scholarly journals StratomeX: Visual Analysis of Large-Scale Heterogeneous Genomics Data for Cancer Subtype Characterization

2012 ◽  
Vol 31 (3pt3) ◽  
pp. 1175-1184 ◽  
Author(s):  
A. Lex ◽  
M. Streit ◽  
H.-J. Schulz ◽  
C. Partl ◽  
D. Schmalstieg ◽  
...  
Keyword(s):  
Large Scale ◽  
Visual Analysis ◽  
Cancer Subtype

scholarly journals InSight2: A Modular Visual Analysis Platform for Network Situational Awareness in Large-Scale Networks

Electronics ◽  
2020 ◽  
Vol 9 (10) ◽  
pp. 1747
Author(s):  
Hansaka Angel Dias Edirisinghe Kodituwakku ◽  
Alex Keller ◽  
Jens Gregor
Keyword(s):  
Real Time ◽  
Computer Networks ◽  
Network Flow ◽  
Large Scale ◽  
Visual Analysis ◽  
Situational Awareness ◽  
Monitoring Network ◽  
Network Activity ◽  
Flow Data ◽  
Large Scale Networks

The complexity and throughput of computer networks are rapidly increasing as a result of the proliferation of interconnected devices, data-driven applications, and remote working. Providing situational awareness for computer networks requires monitoring and analysis of network data to understand normal activity and identify abnormal activity. A scalable platform to process and visualize data in real time for large-scale networks enables security analysts and researchers to not only monitor and study network flow data but also experiment and develop novel analytics. In this paper, we introduce InSight2, an open-source platform for manipulating both streaming and archived network flow data in real time that aims to address the issues of existing solutions such as scalability, extendability, and flexibility. Case-studies are provided that demonstrate applications in monitoring network activity, identifying network attacks and compromised hosts and anomaly detection.

scholarly journals Visual Analysis of Large‐Scale Protein‐Ligand Interaction Data

2021 ◽  
Author(s):  
Karsten Schatz ◽  
Juan José Franco‐Moreno ◽  
Marco Schäfer ◽  
Alexander S. Rose ◽  
Valerio Ferrario ◽  
...  
Keyword(s):  
Large Scale ◽  
Visual Analysis ◽  
Interaction Data ◽  
Ligand Interaction ◽  
Protein Ligand Interaction

scholarly journals Wireless Sensor Network-Based Mathematical Modeling for Communication Intelligent Monitoring System

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Ying Shen
Keyword(s):  
Cell Phone ◽  
Large Scale ◽  
Visual Analysis ◽  
User Behavior ◽  
Base Station ◽  
Time Base ◽  
Behavior Patterns ◽  
Behavioral Patterns ◽  
Commercial Development ◽  
Clustering Model

Knowing the behavioral patterns of city residents is of great value in formulating and adjusting urban planning strategies, such as urban road planning, urban commercial development, and urban pedestrian flow control. Based on the high penetration rate of cell phones, it is possible to indirectly understand the behavior of city residents based on the call records of users. However, the behavioral patterns of large-scale users over a long period of time can present characteristics such as large dispersion, difficult to discover patterns, and difficult to explain behavioral patterns. In this paper, we design and implement a human behavior pattern analysis system based on massive mobile communication data based on serial data modeling method and visual analysis technology. For the problem that it is difficult to capture the behavioral patterns of residents in cities in call records, this paper constructs base station trajectories based on users’ cell phone call records and uses users’ long-time base station trajectories to mine users’ potential behavioral patterns. Since users with similar activity characteristics will exhibit similar base station trajectories, this paper focuses on the similarity between text sequences and base station trajectory sequences and combines the word embedding method in natural language processing to build a Cell2vec model to identify the semantics of base stations in cities. In order to obtain the group behavior patterns of users from the base station trajectories of group users, a user clustering method based on users’ regional mobile preferences is proposed, and the results are projected using the Stochastic Neighbor Embedding (t-SNE) algorithm to expose the clustering features of large-scale cell phone users in the low-dimensional space. To address the problem that user behavior patterns are difficult to interpret, a visual analysis model with group as well as regional semantics is designed for the spatial and temporal characteristics of user behavior. Among them, the clustering model uses the distance between scatter points to map the similarity between users, which helps analysts to explore the behavioral characteristics of group users.

scholarly journals Translucent Visual Analysis of Large Scale 3D Point Data Generated by Particle Fluid Simulation of Tsunami Water

2014 ◽  
Vol 1 (1) ◽  
pp. 5-15 ◽  
Author(s):  
Kentaro Tanaka ◽  
Satoshi Tanaka ◽  
Kyoko Hasegawa ◽  
Kohei Murotani ◽  
Seiichi Koshizuka
Keyword(s):  
Large Scale ◽  
Visual Analysis ◽  
Fluid Simulation ◽  
Point Data

scholarly journals Scientific Visual Analysis System Required for Large-Scale Numerical Simulations.

2002 ◽  
Vol 78 (1) ◽  
pp. 59-69 ◽  
Author(s):  
Yoshio SUZUKI ◽  
Yasuaki KISHIMOTO ◽  
NEXT group
Keyword(s):  
Numerical Simulations ◽  
Large Scale ◽  
Visual Analysis ◽  
Analysis System

scholarly journals Combining Strengths for Multi-genome Visual Analytics Comparison

2019 ◽  
Vol 13 ◽  
pp. 117793221882512 ◽  
Author(s):  
Sergio Diaz-del-Pino ◽  
Pablo Rodriguez-Brazzarola ◽  
Esteban Perez-Wohlfeil ◽  
Oswaldo Trelles
Keyword(s):  
Data Analysis ◽  
Data Acquisition ◽  
Visual Analytics ◽  
Large Scale ◽  
Visual Analysis ◽  
Homo Sapiens ◽  
Third Party ◽  
Genome Comparison ◽  
Post Processing ◽  
Sequence Comparisons

The eclosion of data acquisition technologies has shifted the bottleneck in molecular biology research from data acquisition to data analysis. Such is the case in Comparative Genomics, where sequence analysis has transitioned from genes to genomes of several orders of magnitude larger. This fact has revealed the need to adapt software to work with huge experiments efficiently and to incorporate new data-analysis strategies to manage results from such studies. In previous works, we presented GECKO, a software to compare large sequences; now we address the representation, browsing, data exploration, and post-processing of the massive amount of information derived from such comparisons. GECKO-MGV is a web-based application organized as client-server architecture. It is aimed at visual analysis of the results from both pairwise and multiple sequences comparison studies combining a set of common commands for image exploration with improved state-of-the-art solutions. In addition, GECKO-MGV integrates different visualization analysis tools while exploiting the concept of layers to display multiple genome comparison datasets. Moreover, the software is endowed with capabilities for contacting external-proprietary and third-party services for further data post-processing and also presents a method to display a timeline of large-scale evolutionary events. As proof-of-concept, we present 2 exercises using bacterial and mammalian genomes which depict the capabilities of GECKO-MGV to perform in-depth, customizable analyses on the fly using web technologies. The first exercise is mainly descriptive and is carried out over bacterial genomes, whereas the second one aims to show the ability to deal with large sequence comparisons. In this case, we display results from the comparison of the first Homo sapiens chromosome against the first 5 chromosomes of Mus musculus.

3D Fine Modeling Method in Large and Complex Steel Truss Bridge

2014 ◽  
Vol 501-504 ◽  
pp. 1408-1412
Author(s):  
Yi Fan Jia ◽  
Yun Dong Peng ◽  
Hua Jiang
Keyword(s):  
Large Scale ◽  
Visual Analysis ◽  
Three Dimensional ◽  
Modeling Method ◽  
Decision Makers ◽  
Data Conversion ◽  
Steel Truss Bridge ◽  
Steel Truss ◽  
Truss Bridge ◽  
Analysis Platform

The design and construction of the stiffening steel truss bridge is a complex and large-scale professional program. The abstract of the plans and the weaknesses of the view angles to the design sketch will also become limitations to the owners and the decision makers. Based on the project of Baling River Bridge of large stiffening steel truss girders, this study creates a three-dimensional fine model for it via CAD, pre-assembles each parts of the bridge, and checks sections and dockings one to one correspondingly. Data conversion of this model directly generates virtual visualized model. This visualized fine model of Baling River Bridge provides decision makers with a visual analysis platform, which also offers technical guarantee and support for sensible decision makings.

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