denoising Autoencoder for feature representation learning in pose-based action recognition
Creators: name: Fanany, Mohamad Ivan
Publisher: name: figshare
Year: 2016
Subjects: subject: Applied Computer Science
subject: 80602 Computer-Human Interaction
subject: FOS: Psychology
subject: 80104 Computer Vision
subject: FOS: Computer and information sciences
subject: 170201 Computer Perception, Memory and Attention

description: In this paper, we studied Stacked Denoising Autoencoder(SDA) model for Human pose-based action recognition. We used public dataset Chalearn 2013 which contains Italian body language actions from 27 persons. We studied two model of SDA for pose clustering: 1) Traditional SDA with epoch and Neural Network supervised classifier and 2) Marginalized SDA which faster and ELM supervised classifier. We used supervised classifier by using initial cluster data from K-means. We deployed global tuning that updating the weight during iterative learning.
A variational principle in the parametric geometry of numbers
Creators: name: Das, Tushar
name: Fishman, Lior
name: Simmons, David
name: Urbański, Mariusz
Publisher: name: arXiv
Year: 2019
Subjects: subject: Number Theory (math.NT)
subject: Dynamical Systems (math.DS)
subject: FOS: Mathematics
subject: 11K55, 11J13 (primary), 28A80, 28A78, 37A15, 37A17, 37C85, 37D40, 91A05, 91A44 (secondary)

description: We extend the parametric geometry of numbers (initiated by Schmidt and Summerer, and deepened by Roy) to Diophantine approximation for systems of $m$ linear forms in $n$ variables, and establish a new connection to the metric theory via a variational principle that computes fractal dimensions of a variety of sets of number-theoretic interest. The proof relies on two novel ingredients: a variant of Schmidt's game capable of computing the Hausdorff and packing dimensions of any set, and the notion of templates, which generalize Roy's rigid systems. In particular, we compute the Hausdorff and packing dimensions of the set of singular systems of linear forms and show they are equal, resolving a conjecture of Kadyrov, Kleinbock, Lindenstrauss and Margulis, as well as a question of Bugeaud, Cheung and Chevallier. As a corollary of Dani's correspondence principle, the divergent trajectories of a one-parameter diagonal action on the space of unimodular lattices with exactly two Lyapunov exponents with opposite signs has equal Hausdorff and packing dimensions. Other applications include quantitative strengthenings of theorems due to Cheung and Moshchevitin, which originally resolved conjectures due to Starkov and Schmidt respectively; as well as dimension formulas with respect to the uniform exponent of irrationality for simultaneous and dual approximation in two dimensions, completing partial results due to Baker, Bugeaud, Cheung, Chevallier, Dodson, Laurent and Rynne.
description: now with a uniform version of the main variational principle
KLASIFIKASI FASE PERTUMBUHAN PADI BERDASARKAN CITRA HIPERSPEKTRAL DENGAN MODIFIKASI LOGIKA FUZZY (PADDY GROWTH STAGES CLASSIFICATION BASED ON HYPERSPECTRAL IMAGE USING MODIFIED FUZZY LOGIC)
Creators: name: Fanany, Mohamad Ivan
Publisher: name: figshare
Year: 2016
Subjects: subject: Applied Computer Science
subject: 80108 Neural, Evolutionary and Fuzzy Computation
subject: FOS: Computer and information sciences
subject: 170203 Knowledge Representation and Machine Learning
subject: FOS: Psychology

description: Remote sensing is a technology that is capable of overcoming the problems of measurement data for fast and accurate information. One of implementation of remote sensing technology in the field of agriculture is in hyperspectral image data retrieval to find out the condition and age of the rice plant. It is necessary for the estimation of rice yield in order to support Government policy in conducting imports rice to meet food needs in Indonesia. To have a good prediction model in estimation of rice yield that has high accuracy must be preceded by the determination of the phase of the rice plant. The selection of the appropriate classifier must also supported the selection of just the right features to get the optimum accuracy. In this study, we conducted a comparison between Fuzzy Logic and Modified Fuzzy Logic to perform the classification on nine rice growth stages based on hyperspectral image. Modified Fuzzy Logic have the same procedure with Fuzzy Logic but with extra crisp rules given in Fuzzy Rules which is expected to increase the accuracy achievement. In this study, Modified Fuzzy Logic proved to be able to improve the accuracy of up to 10% compared to Fuzzy Logic.
DP-colorings of uniform hypergraphs and splittings of Boolean hypercube into faces
Creators: name: Potapov, Vladimir N.
Publisher: name: arXiv
Year: 2019
Subjects: subject: Combinatorics (math.CO)
subject: FOS: Mathematics
subject: 05C15, 05C65, 05C35, 05B05, 51E05

description: We develop a connection between DP-colorings of $k$-uniform hypergraphs of order $n$ and coverings of $n$-dimensional Boolean hypercube by pairs of antipodal $(n-k)$-dimensional faces. Bernshteyn and Kostochka established that the lower bound on edges in a non-2-DP-colorable $k$-uniform hypergraph is equal to $2^{k-1}$ for odd $k$ and $2^{k-1}+1$ for even $k$. They proved that these bounds are tight for $k=3,4$. In this paper, we prove that the bound is achieved for all odd $k\geq 3$.
description: The previous versions of paper contains a significant error
Generalization in Transfer Learning
Creators: name: Ada, Suzan Ece
name: Ugur, Emre
name: Akin, H. Levent
Publisher: name: arXiv
Year: 2019
Subjects: subject: Machine Learning (cs.LG)
subject: Artificial Intelligence (cs.AI)
subject: Robotics (cs.RO)
subject: Machine Learning (stat.ML)
subject: FOS: Computer and information sciences

description: Agents trained with deep reinforcement learning algorithms are capable of performing highly complex tasks including locomotion in continuous environments. We investigate transferring the learning acquired in one task to a set of previously unseen tasks. Generalization and overfitting in deep reinforcement learning are not commonly addressed in current transfer learning research. Conducting a comparative analysis without an intermediate regularization step results in underperforming benchmarks and inaccurate algorithm comparisons due to rudimentary assessments. In this study, we propose regularization techniques in deep reinforcement learning for continuous control through the application of sample elimination, early stopping and maximum entropy regularized adversarial learning. First, the importance of the inclusion of training iteration number to the hyperparameters in deep transfer reinforcement learning will be discussed. Because source task performance is not indicative of the generalization capacity of the algorithm, we start by acknowledging the training iteration number as a hyperparameter. In line with this, we introduce an additional step of resorting to earlier snapshots of policy parameters to prevent overfitting to the source task. Then, to generate robust policies, we discard the samples that lead to overfitting via a method we call strict clipping. Furthermore, we increase the generalization capacity in widely used transfer learning benchmarks by using maximum entropy regularization, different critic methods, and curriculum learning in an adversarial setup. Subsequently, we propose maximum entropy adversarial reinforcement learning to increase the domain randomization. Finally, we evaluate the robustness of these methods on simulated robots in target environments where the morphology of the robot, gravity, and tangential friction coefficient of the environment are altered.
description: 23 pages, 36 figures
Neural Memory Networks for Seizure Type Classification
Creators: name: Ahmedt-Aristizabal, David
name: Fernando, Tharindu
name: Denman, Simon
name: Petersson, Lars
name: Aburn, Matthew J.
name: Fookes, Clinton
Publisher: name: arXiv
Year: 2019
Subjects: subject: Signal Processing (eess.SP)
subject: Machine Learning (cs.LG)
subject: Neural and Evolutionary Computing (cs.NE)
subject: Machine Learning (stat.ML)
subject: FOS: Electrical engineering, electronic engineering, information engineering
subject: FOS: Computer and information sciences

description: Classification of seizure type is a key step in the clinical process for evaluating an individual who presents with seizures. It determines the course of clinical diagnosis and treatment, and its impact stretches beyond the clinical domain to epilepsy research and the development of novel therapies. Automated identification of seizure type may facilitate understanding of the disease, and seizure detection and prediction has been the focus of recent research that has sought to exploit the benefits of machine learning and deep learning architectures. Nevertheless, there is not yet a definitive solution for automating the classification of seizure type, a task that must currently be performed by an expert epileptologist. Inspired by recent advances in neural memory networks (NMNs), we introduce a novel approach for the classification of seizure type using electrophysiological data. We first explore the performance of traditional deep learning techniques which use convolutional and recurrent neural networks, and enhance these architectures by using external memory modules with trainable neural plasticity. We show that our model achieves a state-of-the-art weighted F1 score of 0.945 for seizure type classification on the TUH EEG Seizure Corpus with the IBM TUSZ preprocessed data. This work highlights the potential of neural memory networks to support the field of epilepsy research, along with biomedical research and signal analysis more broadly.
description: Proceedings of the IEEE International Conference of Engineering in Medicine and Biology Society. 2020
Modiﬁed PSO Algorithm for Odor Source Localization Problems: Progress and Challenge
Creators: name: Fanany, Mohamad Ivan
Publisher: name: figshare
Year: 2016
Subjects: subject: 80101 Adaptive Agents and Intelligent Robotics
subject: FOS: Computer and information sciences
subject: 90602 Control Systems, Robotics and Automation
subject: FOS: Electrical engineering, electronic engineering, information engineering
subject: Computer Engineering
subject: 170201 Computer Perception, Memory and Attention
subject: FOS: Psychology
subject: Applied Computer Science
subject: Computer Software

description: Research using the Particle Swarm Optimization (PSO) with robots as agents for solving odor source localization in dynamic advection-diffusion environment had been developed. Simulation and realworld implementation are used to verify the robustness of PSO for odor source localization. Result verifies that PSO is feasible to be implemented either simulation orreal-world implementation. To enhance the potency of PSO, a new algorithm based on PSO which can handle the environmental change is investigated. Modification involves the capability to follow a local gradient of the chemical concentration within a plume and follow direction of the wind velocity. Moreover, the simultaneous search done by many groups of robots is adopted on Modified PSO (MPSO) to solve the multi-peak and multisource problem. Some modification is needed on the parallel search to handle multiple groups which following the same sources. Then ODE (Open Dynamics Engine) library is used for physical modeling of the robot like friction, balancing moment and the other. Finally the statistical analysis shows that the MPSO is technically sounds.
Model reduction in Smoluchowski-type equations
Creators: name: Timokhin, Ivan V.
name: Matveev, Sergey A.
name: Tyrtyshnikov, Eugene E.
name: Smirnov, Alexander P.
Publisher: name: arXiv
Year: 2020
Subjects: subject: Numerical Analysis (math.NA)
subject: FOS: Mathematics
subject: G.1.3; G.1.7

description: In this paper we utilize the Proper Orthogonal Decomposition (POD) method for model order reduction in application to Smoluchowski aggregation equations with source and sink terms. In particular, we show in practice that there exists a low-dimensional space allowing to approximate the solutions of aggregation equations. We also demonstrate that it is possible to model the aggregation process with the complexity depending only on dimension of such a space but not on the original problem size. In addition, we propose a method for reconstruction of the necessary space without solving of the full evolutionary problem, which can lead to significant acceleration of computations, examples of which are also presented.
description: 16 pages, 4 figures, 3 tables
Uniruledness of some low-dimensional ball quotients
Creators: name: Maeda, Yota
Publisher: name: arXiv
Year: 2020
Subjects: subject: Number Theory (math.NT)
subject: Algebraic Geometry (math.AG)
subject: FOS: Mathematics
subject: Primary 14G35, Secondary 11G18, 11E39

description: We define reflective modular forms on complex balls and use a method of Gritsenko and Hulek to show that some ball quotients of dimensions 3, 4 and 5 are uniruled. We give examples of Hermitian lattices over the rings of integers of imaginary quadratic fields $\mathbb{Q}(\sqrt{-1})$ and $\mathbb{Q}(\sqrt{-2})$ for which the associated ball quotients are uniruled. Our examples include the moduli space of 8 points on $\mathbb{P}^1$. Moreover, we find that some of their Satake-Baily-Borel compactifications are rationally chain connected modulo certain cusps.
Theoretical Analysis of the Advantage of Deepening Neural Networks
Creators: name: Esaki, Yasushi
name: Nakahara, Yuta
name: Matsushima, Toshiyasu
Publisher: name: arXiv
Year: 2020
Subjects: subject: Machine Learning (cs.LG)
subject: Neural and Evolutionary Computing (cs.NE)
subject: Machine Learning (stat.ML)
subject: FOS: Computer and information sciences
subject: I.2.6; I.5.1

description: We propose two new criteria to understand the advantage of deepening neural networks. It is important to know the expressivity of functions computable by deep neural networks in order to understand the advantage of deepening neural networks. Unless deep neural networks have enough expressivity, they cannot have good performance even though learning is successful. In this situation, the proposed criteria contribute to understanding the advantage of deepening neural networks since they can evaluate the expressivity independently from the efficiency of learning. The first criterion shows the approximation accuracy of deep neural networks to the target function. This criterion has the background that the goal of deep learning is approximating the target function by deep neural networks. The second criterion shows the property of linear regions of functions computable by deep neural networks. This criterion has the background that deep neural networks whose activation functions are piecewise linear are also piecewise linear. Furthermore, by the two criteria, we show that to increase layers is more effective than to increase units at each layer on improving the expressivity of deep neural networks.
description: 9 pages, 7 figures; accepted in 19th IEEE International Conference on Machine Learning and Applications (IEEE ICMLA 2020)
Modularity of special cycles on unitary Shimura varieties over CM-fields
Creators: name: Maeda, Yota
Publisher: name: arXiv
Year: 2021
Subjects: subject: Number Theory (math.NT)
subject: FOS: Mathematics

description: We study the modularity of the generating series of special cycles on unitary Shimura varieties over CM-fields of degree $2d$ associated with a Hermitian form in $n+1$ variables whose signature is $(n,1)$ at $e$ real places and $(n+1,0)$ at the remaining $d-e$ real places for $1\leq e 1$, we prove that the generating series of special cycles of codimension $er$ in the Chow group is a Hermitian modular form of weight $n+1$ and genus $r$, assuming the Beilinson-Bloch conjecture with respect to orthogonal Shimura varieties. Our result is a generalization of $\textit{Kudla's modularity conjecture}$, solved by Liu unconditionally when $e=1$.
description: 13 pages
ROBOTS IMPLEMENTATION FOR ODOR SOURCELOCALIZA TION USING PSO ALGORITHM
Creators: name: Fanany, Mohamad Ivan
Publisher: name: figshare
Year: 2016
Subjects: subject: Computer Engineering
subject: 80309 Software Engineering
subject: FOS: Computer and information sciences
subject: 90602 Control Systems, Robotics and Automation
subject: FOS: Electrical engineering, electronic engineering, information engineering
subject: 170203 Knowledge Representation and Machine Learning
subject: FOS: Psychology

description: Research topics in robotic application is quite varies but one of the most interesting topic is odor source localization. This research combine the robot ability to recognize odor and track the movement so that robot can find the source. Most of the research are done to improve the algorithm to localize the source by using simulation software. This paper tries to verify the robustness of one of the localization method known as Particle Swarm Optimization (PSO) in the real-world implementation. This paper will shows robot model that used in the experiment and also discuss the architecture to implement robot behavior. A group of mobile robots equipped with wireless communication device and odor sensors is employed. The experiment is conduct in area of 488cm x 488cm with dynamic odor source in one end. The experiment also used a set of camera to track robots position. The experiement result verifies that PSO is technically sound for real-world odor source localization. In this experiment, PSO can localized the source in 360 seconds or bellow.
DMP Predicting House Sale Prices Using Machine Learning
Creators: name: Grishan, Aleksandra
Publisher: name: Zenodo
Year: 2025
Subjects: Machine Learning
Regression
House Pricing

description: Data Management Plan for the Housing-Price-Prediction project

The original OpenML dataset, containing housing sales records from King County between May 2014 and May 2015, along with the three curated splits (train, validation, and test), is archived in DBRepo (DOIs P1–P4). The final Random Forest, Gradient Boosting, and XGBoost models, together with tuning diagnostics and evaluation reports, are available on GitHub: https://github.com/kusoksaxara/housing-price-prediction.
Décimas glosadas en las que se manifiesta los desprecios que hace una dama a todos los que la pretenden: Digital edition
Creators: name: Leblanc Elina
Publisher: name: Zenodo
Year: 2024
Subjects: Spanish literature
Digital edition
XML-TEI

description: Digital edition of a Spanish pliego de cordel, published by the Andalusian printer José María Moreno (19th c.). It contains the XML-TEI file of the edition, as well as the files that led to this edition, i.e. the digital facsimiles (raw and retouched), and the transcription produced by the OCR tool Transkribus (PAGE-XML). This digital edition is a part of the research project Desenrollando el cordel / Untangling the cordel / Démêler le cordel (2020-2024), led by professor Constance Carta at the University of Geneva and supported by the philanthropic Sandoz-Monique de Meuron Family Foundation.
On the Optimality of the Oja's Algorithm for Online PCA
Creators: name: Liang, Xin
Publisher: name: arXiv
Year: 2021
Subjects: subject: Machine Learning (cs.LG)
subject: Optimization and Control (math.OC)
subject: FOS: Computer and information sciences
subject: FOS: Mathematics
subject: 62H25, 68W27, 65F15

description: In this paper we analyze the behavior of the Oja's algorithm for online/streaming principal component subspace estimation. It is proved that with high probability it performs an efficient, gap-free, global convergence rate to approximate an principal component subspace for any sub-Gaussian distribution. Moreover, it is the first time to show that the convergence rate, namely the upper bound of the approximation, exactly matches the lower bound of an approximation obtained by the offline/classical PCA up to a constant factor.
description: 25 pages. arXiv admin note: text overlap with arXiv:1711.06644
IN03183 Anurādhapura Archaeological Museum Stone Step Inscription
Creators: name: Paranavitana, S.
Publisher: name: Zenodo
Year: 2020
Subjects: IN03183
Epigraphia Zeylanica
Anuradhapura

description: IN03183 Anurādhapura Archaeological Museum Stone Step Inscription - Transcript and Translation Source: Paranavitana, S. (1934–41). ‘No. 17. Seven Sinhalese Inscriptions of the Seventh and Eighth Centuries,’ Epigraphia Zeylanica 4, pp. 144–145, no. 17, IV.
Décimas glosadas en las que se manifiesta los desprecios que hace una dama a todos los que la pretenden: Digital edition
Creators: name: Leblanc Elina
Publisher: name: Zenodo
Year: 2021
Subjects: Spanish literature
Digital edition
XML-TEI

description: Digital edition of a Spanish pliego de cordel, published by the Andalusian printer José María Moreno (19th c.). It contains the XML-TEI file of the edition, as well as the files that led to this edition, i.e. the digital facsimiles (raw and retouched), and the transcription produced by the OCR tool Transkribus (PAGE-XML). This digital edition is a part of the research project Desenrollando el cordel / Untangling the cordel / Démêler le cordel (2020-2022), led by the professor Constance Carta at the University of Geneva and supported by the philanthropic Sandoz-Monique de Meuron Family Foundation.
Towards a dichotomy for the switch list homomorphism problem for signed graphs
Creators: name: Kim, Hyobin
name: Siggers, Mark
Publisher: name: arXiv
Year: 2021
Subjects: subject: Combinatorics (math.CO)
subject: FOS: Mathematics
subject: 05C22 (Primary), 05C85 (Secondary)

description: We make advances towards a structural characterisation of the signed graphs $H$ for which the list switch $H$-colouring problem $\operatorname{LSwHom}(H)$ problem is polynomial time solvable. We conjecture a characterisation for signed graphs that can be switched to graphs such that every negative edge is also positive, and prove the characterisation in the case that the signed graph is reflexive.
Décimas glosadas en las que se manifiesta los desprecios que hace una dama a todos los que la pretenden: Digital edition
Creators: name: Leblanc Elina
Publisher: name: Zenodo
Year: 2022
Subjects: Spanish literature
Digital edition
XML-TEI

description: Digital edition of a Spanish pliego de cordel, published by the Andalusian printer José María Moreno (19th c.). It contains the XML-TEI file of the edition, as well as the files that led to this edition, i.e. the digital facsimiles (raw and retouched), and the transcription produced by the OCR tool Transkribus (PAGE-XML). This digital edition is a part of the research project Desenrollando el cordel / Untangling the cordel / Démêler le cordel (2020-2024), led by the professor Constance Carta at the University of Geneva and supported by the philanthropic Sandoz-Monique de Meuron Family Foundation.
A Unified Framework for Creating Domain Dependent Polarity Lexicons from User Generated Reviews
Creators: name: Zubair Asghar
Publisher: name: figshare
Year: 2015
Subjects: subject: Information Systems
subject: FOS: Computer and information sciences
subject: Computer Software

description: The polarity lexicons often play a pivotal role in the OM, indicating the positivity and negativity of a term along with the numeric score. However, the commonly available domain independent lexicons are not an optimal choice for all of the domains within the OM applications. The aforementioned is due to the fact that the polarity of a term changes from one domain to other and such lexicons do not contain the correct polarity of a term for every domain. In this work, we focus on the problem of adapting a domain dependent polarity lexicon from set of labeled user reviews and domain independent lexicon to propose a unified learning framework based on the information theory concepts that can assign the terms with correct polarity (+ive, -ive) scores. The benchmarking on three datasets (car, hotel, and drug reviews) shows that our approach improves the performance of the polarity classification by achieving higher accuracy.
CARE-checklist-English-2013 sectionwise.pdf
Creators: name: Hossain, Mohammad Ali
name: Rashid, Md Utba
name: Barsha, Sabrina Yesmin
name: Khan, Md. Abdullah Saeed
name: Haque, Miah Md. Akiful
name: Rahman, Mohammad Lutfor
name: Hossian, Mosharop
name: Bhuiyan, AKM Mohiuddin
name: Nabi, Mohammad Hayatun
name: Hawlader, Mohammad Delwer Hossain
Publisher: name: figshare
Year: 2022
Subjects: subject: 110201 Cardiology (incl. Cardiovascular Diseases)
subject: FOS: Clinical medicine

description: CARE Checklist for Case Report: Acute myocardial infarction with acute left ventricular failure and acute renal damage following mRNA-1273 vaccination: Possible adverse effect of COVID-19 vaccination?
Detection and Scoring of Internet Slangs for Sentiment Analysis Using SentiWordNet
Creators: name: Zubair Asghar
Publisher: name: figshare
Year: 2015
Subjects: subject: Information Systems
subject: FOS: Computer and information sciences
subject: Computer Software

description: People express their views about products, events or services using social networking services. These reviewers excessively use Slangs and acronyms to express their views. Therefore, Slang's analysis is essential for sentiment recognition. This paper presents a framework for detection and scoring of Internet Slangs (DSIS) using SentiWordNet in conjunction with other lexical resources
DFT Investigation of Biocatalytic Mechanisms from pH-Driven, Multi-Enzyme, Biomimetic Behavior in CeO2
Creators: name: Ma, Hongyang
name: Liu, Zhao
name: Koshy, Pramod
name: Sorrell, Charles C.
name: Hart, Judy N.
Publisher: name: arXiv
Year: 2021
Subjects: subject: Materials Science (cond-mat.mtrl-sci)
subject: FOS: Physical sciences

description: There is considerable interest in the pH-dependent, switchable, biocatalytic properties of cerium oxide (CeO2) nanoparticles (CeNPs) in biomedicine, where these materials exhibit beneficial antioxidant activity against reactive oxygen species (ROS) at basic physiological pH but cytotoxic prooxidant activity in acidic cancer cell pH microenvironment. While the general characteristics of the role of oxygen vacancies are known, the mechanism of their action at the atomic scale under different pH conditions has yet to be elucidated. The present work applies density functional theory (DFT) calculations to interpret, at the atomic scale, the pH-induced behavior of the stable {111} surface of CeO2 containing oxygen vacancies. Analysis of the surface-adsorbed media species reveals the critical role of pH on the interaction between ROS and the defective CeO2 {111} surface. Under basic conditions, the superoxide dismutase (SOD) and catalase (CAT) biomimetic reactions can be performed cyclically, scavenging and decomposing ROS to harmless products, making CeO2 an excellent antioxidant. However, under acidic conditions, the CAT biomimetic reaction is hindered owing to the limited reversibility of Ce3+ and Ce4+ and formation and annihilation of oxygen vacancies. A Fenton biomimetic reaction is predicted to occur simultaneously with the SOD and CAT biomimetic reactions, resulting in the formation of hydroxyl radicals, making CeO2 a cytotoxic prooxidant.
description: 25 pages, 7 figures
Fano Shimura varieties with mostly branched cusps
Creators: name: Maeda, Yota
name: Odaka, Yuji
Publisher: name: arXiv
Year: 2021
Subjects: subject: Algebraic Geometry (math.AG)
subject: Number Theory (math.NT)
subject: FOS: Mathematics
subject: 14G35 (Primary), 14E99, 11F03, 11E12 (Secondary)

description: We prove that the Satake-Baily-Borel compactification of certain Shimura varieties are Fano varieties, Calabi-Yau varieties or have ample canonical divisors with mild singularities. We also prove some variants statements, give applications and discuss various examples including new ones, for instance, the moduli spaces of unpolarized (log) Enriques surfaces.
description: 33 pages
Pots of Gold at the End of the Rainbow: What is Success for Open Source Contributors?
Creators: name: Trinkenreich, Bianca
name: Guizani, Mariam
name: Wiese, Igor
name: Conte, Tayana
name: Gerosa, Marco
name: Sarma, Anita
name: Steinmacher, Igor
Publisher: name: arXiv
Year: 2021
Subjects: subject: Software Engineering (cs.SE)
subject: FOS: Computer and information sciences

description: Success in Open Source Software (OSS) is often perceived as an exclusively code-centric endeavor. This perception can exclude a variety of individuals with a diverse set of skills and backgrounds, in turn helping create the current diversity & inclusion imbalance in OSS. Because people's perspectives of success affect their personal, professional, and life choices, to be able to support a diverse class of individuals, we must first understand what OSS contributors consider successful. Thus far, research has used a uni-dimensional, code-centric lens to define success. In this paper, we challenge this status-quo and reveal the multi-faceted definition of success among OSS contributors. We do so through interviews with 27 OSS contributors who are recognized as successful in their communities, and a follow-up open survey with 193 OSS contributors. Our study provides nuanced definitions of success perceptions in OSS, which might help devise strategies to attract and retain a diverse set of contributors, helping them attain their "pots of gold at the end of the rainbow".
Towards Interpretable Attention Networks for Cervical Cancer Analysis
Creators: name: Wang, Ruiqi
name: Armin, Mohammad Ali
name: Denman, Simon
name: Petersson, Lars
name: Ahmedt-Aristizabal, David
Publisher: name: arXiv
Year: 2021
Subjects: subject: Computer Vision and Pattern Recognition (cs.CV)
subject: Machine Learning (cs.LG)
subject: Image and Video Processing (eess.IV)
subject: FOS: Computer and information sciences
subject: FOS: Electrical engineering, electronic engineering, information engineering

description: Recent advances in deep learning have enabled the development of automated frameworks for analysing medical images and signals, including analysis of cervical cancer. Many previous works focus on the analysis of isolated cervical cells, or do not offer sufficient methods to explain and understand how the proposed models reach their classification decisions on multi-cell images. Here, we evaluate various state-of-the-art deep learning models and attention-based frameworks for the classification of images of multiple cervical cells. As we aim to provide interpretable deep learning models to address this task, we also compare their explainability through the visualization of their gradients. We demonstrate the importance of using images that contain multiple cells over using isolated single-cell images. We show the effectiveness of the residual channel attention model for extracting important features from a group of cells, and demonstrate this model's efficiency for this classification task. This work highlights the benefits of channel attention mechanisms in analyzing multiple-cell images for potential relations and distributions within a group of cells. It also provides interpretable models to address the classification of cervical cells.
Video-Based Inpatient Fall Risk Assessment: A Case Study
Creators: name: Wang, Ziqing
name: Armin, Mohammad Ali
name: Denman, Simon
name: Petersson, Lars
name: Ahmedt-Aristizabal, David
Publisher: name: arXiv
Year: 2021
Subjects: subject: Computer Vision and Pattern Recognition (cs.CV)
subject: Machine Learning (cs.LG)
subject: FOS: Computer and information sciences

description: Inpatient falls are a serious safety issue in hospitals and healthcare facilities. Recent advances in video analytics for patient monitoring provide a non-intrusive avenue to reduce this risk through continuous activity monitoring. However, in-bed fall risk assessment systems have received less attention in the literature. The majority of prior studies have focused on fall event detection, and do not consider the circumstances that may indicate an imminent inpatient fall. Here, we propose a video-based system that can monitor the risk of a patient falling, and alert staff of unsafe behaviour to help prevent falls before they occur. We propose an approach that leverages recent advances in human localisation and skeleton pose estimation to extract spatial features from video frames recorded in a simulated environment. We demonstrate that body positions can be effectively recognised and provide useful evidence for fall risk assessment. This work highlights the benefits of video-based models for analysing behaviours of interest, and demonstrates how such a system could enable sufficient lead time for healthcare professionals to respond and address patient needs, which is necessary for the development of fall intervention programs.
A Survey on Graph-Based Deep Learning for Computational Histopathology
Creators: name: Ahmedt-Aristizabal, David
name: Armin, Mohammad Ali
name: Denman, Simon
name: Fookes, Clinton
name: Petersson, Lars
Publisher: name: arXiv
Year: 2021
Subjects: subject: Machine Learning (cs.LG)
subject: Computer Vision and Pattern Recognition (cs.CV)
subject: Tissues and Organs (q-bio.TO)
subject: FOS: Computer and information sciences
subject: FOS: Biological sciences

description: With the remarkable success of representation learning for prediction problems, we have witnessed a rapid expansion of the use of machine learning and deep learning for the analysis of digital pathology and biopsy image patches. However, learning over patch-wise features using convolutional neural networks limits the ability of the model to capture global contextual information and comprehensively model tissue composition. The phenotypical and topological distribution of constituent histological entities play a critical role in tissue diagnosis. As such, graph data representations and deep learning have attracted significant attention for encoding tissue representations, and capturing intra- and inter- entity level interactions. In this review, we provide a conceptual grounding for graph analytics in digital pathology, including entity-graph construction and graph architectures, and present their current success for tumor localization and classification, tumor invasion and staging, image retrieval, and survival prediction. We provide an overview of these methods in a systematic manner organized by the graph representation of the input image, scale, and organ on which they operate. We also outline the limitations of existing techniques, and suggest potential future research directions in this domain.
description: Preprint submitted to Computerized Medical Imaging and Graphics
Anisotropic flow and correlations between azimuthal anisotropy Fourier harmonics in Xe-Xe collisions at $\sqrt{s_{NN}}$ = 5.44 TeV under HYDJET++ framework
Creators: name: Pandey, Saraswati
name: Singh, B. K.
Publisher: name: arXiv
Year: 2021
Subjects: subject: High Energy Physics - Phenomenology (hep-ph)
subject: FOS: Physical sciences

description: The study of anisotropic harmonic flow coefficients $ v_{n}$(n=2,3,4) is performed in Xe-Xe collisions at $\sqrt{s_{NN}}$ = 5.44 TeV under Monte Carlo HYDJET++ model (HYDrodynamics plus JETs) framework. Anisotropic flow of identified particles and correlation between the azimuthal harmonic flow amplitudes is presented. Here, we have considered body-body and tip-tip type of geometrical configurations for Xe-Xe collision systems. The kinematic ranges $|η|<0.8$, $0 2$ are considered. The results have been shown for seven classes of centrality and compared with the ALICE experimental data. The anisotropic flow of identified charged particles show a strong centrality dependence. Mass ordering is observed for $v_{2},v_{3}$ and $v_{4}$. Mass ordering is different for different ranges of transverse momentum $p_{T}$. Strong correlation is observed between $v_{3}-v_{2}$, $v_{4}-v_{2}$, and $v_{4}-v_{3}$. Such correlation is centrality dependent and is different in different centrality windows. The anisotropic flow coefficients show a clear dependence on the total charged particle multiplicity. HYDJET++ model justifies experimental data well enough.
description: 13 pages, 10 figures
Irregular cusps of ball quotients
Creators: name: Maeda, Yota
Publisher: name: arXiv
Year: 2021
Subjects: subject: Algebraic Geometry (math.AG)
subject: Number Theory (math.NT)
subject: FOS: Mathematics

description: We study the branch divisors on the boundary of the canonical toroidal compactification of ball quotients. We show a criterion, the low slope cusp form trick, for proving that ball quotients are of general type. Moreover, we classify when irregular cusps exist in the case of the discriminant kernel and construct concrete examples for some arithmetic subgroups. As another direction of study, when a complex ball is embedded into a Hermitian symmetric domain of type IV, we determine when regular or irregular cusps map to regular or irregular cusps studied by Ma.
description: 24 pages
MPEC 2024-F89 : DAILY ORBIT UPDATE (2024 March 27)
Creators: name: Minor Planet Center Staff
Publisher: name: The Minor Planet Center
Year: 2024
Subjects: subject: Small Solar System bodies
valueUri: http://astrothesaurus.org/uat/1469

description: The Minor Planet Electronic Circulars contain information on unusual minor planets, routine data on comets and natural satellites, and occasional editorial announcements.  They are published on behalf of Division F of the International Astronomical Union by the Minor Planet Center, Smithsonian Astrophysical Observatory, Cambridge, MA 02138, U.S.A.
ผลของโปรแกรมการเสริมสร้างพลังอำนาจต่อความรู้ ความตระหนักและพฤติกรรมการปองกันการติดเชื้อวัณโรคของผู้สัมผัสร่วมบ้านผู้ป่วยวัณโรคโรงพยาบาลวัดญาณสังวราราม
Creators: name: นริศรา ถาพันธ์
Publisher: name: สำนักจัดการความรู้ กรมควบคุมโรค กระทรวงสาธารณสุข
Year: 2556
Subjects: โปรแกรมการเสริมสร้างพลังอำนาจ
การป้องกัน
การติดเชื้อวัณโรค

description: วารสารควบคุมโรค, 39, 4, 309-317
Recolouring Homomorphisms to triangle-free reflexive graphs
Creators: name: Lee, Jae-baek
name: Noel, Jonathan A.
name: Siggers, Mark
Publisher: name: arXiv
Year: 2021
Subjects: subject: Combinatorics (math.CO)
subject: FOS: Mathematics
subject: Primary 05C15, Secondary 05C85

description: For a graph $H$, the $H$-recolouring problem $\operatorname{Recol}(H)$ asks, for two given homomorphisms from a given graph $G$ to $H$, if one can get between them by a sequence of homomorphisms of $G$ to $H$ in which consecutive homomorphisms differ on only one vertex. We show that, if $G$ and $H$ are reflexive and $H$ is triangle-free, then this problem can be solved in polynomial time. This shows, at the same time, that the closely related $H$-reconfiguration problem $\operatorname{Recon}(H)$ of deciding whether two given homomorphisms from a given graph $G$ to $H$ are in the same component of the Hom-graph $\operatorname{Hom}(G,H)$, can be solved in polynomial time for triangle-free reflexive graphs $H$.
ผู้ป่วยติดเซือเอซโอวี ด้วย simple smear technique, formalin ethyl acetateconcentration technique และ Parasep? faecal parasite concentration technique
Creators: name: ภาวิตา สุวรรณวัฒนะ
Publisher: name: สำนักจัดการความรู้ กรมควบคุมโรค กระทรวงสาธารณสุข
Year: 2556
Subjects: พยาธิโปรโตซัว
โปรโตซัวฉวยโอกาส
อุจจาระ
เอชไอวี

description: วารสารควบคุมโรค, 39, 4, 318-325
The intrinsic Toeplitz structure and its applications in algebraic Riccati equations
Creators: name: Guo, Zhen-Chen
name: Liang, Xin
Publisher: name: arXiv
Year: 2021
Subjects: subject: Numerical Analysis (math.NA)
subject: FOS: Mathematics
subject: 15A24, 15B05, 65F45, 93B52

description: In this paper we derive a Toeplitz-structured closed form of the unique positive semi-definite stabilizing solution for the discrete-time algebraic Riccati equations, especially for the case that the state matrix is not stable. Based on the found form and fast Fourier transform, we propose a new algorithm for solving both discrete-time and continuous-time large-scale algebraic Riccati equations with low-rank structure. It works without unnecessary assumptions, complicated shift selection strategies, or matrix calculations of the cubic order with respect to the problem scale. Numerical examples are given to illustrate its features. Besides, we show that it is theoretically equivalent to several algorithms existing in the literature in the sense that they all produce the same sequence under the same parameter setting.
description: 28 pages, 1 figure
In-Bed Human Pose Estimation from Unseen and Privacy-Preserving Image Domains
Creators: name: Cao, Ting
name: Armin, Mohammad Ali
name: Denman, Simon
name: Petersson, Lars
name: Ahmedt-Aristizabal, David
Publisher: name: arXiv
Year: 2021
Subjects: subject: Computer Vision and Pattern Recognition (cs.CV)
subject: Machine Learning (cs.LG)
subject: FOS: Computer and information sciences

description: Medical applications have benefited greatly from the rapid advancement in computer vision. Considering patient monitoring in particular, in-bed human posture estimation offers important health-related metrics with potential value in medical condition assessments. Despite great progress in this domain, it remains challenging due to substantial ambiguity during occlusions, and the lack of large corpora of manually labeled data for model training, particularly with domains such as thermal infrared imaging which are privacy-preserving, and thus of great interest. Motivated by the effectiveness of self-supervised methods in learning features directly from data, we propose a multi-modal conditional variational autoencoder (MC-VAE) capable of reconstructing features from missing modalities seen during training. This approach is used with HRNet to enable single modality inference for in-bed pose estimation. Through extensive evaluations, we demonstrate that body positions can be effectively recognized from the available modality, achieving on par results with baseline models that are highly dependent on having access to multiple modes at inference time. The proposed framework supports future research towards self-supervised learning that generates a robust model from a single source, and expects it to generalize over many unknown distributions in clinical environments.
description: In the IEEE International Symposium on Biomedical Imaging (ISBI)
Programming Interactions in Magnetic Handshake Materials
Creators: name: Du, Chrisy Xiyu
name: Zhang, Hanyu Alice
name: Pearson, Tanner
name: Ng, Jakin
name: McEuen, Paul
name: Cohen, Itai
name: Brenner, Michael P.
Publisher: name: arXiv
Year: 2021
Subjects: subject: Soft Condensed Matter (cond-mat.soft)
subject: Materials Science (cond-mat.mtrl-sci)
subject: FOS: Physical sciences

description: The ability to rapidly manufacture building blocks with specific binding interactions is a key aspect of programmable assembly. Recent developments in DNA nanotechnology and colloidal particle synthesis have significantly advanced our ability to create particle sets with programmable interactions, based on DNA or shape complementarity. The increasing miniaturization underlying magnetic storage offers a new path for engineering programmable components for self assembly, by printing magnetic dipole patterns on substrates using nanotechnology. How to efficiently design dipole patterns for programmable assembly remains an open question as the design space is combinatorially large. Here, we present design rules for programming these magnetic interactions. By optimizing the structure of the dipole pattern, we demonstrate that the number of independent building blocks scales super linearly with the number of printed domains. We test these design rules using computational simulations of self assembled blocks, and experimental realizations of the blocks at the mm scale, demonstrating that the designed blocks give high yield assembly. In addition, our design rules indicate that with current printing technology, micron sized magnetic panels could easily achieve hundreds of different building blocks.