scholarly journals ILSHR Rumor Spreading Model by Combining SIHR and ILSR Models in Complex Networks

2021 ◽  
Vol 13 (6) ◽  
pp. 51-59
Author(s):  
Adel Angali ◽  
◽  
Musa Mojarad ◽  
Hassan Arfaeinia
Keyword(s):  
State Transition ◽  
Negative Impact ◽  
Transition Function ◽  
Rumor Spreading ◽  
Sina Weibo ◽  
Spreading Model ◽  
Proposed Model ◽  
Significant Negative Impact ◽  
State Transition Function ◽  
Important Form

Rumor is an important form of social interaction. However, spreading harmful rumors can have a significant negative impact on social welfare. Therefore, it is important to examine rumor models. Rumors are often defined as unconfirmed details or descriptions of public things, events, or issues that are made and promoted through various tools. In this paper, the Ignorant-Lurker-Spreader-Hibernator-Removal (ILSHR) rumor spreading model has been developed by combining the ILSR and SIHR epidemic models. In addition to the characteristics of the lurker group of ILSR, this model also considers the characteristics of the hibernator group of the SIHR model. Due to the complexity of the complex network structure, the state transition function for each node is defined based on their degree to make the proposed model more efficient. Numerical simulations have been performed to compare the ILSHR rumor spreading model with other similar models on the Sina Weibo dataset. The results show more effective ILSHR performance with 95.83% accuracy than CSRT and SIR-IM models.

The Factors of Why the People of Pakistan Do Not Purchase Paid Apps

2020 ◽  
Vol 10 (2) ◽  
pp. 44-56
Author(s):  
Umar Farooq Gillani ◽  
Muhammad Ishfaq Khan ◽  
Manzar Waseem Ishaq ◽  
Kashif Aziz ◽  
Muhammad Nawas Akram
Keyword(s):  
Purchase Intention ◽  
Negative Impact ◽  
Value Theory ◽  
Growth Potential ◽  
High Price ◽  
Research Model ◽  
Mobile Game ◽  
The People ◽  
Proposed Model ◽  
Significant Negative Impact

Despite the huge growth potential that has been predicted for purchase intention toward paid apps and the mobile game market, little is known about what motivates game players to make such purchases. The purpose of this article is to build a research model based on the satisfaction literature and studies of value theory to identify the antecedents of paid app purchase intention in the context of mobile games. The proposed model was empirically tested and uses data from 310 players of different games groups. Multiple regression, Process Macro, and moderation regression were used to measure the research model. The results tell that satisfaction to the mobile game has a significant influence on a player's intention to make paid app purchase. The perceived values of the game have a direct influence on the satisfaction of all players but appear to have relatively moderation impact of price have significant negative impact on the purchase intentions of players. Specifically, our study revealed a high price decrease the purchase intention of a satisfied player.

A fuzzy rumor spreading model based on transmission capacity

2018 ◽  
Vol 29 (02) ◽  
pp. 1850012 ◽  
Author(s):  
Yi Zhang ◽  
Jiuping Xu ◽  
Yue Wu
Keyword(s):  
Simulated Data ◽  
Real Data ◽  
Transmission Capacity ◽  
Model Assessment ◽  
Rumor Spreading ◽  
Factors Affecting ◽  
Fuzzy Variables ◽  
Spreading Model ◽  
Proposed Model ◽  
Special Cases

This paper proposes a rumor spreading model that considers three main factors: the event importance, event ambiguity, and the publics critical sense, each of which are defined by decision makers using linguistic descriptions and then transformed into triangular fuzzy numbers. To calculate the resultant force of these three factors, the transmission capacity and a new parameter category with fuzzy variables are determined. A rumor spreading model is then proposed which has fuzzy parameters rather than the fixed parameters in traditional models. As the proposed model considers the comprehensive factors affecting rumors from three aspects rather than examining special factors from a particular aspect. The proposed rumor spreading model is tested using different parameters for several different conditions on BA networks and three special cases are simulated. The simulation results for all three cases suggested that events of low importance, those that are only clarifying facts, and those that are strongly critical do not result in rumors. Therefore, the model assessment results were proven to be in agreement with reality. Parameters for the model were then determined and applied to an analysis of the 7.23 Yong–Wen line major transportation accident (YWMTA). When the simulated data were compared with the real data from this accident, the results demonstrated that the interval for the rumor spreading key point in the model was accurate, and that the key point for the YWMTA rumor spread fell into the range estimated by the model.

scholarly journals DESIGNING COMPLEX DYNAMICS IN CELLULAR AUTOMATA WITH MEMORY

2013 ◽  
Vol 23 (10) ◽  
pp. 1330035 ◽  
Author(s):  
GENARO J. MARTÍNEZ ◽  
ANDREW ADAMATZKY ◽  
RAMON ALONSO-SANZ
Keyword(s):  
Cellular Automata ◽  
State Transition ◽  
Complex Dynamics ◽  
Transition Function ◽  
Systematic Analysis ◽  
Time Dynamics ◽  
Controversial Topic ◽  
State Transition Function ◽  
And Behavior ◽  
With Memory

Since their inception at Macy conferences in later 1940s, complex systems have remained the most controversial topic of interdisciplinary sciences. The term "complex system" is the most vague and liberally used scientific term. Using elementary cellular automata (ECA), and exploiting the CA classification, we demonstrate elusiveness of "complexity" by shifting space-time dynamics of the automata from simple to complex by enriching cells with memory. This way, we can transform any ECA class to another ECA class — without changing skeleton of cell-state transition function — and vice versa by just selecting a right kind of memory. A systematic analysis displays that memory helps "discover" hidden information and behavior on trivial — uniform, periodic, and nontrivial — chaotic, complex — dynamical systems.

scholarly journals On the Equivalence between Small-Step and Big-Step Abstract Machines: A Simple Application of Lightweight Fusion

2007 ◽  
Vol 14 (16) ◽  
Author(s):  
Olivier Danvy ◽  
Kevin Millikin
Keyword(s):  
Fixed Point ◽  
Simple Proof ◽  
Recursive Function ◽  
State Transition ◽  
Transition Function ◽  
Simple Application ◽  
Small Step ◽  
Final State ◽  
Abstract Machines ◽  
State Transition Function

We show how Ohori and Sasano's recent lightweight fusion by fixed-point promotion provides a simple way to prove the equivalence of the two standard styles of specification of abstract machines: (1) in small-step form, as a state-transition function together with a `driver loop,' i.e., a function implementing the iteration of this transition function; and (2) in big-step form, as a tail-recursive function that directly maps a given configuration to a final state, if any. The equivalence hinges on our observation that for abstract machines, fusing a small-step specification yields a big-step specification. We illustrate this observation here with a recognizer for Dyck words, the CEK machine, and Krivine's machine with call/cc.<br /> <br />The need for such a simple proof is motivated by our current work on small-step abstract machines as obtained by refocusing a function implementing a reduction semantics (a syntactic correspondence), and big-step abstract machines as obtained by CPS-transforming and then defunctionalizing a function implementing a big-step semantics (a functional correspondence).

scholarly journals Learning and Communicating the Latent States of Human-Machine Collaboration

2018 ◽  
Author(s):  
Vaibhav V. Unhelkar ◽  
Julie A. Shah
Keyword(s):  
Decision Making ◽  
State Transition ◽  
Complete Information ◽  
Transition Function ◽  
Shared Environment ◽  
Decision Making Under Uncertainty ◽  
Artificial Agents ◽  
Rescue Operation ◽  
Novel Algorithms ◽  
State Transition Function

Artificial agents (both embodied robots and software agents) that interact with humans are increasing at an exceptional rate. Yet, achieving seamless collaboration between artificial agents and humans in the real world remains an active problem. A key challenge is that the agents need to make decisions without complete information about their shared environment and collaborators. For instance, a human-robot team performing a rescue operation after a disaster may not have an accurate map of their surroundings. Even in structured domains, such as manufacturing, a robot might not know the goals or preferences of its human collaborators. Algorithmically, this challenge manifests itself as a problem of decision-making under uncertainty in which the agent has to reason about the latent states of its environment and human collaborator. However, in practice, quantifying this uncertainty (i.e., the state transition function) and even specifying the features (i.e., the relevant states) of human-machine collaboration is difficult. Thus, the objective of this thesis research is to develop novel algorithms that enable artificial agents to learn and reason about the latent states of human-machine collaboration and achieve fluent interaction.

scholarly journals Modeling the spread of fake news on Twitter

PLoS ONE ◽  
2021 ◽  
Vol 16 (4) ◽  
pp. e0250419
Author(s):  
Taichi Murayama ◽  
Shoko Wakamiya ◽  
Eiji Aramaki ◽  
Ryota Kobayashi
Keyword(s):  
Process Model ◽  
Negative Impact ◽  
News Item ◽  
Compact Representation ◽  
News Story ◽  
Fake News ◽  
Proposed Model ◽  
Significant Negative Impact ◽  
Twitter Users ◽  
The Moment

Fake news can have a significant negative impact on society because of the growing use of mobile devices and the worldwide increase in Internet access. It is therefore essential to develop a simple mathematical model to understand the online dissemination of fake news. In this study, we propose a point process model of the spread of fake news on Twitter. The proposed model describes the spread of a fake news item as a two-stage process: initially, fake news spreads as a piece of ordinary news; then, when most users start recognizing the falsity of the news item, that itself spreads as another news story. We validate this model using two datasets of fake news items spread on Twitter. We show that the proposed model is superior to the current state-of-the-art methods in accurately predicting the evolution of the spread of a fake news item. Moreover, a text analysis suggests that our model appropriately infers the correction time, i.e., the moment when Twitter users start realizing the falsity of the news item. The proposed model contributes to understanding the dynamics of the spread of fake news on social media. Its ability to extract a compact representation of the spreading pattern could be useful in the detection and mitigation of fake news.

scholarly journals Estimation of Urban Link Travel Time Distribution Using Markov Chains and Bayesian Approaches

2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Wenwen Qin ◽  
Meiping Yun
Keyword(s):  
Markov Chain ◽  
Travel Time ◽  
Time Distribution ◽  
State Transition ◽  
Transition Function ◽  
Travel Times ◽  
Travel Time Distribution ◽  
Multimodal Distributions ◽  
State Transition Function ◽  
Link Travel Time

Despite the wide application of Floating Car Data (FCD) in urban link travel time and congestion estimation, the sparsity of observations from a low penetration rate of GPS-equipped floating cars make it difficult to estimate travel time distribution (TTD), especially when the travel times may have multimodal distributions that are associated with the underlying traffic states. In this case, the study develops a Bayesian approach based on particle filter framework for link TTD estimation using real-time and historical travel time observations from FCD. First, link travel times are classified by different traffic states according to the levels of vehicle delays. Then, a state-transition function is represented as a Transition Probability Matrix of the Markov chain between upstream and current links with historical observations. Using the state-transition function, an importance distribution is constructed as the summation of historical link TTDs conditional on states weighted by the current link state probabilities. Further, a sampling strategy is developed to address the sparsity problem of observations by selecting the particles with larger weights in terms of the importance distribution and a Gaussian likelihood function. Finally, the current link TTD can be reconstructed by a generic Markov Chain Monte Carlo algorithm incorporating high weighted particles. The proposed approach is evaluated using real-world FCD. The results indicate that the proposed approach provides good accurate estimations, which are very close to the empirical distributions. In addition, the approach with different percentage of floating cars is tested. The results are encouraging, even when multimodal distributions and very few or no observations exist.

scholarly journals Discrete Optimization on Train Rescheduling on Single-Track Railway: Clustering Hierarchy and Heuristic Search

2020 ◽  
Vol 2020 ◽  
pp. 1-19 ◽  
Author(s):  
Zhengkun Zhang ◽  
Changfeng Zhu ◽  
Wenhu Ma
Keyword(s):  
Dynamic System ◽  
Heuristic Search ◽  
Search Strategy ◽  
State Transition ◽  
Transition Function ◽  
Discrete Dynamic ◽  
Discrete Dynamic System ◽  
Simulation Efficiency ◽  
Train Rescheduling ◽  
State Transition Function

This paper focuses on discrete dynamic optimization on train rescheduling on single-track railway with the consideration of train punctuality and station satisfaction degree. A discrete dynamic system is firstly described to mimic train rescheduling, and a state transition function is specially designed according to the train departure event. The purpose of this function is to improve simulation efficiency by directly confirming the next discrete time. After the construction and analysis of optimization models to discrete dynamic system, a two-stage heuristic search strategy is developed, by using clustering hierarchy theory and stochastic search strategy, to obtain train departure time and arrival time before each state transition of the system. Finally, a numerical experiment is conducted to verify the proposed system, models, and the heuristic search strategy. The result shows that the discrete dynamic system, together with the state transition function and heuristic search strategy, shows better performance in simulation efficiency and solution quality.

Comparison of Time spent between an electronic and a paper-based laboratory information system by laboratorians at a polyclinic in Greater Accra, Ghana: A time-motion study

2020 ◽  
Author(s):  
Philip Boakye
Keyword(s):  
Information System ◽  
Negative Impact ◽  
Laboratory Information System ◽  
Time Motion ◽  
Accessible Information ◽  
Motion Study ◽  
Significant Difference ◽  
Significant Negative Impact ◽  
Key Issues ◽  
Motion Studies

The acceptance of electronic laboratory information system (LIS) is gradually increasing in developing countries. However, the issue of time effectiveness due to computerization is less clear as there is fewer accessible information. One of the key issues for laboratorians is their indecision with LISs’ would-be effect of time on their work. A polyclinic in Ghana was in the process of implementing electronic LIS. Several of the laboratorians did not have knowledge and skill in computing and there were disagreeing views on the time effectiveness of the LIS after implementation. The management of the polyclinic laboratory was concerned to assess time advantageousness of recording data when using the electronic LIS compared with paper-based LIS. <div><br></div><div>Five randomly selected laboratorians were provided two sheets of paper with tables to document the time they spent for both paper-based and electronic LIS. Data were collected for a total of 230 records,115 electronic LIS and 115 paper-based LIS. The t-test (mean-comparison test) was computed to compare the means of both electronic and paperbased LIS times. </div><div><br></div><div>There was a statistical significant difference in the time spent between electronic and paper-based LIS. The time spent between paper-based and electronic LIS was 0.41 minutes (95% CI 0.15 to 0.66) longer than in electronic LIS. </div><div><br></div><div>LIS can be adopted in polyclinics without having significant negative impact on time spent between electronic and paper-based LIS. More time–motion studies that include laboratorians are however necessary in order to get a more complete picture of time spent between electronic and paper-based LIS. </div>

ASSESSMENT OF THE SPATIOTEMPORAL DYNAMICS OF THE MACROPHYTE THICKET ECOSYSTEMS IN THE NEVA BAY AND THE ADJACENT WATERS OF THE EASTERN GULF OF FINLAND

2017 ◽  
Author(s):  
Ekaterina Maksimova ◽  
Ekaterina Maksimova ◽  
Vladimir Zhigulsky ◽  
Vladimir Zhigulsky ◽  
Vladimir Shuisky ◽  
...  
Keyword(s):  
Aquatic Vegetation ◽  
Temporal Dynamics ◽  
Negative Impact ◽  
Spatiotemporal Dynamics ◽  
Gulf Of Finland ◽  
Active Growth ◽  
Nesting Sites ◽  
Significant Negative Impact ◽  
And Migration ◽  
Neva Bay

The macrophyte thicket ecosystems of higher aquatic vegetation in the Neva Bay (NB) and Eastern Gulf of Finland (EGoF) perform many important roles, including acting as the habitats, nesting sites and migration sites for aquatic and semi-aquatic birds, creating the specific conditions necessary for the spawning and growth of many species of fish, and taking part in the self-purification of the aquatic ecosystems. Many anthropogenic disturbances, hydraulic works in particular, have a significant negative impact on these macrophyte thicket ecosystems. In recent years, the active growth of a new type of macrophyte thicket has been observed in the NB. This is due to the aftereffects of the construction of the Saint Petersburg Flood Prevention Facility Complex (FPFC). It is quite likely that the total macrophyte thicket area in these waters is currently increasing. In the future, it will be necessary to assess the environmental impacts of the hydraulic works on the macrophyte thicket of the NB and EGoF, taking into account the background processes of the spatiotemporal dynamics of the reed beds in the waters in question. To do this, it will be necessary to carry out a comprehensive study of these ecosystems and identify patterns in their spatial and temporal dynamics. The program of the study has been developed and is currently being implemented by Eco-Express-Service, a St. Petersburg eco-design company.

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