scholarly journals Analysis of Train Driver's Visual Perceptual Skills Using Markov Cluster Algorithm

2016 ◽  
Vol 28 (3) ◽  
pp. 598-607
Author(s):  
Yukio HORIGUCHI ◽  
Takaya SUZUKI ◽  
Takayuki SUZUKI ◽  
Tetsuo SAWARAGI ◽  
Hiroaki NAKANISHI ◽  
...  
Keyword(s):  
Cluster Algorithm ◽  
Perceptual Skills ◽  
Markov Cluster Algorithm ◽  
Markov Cluster

Predicting Figure Coalition for 2019 Indonesian Presindential Election Using Modified Markov Clustering Algorithm

2019 ◽  
Vol 3 (1) ◽  
pp. 23
Author(s):  
Rahmat Al Kafi ◽  
Dian Maharani ◽  
Kartika Chandra Dewi ◽  
Yuni Rosita Dewi ◽  
Alhadi Bustamam
Keyword(s):  
Presidential Election ◽  
Clustering Algorithm ◽  
Cluster Algorithm ◽  
New Approach ◽  
Markov Cluster Algorithm ◽  
The Matrix ◽  
Markov Clustering ◽  
Markov Cluster

This paper presents a new approach to ameliorate the Markov Cluster algorithm for predicting figure coalition for 2019 Indonesian Presidential Election. The proposed method is the modification of the Markov Clustering algorithm. First, 20 figures are collected to form a 20 x 20 matrix. Second, the entries of the matrix are scored by 0, 1, 2, or 3 concerning the number of positive comments from netizen towards the observed figures photo on Instagram. Third, we implemented the Markov Clustering to find the clusters that represent the number of coalitions. The effectiveness of the proposed method is confirmed by comparing the prediction results with the actual coalition.

scholarly journals PhyloFisher: A phylogenomic package for resolving eukaryotic relationships

PLoS Biology ◽  
2021 ◽  
Vol 19 (8) ◽  
pp. e3001365
Author(s):  
Alexander K. Tice ◽  
David Žihala ◽  
Tomáš Pánek ◽  
Robert E. Jones ◽  
Eric D. Salomaki ◽  
...  
Keyword(s):  
Single Copy ◽  
Protein Coding ◽  
Eukaryotic Diversity ◽  
Protein Coding Genes ◽  
Markov Cluster Algorithm ◽  
Pruning Algorithms ◽  
Phylogenomic Analyses ◽  
Diverse Groups ◽  
Tree Pruning ◽  
Markov Cluster

Phylogenomic analyses of hundreds of protein-coding genes aimed at resolving phylogenetic relationships is now a common practice. However, no software currently exists that includes tools for dataset construction and subsequent analysis with diverse validation strategies to assess robustness. Furthermore, there are no publicly available high-quality curated databases designed to assess deep (>100 million years) relationships in the tree of eukaryotes. To address these issues, we developed an easy-to-use software package, PhyloFisher (https://github.com/TheBrownLab/PhyloFisher), written in Python 3. PhyloFisher includes a manually curated database of 240 protein-coding genes from 304 eukaryotic taxa covering known eukaryotic diversity, a novel tool for ortholog selection, and utilities that will perform diverse analyses required by state-of-the-art phylogenomic investigations. Through phylogenetic reconstructions of the tree of eukaryotes and of the Saccharomycetaceae clade of budding yeasts, we demonstrate the utility of the PhyloFisher workflow and the provided starting database to address phylogenetic questions across a large range of evolutionary time points for diverse groups of organisms. We also demonstrate that undetected paralogy can remain in phylogenomic “single-copy orthogroup” datasets constructed using widely accepted methods such as all vs. all BLAST searches followed by Markov Cluster Algorithm (MCL) clustering and application of automated tree pruning algorithms. Finally, we show how the PhyloFisher workflow helps detect inadvertent paralog inclusions, allowing the user to make more informed decisions regarding orthology assignments, leading to a more accurate final dataset.

Demonstration: Virtual Patient Immersive Trainer to Train Perceptual Skills Using Augmented Reality

2020 ◽  
Vol 64 (1) ◽  
pp. 470-472
Author(s):  
Christen E. Sushereba ◽  
Laura G. Militello
Keyword(s):  
Medical Students ◽  
Augmented Reality ◽  
Student Performance ◽  
Group Interaction ◽  
Virtual Patient ◽  
Perceptual Cues ◽  
Perceptual Skills ◽  
Individual Interaction ◽  
Severity Of Injury ◽  
Microsoft Hololens

In this session, we will demonstrate the Virtual Patient Immersive Trainer (VPIT). The VPIT system uses augmented reality (AR) to allow medics and medical students to experience a photorealistic, life-sized virtual patient. The VPIT supports learners in obtaining the perceptual skills required to recognize and interpret subtle perceptual cues critical to assessing a patient’s condition. We will conduct an interactive demonstration of the virtual patient using both a tablet (for group interaction) and an AR-enabled headset (Microsoft HoloLens) for individual interaction. In addition, we will demonstrate use of the instructor tablet to control what the learner sees (e.g., injury types, severity of injury) and to monitor student performance.

scholarly journals Hamiltonian models of lattice fermions solvable by the meron-cluster algorithm

2021 ◽  
Vol 103 (5) ◽  
Author(s):  
Hanqing Liu ◽  
Shailesh Chandrasekharan ◽  
Ribhu K. Kaul
Keyword(s):  
Cluster Algorithm ◽  
Hamiltonian Models ◽  
Lattice Fermions
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