Network Analysis and Visualization of the Complexity of an Individual Tax Return

2015 ◽  
Vol 13 (1) ◽  
pp. 17-35
Author(s):  
Suzanne M. Luttman ◽  
David E. Monarchi ◽  
Balázs Nagy
Keyword(s):  
Network Analysis ◽  
Data Visualization ◽  
Tax Reform ◽  
Internal Revenue ◽  
Tax Professionals ◽  
The Brain ◽  
Problem Data

ABSTRACT Tax professionals who work with the Internal Revenue Code are well aware of its volume and complexity. They also have an abstract sense of the interrelatedness of its many provisions. However, the brain soon limits our ability to comprehend the relationships involved in a tax problem. Data visualization can present a coherent representation of the degree of difficulty of comprehending the Code. We graphically illustrate the morass of interconnected Code sections directly and indirectly required to complete a simple tax return. We conclude by suggesting how this technique may be useful in developing and analyzing future tax reform proposals.

scholarly journals Human Emotion Detection using Eeg Sensor

2020 ◽  
Vol 9 (5) ◽  
pp. 409-413
Keyword(s):  
Data Visualization ◽  
Concentration Level ◽  
Brain Activity ◽  
Emotion Detection ◽  
Attention Span ◽  
Brain Waves ◽  
Alpha Beta ◽  
The Right ◽  
The Waves ◽  
The Brain

This is a data visualization art piece using 10 seconds of mind waves recordings of the human, captured with EEG sensor.10 seconds of Alpha, Beta, Gamma & Theta brain waves while meditating are recorded, the different wave channels are categorized to state when the right brain representing artistic brain activity, isolating the ranges for each channel when the brain channels were more meditating and imaginative. Based on the waves of the brain obtained, we will be able to deduce few attributes such as attention span and mood. The moods we will be trying to assess and display here the level of happiness, sadness, anger along with attention span and meditation level (Concentration level).

Creating “(Social) Network Art” with NodeXL

2017 ◽  
pp. 342-393
Author(s):  
Shalin Hai-Jew
Keyword(s):  
Social Media ◽  
Big Data ◽  
Social Network ◽  
Network Analysis ◽  
Web 2.0 ◽  
Data Visualization ◽  
Network Graph ◽  
Social Media Platforms ◽  
Machine Art ◽  
Social Sharing

If human-created objects of art are historically contingent, then the emergence of (social) network art may be seen as a product of several trends: the broad self-expression and social sharing on Web 2.0; the application of network analysis and data visualization to understand big data, and an appreciation for online machine art. Social network art is a form of cyborg art: it melds data from both humans and machines; the sensibilities of humans and machines; and the pleasures and interests of people. This chapter will highlight some of the types of (social) network art that may be created with Network Overview, Discovery and Exploration for Excel (NodeXL Basic) and provide an overview of the process. The network graph artwork presented here were all built from datasets extracted from popular social media platforms (Twitter, Flickr, YouTube, Wikipedia, and others). This chapter proposes some early aesthetics for this type of electronic artwork.

scholarly journals Network analysis of the brain proteome of GRN knockout mice reveals pathogenic mechanisms shared in human frontotemporal dementia caused by GRN mutations

2020 ◽  
Vol 16 (S3) ◽  
Author(s):  
Thomas Kukar ◽  
Meixiang Huang ◽  
Erica S Modeste ◽  
Eric B Dammer ◽  
Christopher J Holler ◽  
...  
Keyword(s):  
Network Analysis ◽  
Frontotemporal Dementia ◽  
Knockout Mice ◽  
Pathogenic Mechanisms ◽  
Brain Proteome ◽  
The Brain

scholarly journals The impact of latent confounders in directed network analysis in neuroscience

2013 ◽  
Vol 371 (1997) ◽  
pp. 20110612 ◽  
Author(s):  
Rebecca Ramb ◽  
Michael Eichler ◽  
Alex Ing ◽  
Marco Thiel ◽  
Cornelius Weiller ◽  
...  
Keyword(s):  
Network Analysis ◽  
Nonlinear System ◽  
Granger Causality ◽  
Directed Network ◽  
Vector Autoregressive Models ◽  
Vector Autoregressive ◽  
Physiological Pathways ◽  
The Impact ◽  
The Brain ◽  
Past Activity

In the analysis of neuroscience data, the identification of task-related causal relationships between various areas of the brain gives insights about the network of physiological pathways that are active during the task. One increasingly used approach to identify causal connectivity uses the concept of Granger causality that exploits predictability of activity in one region by past activity in other regions of the brain. Owing to the complexity of the data, selecting components for the analysis of causality as a preprocessing step has to be performed. This includes predetermined—and often arbitrary—exclusion of information. Therefore, the system is confounded by latent sources. In this paper, the effect of latent confounders is demonstrated, and paths of influence among three components are studied. While methods for analysing Granger causality are commonly based on linear vector autoregressive models, the effects of latent confounders are expected to be present also in nonlinear systems. Therefore, all analyses are also performed for a simulated nonlinear system and discussed with regard to applications in neuroscience.

scholarly journals Predicting Brain Regions Related to Alzheimer’s Disease Based on Global Feature

2020 ◽  
Author(s):  
Qi Wang ◽  
Siwei Chen ◽  
He Wang ◽  
Luzeng Chen ◽  
Yongan Sun ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Network Analysis ◽  
Diffusion Tensor ◽  
The Elderly ◽  
Brain Regions ◽  
Imaging Method ◽  
Global Feature ◽  
Objective Monitoring ◽  
The Brain

AbstractAlzheimer’s disease (AD) is a common neurodegenerative disease in the elderly, early diagnosis and timely treatment are very important to delay the course of the disease. In the past, most of the brain regions related to AD were identified based on the imaging method, which can only identify some atrophic brain regions. In this work, we used mathematical models to find out the potential brain regions related to AD. First, diffusion tensor imaging (DTI) was used to construct the brain structural network. Next, we set a new local feature index 2hop-connectivity to measure the correlation among different areas. And for this, we proposed a novel algorithm named 2hopRWR to measure 2hop-connectivity. At last, we proposed a new index GFS (Global Feature Score) based on global feature by combing 5 local features: degree centrality, betweenness centrality, closeness centrality, the number of maximal cliques, and 2hop-connectivity, to judge which brain regions are likely related to Alzheimer’s Disease. As a result, all the top ten brain regions in GFS scoring difference between the AD group and the non-AD group were related to AD by literature verification. Finally, the results of the canonical correlation analysis showed that the GFS was significantly correlated with the scores of the mini-mental state examination (MMSE) scale and montreal cognitive assessment (MoCA) scale. So, we believe the GFS can also be used as a new index to assist in diagnosis and objective monitoring of disease progression. Besides, the method proposed in this paper can be used as a differential network analysis method in other areas of network analysis.

Tax Decision Making under the New Burden of Proof Rules

2004 ◽  
Vol 26 (2) ◽  
pp. 23-42 ◽  
Author(s):  
Anne M. Magro ◽  
Beth Stetson
Keyword(s):  
Decision Making ◽  
Burden Of Proof ◽  
Internal Revenue Service ◽  
Popular Press ◽  
Tax System ◽  
Internal Revenue ◽  
Playing Field ◽  
Proof Rules ◽  
Tax Professionals

In the late 1990s, controversy over alleged Internal Revenue Service abuses and concern about the extent of the agency's power over taxpayers led to the passage of new rules governing relations between the IRS and taxpayers. An important element of this new set of rules was I.R.C. § 7491, which purported to shift the burden of proof in civil tax cases from the taxpayer to the IRS. Commentators generally agreed that the shift would have little effect on the outcome of cases, but the popular press touted the new provision as an important step to level the playing field between the parties. We conduct an experiment in which we manipulate the applicability of I.R.C. § 7491 and measure role in the tax system (taxpayer versus tax professional). As predicted, we find that taxpayers assess a higher likelihood of success in litigation when the anticipated burden of proof rests with the IRS than when the anticipated burden of proof rests with the taxpayer. Taxpayers who believe that the IRS bears the burden of proof also assess a higher likelihood of success than do tax professionals, regardless of the applicability of I.R.C. § 7491. This increased perceived likelihood of success in litigation translates to an increased willingness on the part of taxpayers to engage in an unsound tax-motivated transaction.

Comparative Genomic and Network Analysis of nNOS by Using Different Bioinformatics Approaches

2021 ◽  
Vol 18 ◽  
Author(s):  
Nymphaea Arora ◽  
Vikash Prashar ◽  
Tania Arora ◽  
Randeep Sidhu ◽  
Anshul Mishra ◽  
...  
Keyword(s):  
Nitric Oxide ◽  
Network Analysis ◽  
Nitric Oxide Synthase ◽  
Vascular Tone ◽  
Neuronal Nitric Oxide Synthase ◽  
Homologous Sequences ◽  
Airway Tone ◽  
Oxide Synthase ◽  
The Brain

Introduction: Nitric oxide (NO) is a diatomic free radical gaseous molecule that is formed from L-arginine through NOS (Nitric oxide synthase) catalyzed reaction. NO controls vascular tone (hence blood pressure), insulin secretion, airway tone, and peristalsis and is involved in angiogenesis (growth of new blood vessels) and in the development of the nervous system. In the CNS, NO is an important messenger molecule, which is involved in various major functions in the brain. NOS has been classified into three isoforms which include nNOS (neuronal NOS), eNOS (endothelial NOS), and iNOS (inducible NOS). NOS1 is localized on chromosome 12, consisting of 1434 amino acids and 161 KDa molecular weight. nNOS is involved in synaptic transmission, regulating the tone of smooth muscles, penile erection. We studied NOS1 gene and protein network analysis through in silico techniques as human nNOS sequence was fetched from GenBank, and its homologous sequences were retrieved through BLAST search. Moreover, the results of this study exploit the role of NOS1 in various pathways, which provide ways to regulate it in various neurodegenerative diseases. Background: Previous research has revealed the role of Nitric Oxide (NO) formed from L-arginine through NOS (Nitric Oxide Synthase) as a physiological inter/intracellular messenger in the central as well as the peripheral nervous system. The diverse functions of NOS include insulin secretion, airway tone, vascular tone regulation, and in the brain, it is involved in differentiation, development, synaptic plasticity, and neurosecretion. Objective: The objective of this study is to unravel the role of neuronal Nitric Oxide Synthase (nNOS) in different pathways and its involvement as a therapeutic target in various neurodegenerative disorders, which can surely provide ways to regulate its activity in different aspects. Materials and Methods: In this study, we employed various bioinformatics tools and databases, initiating the study by fetching the neuronal Nitric Oxide Synthase (nNOS) sequence(GenBank) to find its homologous sequences(BLAST) and then exploring its physical properties and post-translational modifications, enhancing the research by network analysis(STRING), leading to its functional enrichment(Panther). Results : The results positively support the hypothesis of its role in various pathways related to neurodegeneration., Its interacting partners are the probable therapeutic targets of various neurodegenerative diseases focusing on specifically multi-target analysis. Conclusion: This study considered the evolutionary trend of physical, chemical, and biological properties of NOS1 through different phyla. The neuronal Nitric Oxide Synthase (nNOS), being one of the three isoforms of NOS (Nitric Oxide Synthase), is found to be involved in more pathways than just forming Nitric Oxide. This research provides the base for further neurological research.

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