scholarly journals Epidemic Source Detection over Dynamic Networks

Electronics ◽  
2020 ◽  
Vol 9 (6) ◽  
pp. 1018
Author(s):  
Jaeyoung Choi
Keyword(s):  
Dynamic Model ◽  
Dynamic Networks ◽  
Dynamic Network ◽  
Estimation Algorithm ◽  
Estimation Methods ◽  
Source Detection ◽  
Source Estimation ◽  
Contact Information ◽  
Node Connectivity ◽  
Over Time

Epidemic source detection is one of the most crucial problems in statistical inference. For example, currently, the debate continues to reveal when and where the first spread of COVID-19 occured. For this problem, most of the works have assumed a static network topology, that is, the connections between nodes do not change over time. This is impractical because many nodes have some mobility in the network, or the connections can be changed. In this paper, we focus on the dynamic network, in the sense that the node connectivity varies over time. We first introduce a simple dynamic model, named k-flip dynamic such that k > 0 connections in the network may be changed with some probability at each time. Next, we design a proper estimation algorithm using some investigation for the contact information between infected nodes, named dynamic network source estimation (DNSE)(k) for the dynamic model. We perform various simulations for the algorithm compared to several existing source estimation methods. Our results show that the proposed algorithm outperforms and is efficient for finding the epidemic source compared to other methods. Further, we see that the detection probability for our proposed algorithm can be above 45% when we use budget to investigate the contact information from the infected nodes under some practical setting of k.

scholarly journals Visualisation of Long in Time Dynamic Networks on Large Touch Displays

2021 ◽  
Author(s):  
◽  
Alexandra Lee
Keyword(s):  
Laboratory Study ◽  
Dynamic Networks ◽  
Dynamic Network ◽  
Network Data ◽  
User Evaluation ◽  
Time Dynamic ◽  
Time Interaction ◽  
Expert User ◽  
Novel Method ◽  
Over Time

Any dataset containing information about relationships between entities can be modelled as a network. This network can be static, where the entities/relationships do not change over time, or dynamic, where the entities/relationships change over time. Network data that changes over time, dynamic network data, is a powerful resource when studying many important phenomena, across wide-ranging fields from travel networks to epidemiology.However, it is very difficult to analyse this data, especially if it covers a long period of time (e.g, one month) with respect to its temporal resolution (e.g. seconds). In this thesis, we address the problem of visualising long in time dynamic networks: networks that may not be particularly large in terms of the number of entities or relationships, but are long in terms of the length of time they cover when compared to their temporal resolution.We first introduce Dynamic Network Plaid, a system for the visualisation and analysis of long in time dynamic networks. We design and build for an 84" touch-screen vertically-mounted display as existing work reports positive results for the use of these in a visualisation context, and that they are useful for collaboration. The Plaid integrates multiple views and we prioritise the visualisation of interaction provenance. In this system we also introduce a novel method of time exploration called ‘interactive timeslicing’. This allows the selection and comparison of points that are far apart in time, a feature not offered by existing visualisation systems. The Plaid is validated through an expert user evaluation with three public health researchers.To confirm observations of the expert user evaluation, we then carry out a formal laboratory study with a large touch-screen display to verify our novel method of time navigation against existing animation and small multiples approaches. From this study, we find that interactive timeslicing outperforms animation and small multiples for complex tasks requiring a compari-son between multiple points that are far apart in time. We also find that small multiples is best suited to comparisons of multiple sequential points in time across a time interval.To generalise the results of this experiment, we later run a second formal laboratory study in the same format as the first, but this time using standard-sized displays with indirect mouse input. The second study reaffirms the results of the first, showing that our novel method of time navigation can facilitate the visual comparison of points that are distant in time in a way that existing approaches, small multiples and animation, cannot. The study demonstrates that our previous results generalise across display size and interaction type (touch vs mouse).In this thesis we introduce novel representations and time interaction techniques to improve the visualisation of long in time dynamic networks, and experimentally show that our novel method of time interaction outperforms other popular methods for some task types.

Forecasting Interconnections in International Housing Markets: Evidence from the Dynamic Model Averaging Approach

2020 ◽  
Vol 42 (1) ◽  
pp. 37-103
Author(s):  
Hardik A. Marfatia
Keyword(s):  
Dynamic Model ◽  
Model Averaging ◽  
Housing Markets ◽  
The United States ◽  
Forecasting Model ◽  
Change Over Time ◽  
The United Kingdom ◽  
Novel Approach ◽  
Dynamic Model Averaging ◽  
Over Time

In this paper, I undertake a novel approach to uncover the forecasting interconnections in the international housing markets. Using a dynamic model averaging framework that allows both the coefficients and the entire forecasting model to dynamically change over time, I uncover the intertwined forecasting relationships in 23 leading international housing markets. The evidence suggests significant forecasting interconnections in these markets. However, no country holds a constant forecasting advantage, including the United States and the United Kingdom, although the U.S. housing market's predictive power has increased over time. Evidence also suggests that allowing the forecasting model to change is more important than allowing the coefficients to change over time.

scholarly journals DNA-based constitutional dynamic networks as functional modules for logic gates and computing circuit operations

2021 ◽  
Vol 12 (15) ◽  
pp. 5473-5483
Author(s):  
Zhixin Zhou ◽  
Jianbang Wang ◽  
R. D. Levine ◽  
Francoise Remacle ◽  
Itamar Willner
Keyword(s):  
Nucleic Acid ◽  
Dynamic Networks ◽  
Dynamic Network ◽  
Logic Gates ◽  
Functional Modules ◽  
Logic Operations

A nucleic acid-based constitutional dynamic network (CDN) provides a single functional computational module for diverse input-guided logic operations and computing circuits.

scholarly journals A Fusion Algorithm for Estimating Time-Independent/-Dependent Parameters and States

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4068
Author(s):  
Zheshuo Zhang ◽  
Jie Zhang ◽  
Jiawen Dai ◽  
Bangji Zhang ◽  
Hengmin Qi
Keyword(s):  
Unscented Kalman Filter ◽  
Time Estimation ◽  
Estimation Algorithm ◽  
Estimation Methods ◽  
Fusion Algorithm ◽  
State Variable ◽  
Current Estimation ◽  
Real Time Estimation ◽  
And Control ◽  
Independent Parameters

Vehicle parameters are essential for dynamic analysis and control systems. One problem of the current estimation algorithm for vehicles’ parameters is that: real-time estimation methods only identify parts of vehicle parameters, whereas other parameters such as suspension damping coefficients and suspension and tire stiffnesses are assumed to be known in advance by means of an inertial parameter measurement device (IPMD). In this study, a fusion algorithm is proposed for identifying comprehensive vehicle parameters without the help of an IPMD, and vehicle parameters are divided into time-independent parameters (TIPs) and time-dependent parameters (TDPs) based on whether they change over time. TIPs are identified by a hybrid-mass state-variable (HMSV). A dual unscented Kalman filter (DUKF) is applied to update both TDPs and online states. The experiment is conducted on a real two-axle vehicle and the test data are used to estimate both TIPs and TDPs to validate the accuracy of the proposed algorithm. Numerical simulations are performed to further investigate the algorithm’s performance in terms of sprung mass variation, model error because of linearization and various road conditions. The results from both the experiment and simulation show that the proposed algorithm can estimate TIPs as well as update TDPs and online states with high accuracy and quick convergence, and no requirement of road information.

The dynamic nature of depression: a new micro-level perspective of mental disorder that meets current challenges

2013 ◽  
Vol 44 (7) ◽  
pp. 1349-1360 ◽  
Author(s):  
M. Wichers
Keyword(s):  
Dynamic Network ◽  
Building Blocks ◽  
Major Depressive ◽  
Dynamic Network Model ◽  
Healthy State ◽  
Behavioural Patterns ◽  
Micro Level ◽  
Continuous Dynamic ◽  
Dynamic Interplay ◽  
Over Time

The examination of moment-to-moment, ‘micro-level’ patterns of experience and behaviour using experience sampling methodology has contributed to our understanding of the ‘macro-level’ development of full-blown symptoms and disorders. This paper argues that the micro-level perspective can be used to identify the smallest building blocks underlying the onset and course of mental ill-health. Psychopathology may be the result of the continuous dynamic interplay between micro-level moment-to-moment experiences and behavioural patterns over time. Reinforcing loops between momentary states may alter the course of mental health towards either a more or less healthy state. An example with observed data, from a population of individuals with depressive symptoms, supports the validity of a dynamic network model of psychopathology and shows that together and over time, this continuous interplay between momentary states may result in the cluster of symptoms we call major depressive disorder. This approach may help conceptualize the nature of mental disorders, and generate individualized insights useful for diagnosis and treatment in psychiatry.

scholarly journals Method for monitoring intertidal communities in a steep rocky shore: a combination of digital image technology and field operational strategy

2007 ◽  
Vol 55 (1) ◽  
pp. 19-27 ◽  
Author(s):  
Danuza Nogueira Moysés ◽  
Andréa de Oliveira R. Junqueira ◽  
Helena Passeri Lavrado ◽  
Sérgio Henrique Gonçalves da Silva
Keyword(s):  
Digital Image ◽  
Field Work ◽  
Benthic Invertebrate ◽  
Rocky Intertidal ◽  
Estimation Methods ◽  
Rocky Shores ◽  
Percent Cover ◽  
Intertidal Communities ◽  
Time Reproduction ◽  
Over Time

This paper introduces a method for temporal studies of steep rocky intertidal communities. It combines the use of digital image technology with field methodology, so that a wide area of the community can be sampled in a short time. Two current nondestructive percent cover estimation methods (visual estimation and point intersection) were compared in terms of cost, operational advantages and data quality, with a proposed method for a sucessional study . The proposed method used sequential photos to sample multiple fixed vertical transects over time. Reproduction of the mid-intertidal transect over time was possible by overlaying temporal transects in an image editing program. This method was similar to the point intersection quadrat method used to estimate percent cover. Benefits included reduced time on field work, economic advantages and other advantages of using digital photography, such as recording. Temporal photography of transects provided measurements of recruitment, mortality and population growth, and made it possible to manufacture an animation of sucessional stages. We suggest that this is the best method for providing information and understanding on the process of succession and for monitoring benthic invertebrate intertidal communities on steep rocky shores.

scholarly journals Topology Control Using Distributed Power Management Algorithm for Mobile Ad Hoc Networks

2009 ◽  
Vol 5 (4) ◽  
pp. 128
Author(s):  
Nuraj Pradhan ◽  
Tarek Saadawi
Keyword(s):  
Ad Hoc ◽  
Dynamic Network ◽  
Path Loss ◽  
Packet Delay ◽  
Management Algorithm ◽  
Physical Channel ◽  
Strongly Connected ◽  
Node Connectivity ◽  
Hoc Networks ◽  
Log Normal

In order to be strongly connected in the network, a node may increase its power indiscriminately causing interference. Since interference is one of the major problems in wireless network, the proposed algorithm will co-operatively reduce inter-node interference in the network. Further, uni-directional links are a major source of interference as most of the routing protocol only utilizes bi-directional links. The algorithm will attempt to prevent such links or if required convert them into bi-directional links. We will show that the proposed algorithm provides strongly connected and more reliable network over dynamic physical channel modeled by log-distance path loss model, log-normal shadowing model and rayleigh fading model. It stabilizes node connectivity over the dynamic network and environment and even, to a certain extent, prevent node from being completely disconnected from the network. For the selected simulation environment, we will show that the proposed algorithm provides a shorter packet delay, improves the network throughput by as much as 37%, decreases the routing overhead and reduces interference.

scholarly journals Emerging, crystalizing, and changing psychological contracts over time: Introducing the iPC-network model

2019 ◽  
Author(s):  
Tim Vantilborgh
Keyword(s):  
Network Model ◽  
Psychological Contract ◽  
Dynamic Network ◽  
Network Models ◽  
Psychological Contracts ◽  
Exchange Relationships ◽  
Contract Breach ◽  
Alternative Approach ◽  
The Individual ◽  
Over Time

This chapter introduces the individual Psychological Contract (iPC) network model as an alternative approach to study psychological contracts. This model departs from the basic idea that a psychological contract forms a mental schema containing obligated inducements and contributions, which are exchanged for each other. This mental schema is captured by a dynamic network, in which the nodes represent the inducements and contributions and the ties represent the exchanges. Building on dynamic systems theory, I propose that these networks evolve over time towards attractor states, both at the level of the network structure and at the level of the nodes (i.e., breach and fulfilment attractor states). I highlight how the iPC-network model integrates recent theoretical developments in the psychological contract literature and explain how it may advance scholars understanding of exchange relationships. In particular, I illustrate how iPC-network models allow researchers to study the actual exchanges in the psychological contract over time, while acknowledging its idiosyncratic nature. This would allow for more precise predictions of psychological contract breach and fulfilment consequences and explains how content and process of the psychological contract continuously influence each other.

scholarly journals Minimum Array Elements for Resolution of Several Direction of Arrival Estimation Methods in Various Noise-Level Environments

2018 ◽  
Vol 2 ◽  
pp. 87-94
Author(s):  
Ismail El Ouargui ◽  
Said Safi ◽  
Miloud Frikel
Keyword(s):  
Gaussian Noise ◽  
Noise Level ◽  
Signal To Noise Ratio ◽  
Additive White Gaussian Noise ◽  
Direction Of Arrival ◽  
Estimation Algorithm ◽  
Doa Estimation ◽  
Estimation Methods ◽  
Minimum Number ◽  
Informative Signals

The resolution of a Direction of Arrival (DOA) estimation algorithm is determined based on its capability to resolve two closely spaced signals. In this paper, authors present and discuss the minimum number of array elements needed for the resolution of nearby sources in several DOA estimation methods. In the real world, the informative signals are corrupted by Additive White Gaussian Noise (AWGN). Thus, a higher signal-to-noise ratio (SNR) offers a better resolution. Therefore, we show the performance of each method by applying the algorithms in different noise level environments.

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