scholarly journals Sensor Control in Anti-Submarine Warfare—A Digital Twin and Random Finite Sets Based Approach

Entropy ◽  
2019 ◽  
Vol 21 (8) ◽  
pp. 767 ◽  
Author(s):  
Peng Wang ◽  
Mei Yang ◽  
Yong Peng ◽  
Jiancheng Zhu ◽  
Rusheng Ju ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Real Time ◽  
Real World ◽  
Information Technologies ◽  
Finite Sets ◽  
The Real ◽  
Time Dynamic ◽  
Digital Twin ◽  
Sensor Control ◽  
Random Finite Sets

Since the submarine has become the major threat to maritime security, there is an urgent need to find a more efficient method of anti-submarine warfare (ASW). The digital twin theory is one of the most outstanding information technologies, and has been quite popular in recent years. The most influential change produced by digital twin is the ability to enable real-time dynamic interactions between the simulation world and the real world. Digital twin can be regarded as a paradigm by means of which selected online measurements are dynamically assimilated into the simulation world, with the running simulation model guiding the real world adaptively in reverse. By combining digital twin theory and random finite sets (RFSs) closely, a new framework of sensor control in ASW is proposed. Two key algorithms are proposed for supporting the digital twin-based framework. First, the RFS-based data-assimilation algorithm is proposed for online assimilating the sequence of real-time measurements with detection uncertainty, data association uncertainty, noise, and clutters. Second, the computation of the reward function by using the results of the proposed data-assimilation algorithm is introduced to find the optimal control action. The results of three groups of experiments successfully verify the feasibility and effectiveness of the proposed approach.

scholarly journals Using Digital Twining in Fast-food Production Chain Simulation

2021 ◽  
Vol 343 ◽  
pp. 03005
Author(s):  
Florina Chiscop ◽  
Bogdan Necula ◽  
Carmen Cristiana Cazacu ◽  
Cristian Eugen Stoica
Keyword(s):  
Real Time ◽  
Fast Food ◽  
Virtual Model ◽  
Time Data ◽  
Production Chain ◽  
The Real ◽  
Time Dynamic ◽  
Digital Twin ◽  
Food Company ◽  
The Moment

The topic of this paper represents our research in the process of creating a virtual model (digital twin) for a fast-food company production chain starting with the moment when a customer launches an order, following with the processing of that order, until the customer receives it. The model will describe elements that are included in this process such as equipment, human resources and the necessary space that is needed to host this layout. The virtual model created in a simulation platform will be a replicate of a real fast-food company, thus helping us observe the real time dynamic of this production system. Using WITNESS HORIZON 23 we will construct the model of the layout based on real time data received from the fast-food company. This digital twin will be used to manage the production chain material flow, evaluating the performance of the system architecture in various scenarios. In order to obtain a diagnosis of the system’s performance we will simulate the workflow running through preliminary architecture in compliance with the real time behaviour to identify the bottlenecks and blockages in the flow trajectory. In the end we will propose two different optimised architectures for the fast-food company production chain.

There and Back Again? Exploring the Real-Time Cognitive Journey of Narrative Transportation

2021 ◽  
pp. 009365022110185
Author(s):  
John M. Tchernev ◽  
James Collier ◽  
Zheng Wang
Keyword(s):  
Real Time ◽  
Real World ◽  
Future Directions ◽  
The Real ◽  
Time Dynamic ◽  
Post Exposure ◽  
Story Content ◽  
Narrative Processing ◽  
Dynamic Perspective ◽  
Dynamic Measures

Prior research has produced seemingly conflicting indications of whether or not audience members who are transported into a narrative leave themselves and the real world behind. This study proposes that a dynamic perspective can help resolve that conflict. Both traditional static post-exposure and real-time dynamic measures were used to examine four cognitive processes: attention, presence, self-referencing, and real world-referencing. Participants ( N = 118) were randomly assigned to view one of two television dramas. They provided continuous rating responses during viewing, as well as post-exposure measures of the overall viewing experience. Post-exposure measures indicated that self and real world-referencing were strongly positively correlated with transportation. The dynamic approach to understanding narrative processing, while exploratory in nature, likewise indicated links between the self, the real world, and the narrative world. Presence in the narrative predicted real world-referencing, and self-referencing predicted attention to the narrative, suggesting that when audience members link story content to their own lives, transportation may be enhanced rather than diminished. Strengths, limitations and future directions are discussed.

scholarly journals Parameter Optimization for Real-World ENSO Forecast in an Intermediate Coupled Model

2019 ◽  
Vol 147 (5) ◽  
pp. 1429-1445 ◽  
Author(s):  
Yuchu Zhao ◽  
Zhengyu Liu ◽  
Fei Zheng ◽  
Yishuai Jin
Keyword(s):  
Data Assimilation ◽  
Parameter Optimization ◽  
Real World ◽  
Climate Models ◽  
Coupled Model ◽  
Prediction Skill ◽  
Model Parameters ◽  
Real World Data ◽  
The Real ◽  
Advection Term

Abstract We performed parameter estimation in the Zebiak–Cane model for the real-world scenario using the approach of ensemble Kalman filter (EnKF) data assimilation and the observational data of sea surface temperature and wind stress analyses. With real-world data assimilation in the coupled model, our study shows that model parameters converge toward stable values. Furthermore, the new parameters improve the real-world ENSO prediction skill, with the skill improved most by the parameter of the highest climate sensitivity (gam2), which controls the strength of anomalous upwelling advection term in the SST equation. The improved prediction skill is found to be contributed mainly by the improvement in the model dynamics, and second by the improvement in the initial field. Finally, geographic-dependent parameter optimization further improves the prediction skill across all the regions. Our study suggests that parameter optimization using ensemble data assimilation may provide an effective strategy to improve climate models and their real-world climate predictions in the future.

Real-Time Unspecified Major Sub-Events Detection in the Twitter Data Stream That Cause the Change in the Sentiment Score of the Targeted Event

2017 ◽  
Vol 12 (4) ◽  
pp. 1-21 ◽  
Author(s):  
Ritesh Srivastava ◽  
M.P.S. Bhatia
Keyword(s):  
Real Time ◽  
Real World ◽  
Virtual Communities ◽  
Change Points ◽  
Time Analysis ◽  
The Real ◽  
Real Time Analysis ◽  
Twitter Data ◽  
Sentiment Score ◽  
Events Detection

Twitter behaves as a social sensor of the world. The tweets provided by the Twitter Firehose reveal the properties of big data (i.e. volume, variety, and velocity). With millions of users on Twitter, the Twitter's virtual communities are now replicating the real-world communities. Consequently, the discussions of real world events are also very often on Twitter. This work has performed the real-time analysis of the tweets related to a targeted event (e.g. election) to identify those potential sub-events that occurred in the real world, discussed over Twitter and cause the significant change in the aggregated sentiment score of the targeted event with time. Such type of analysis can enrich the real-time decision-making ability of the event bearer. The proposed approach utilizes a three-step process: (1) Real-time sentiment analysis of tweets (2) Application of Bayesian Change Points Detection to determine the sentiment change points (3) Major sub-events detection that have influenced the sentiment of targeted event. This work has experimented on Twitter data of Delhi Election 2015.

Augmented Reality Berbasis Android Sebagai Media Pembelajaran Sistem Tata Surya

2021 ◽  
Vol 2 (1) ◽  
pp. 53-59
Author(s):  
Yulia Fatma ◽  
Armen Salim ◽  
Regiolina Hayami
Keyword(s):  
Augmented Reality ◽  
Solar System ◽  
Real Time ◽  
Real World ◽  
Virtual World ◽  
The Real ◽  
Virtual Objects ◽  
Augmented Reality Technology ◽  
The Revolution

Along with the development, the application can be used as a medium for learning. Augmented Reality is a technology that combines two-dimensional’s virtual objects and three-dimensional’s virtual objects into a real three-dimensional’s  then projecting the virtual objects in real time and simultaneously. The introduction of Solar System’s material, students are invited to get to know the planets which are directly encourage students to imagine circumtances in the Solar System. Explenational of planets form and how the planets make the revolution and rotation in books are considered less material’s explanation because its only display objects in 2D. In addition, students can not practice directly in preparing the layout of the planets in the Solar System. By applying Augmented Reality Technology, information’s learning delivery can be clarified, because in these applications are combined the real world and the virtual world. Not only display the material, the application also display images of planets in 3D animation’s objects with audio.

scholarly journals Usability in the real world: assessing medical information technologies in patients’ homes

2003 ◽  
Vol 36 (1-2) ◽  
pp. 45-60 ◽  
Author(s):  
David R Kaufman ◽  
Vimla L Patel ◽  
Charlyn Hilliman ◽  
Philip C Morin ◽  
Jenia Pevzner ◽  
...  
Keyword(s):  
Real World ◽  
Information Technologies ◽  
Medical Information ◽  
The Real

scholarly journals Construction of Intelligent Integrated Model Framework for the Workshop Manufacturing System Via Digital Twin

2021 ◽  
Author(s):  
Zhongyu Zhang ◽  
Zhenjie Zhu ◽  
Jinsheng Zhang ◽  
Jingkun Wang
Keyword(s):  
Real Time ◽  
Production System ◽  
Manufacturing System ◽  
System Optimization ◽  
Production Cycle ◽  
Model Framework ◽  
The Real ◽  
Digital Twin ◽  
Twin Model ◽  
Information Layer

Abstract With the drastic development of the globally advanced manufacturing industry, transition of the original production pattern from traditional industries to advanced intelligence is completed with the least delay possible, which are still facing new challenges. Because the timeliness, stability and reliability of them is significantly restricted due to lack of the real-time communication. Therefore, an intelligent workshop manufacturing system model framework based on digital twin is proposed in this paper, driving the deep inform integration among the physical entity, data collection, and information decision-making. The conceptual and obscure of the traditional digital twin is refined, optimized, and upgraded on the basis of the four-dimension collaborative model thinking. A refined nine-layer intelligent digital twin model framework is established. Firstly, the physical evaluation is refined into entity layer, auxiliary layer and interface layer, scientifically managing the physical resources as well as the operation and maintenance of the instrument, and coordinating the overall system. Secondly, dividing the data evaluation into the data layer and the processing layer can greatly improve the flexible response-ability and ensure the synchronization of the real-time data. Finally, the system evaluation is subdivided into information layer, algorithm layer, scheduling layer, and functional layer, developing flexible manufacturing plan more reasonably, shortening production cycle, and reducing logistics cost. Simultaneously, combining SLP and artificial bee colony are applied to investigate the production system optimization of the textile workshop. The results indicate that the production efficiency of the optimized production system is increased by 34.46%.

Real-time in the real world

1996 ◽  
Vol 28 (4es) ◽  
pp. 187 ◽  
Author(s):  
Lui Sha
Keyword(s):  
Real Time ◽  
Real World ◽  
The Real
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