A multilayer affective computing model with evolutionary strategies reflecting decision-makers’ preferences in process control

2021 ◽  
Author(s):  
Chong Su ◽  
Xuri Ma ◽  
Jing Lv ◽  
Tao Tu ◽  
Hongguang Li
Keyword(s):  
Process Control ◽  
Affective Computing ◽  
Decision Makers ◽  
Evolutionary Strategies ◽  
Computing Model

Adapting Chatterbots’ Interaction for Use in Children’s Education

2014 ◽  
pp. 413-428
Author(s):  
Antonio F. L. Jacob ◽  
Eulália C. da Mata ◽  
Ádamo L. Santana ◽  
Carlos R. L. Francês ◽  
João C. W. A. Costa ◽  
...  
Keyword(s):  
Knowledge Base ◽  
Affective Computing ◽  
Traditional Methods ◽  
Children's Education ◽  
Computing Model ◽  
Wide Range ◽  
Children’S Education ◽  
Effective Use ◽  
The Web

The Web is providing greater freedom for users to create and obtain information in a more dynamic and appropriate way. One means of obtaining information on this platform, which complements or replaces other forms, is the use of conversation robots or Chatterbots. Several factors must be taken into account for the effective use of this technology; the first of which is the need to employ a team of professionals from various fields to build the knowledge base of the system and be provided with a wide range of responses, i.e. interactions. It is a multidisciplinary task to ensure that the use of this system can be targeted to children. In this context, this chapter carries out a study of the technology of Chatterbots and shows some of the changes that have been implemented for the effective use of this technology for children. It also highlights the need for a shift away from traditional methods of interaction so that an affective computing model can be implemented.

Design of Emotional Interaction System Based on Affective Computing Model

2012 ◽  
Vol 198-199 ◽  
pp. 367-373
Author(s):  
Guo Liang Yang ◽  
Jin Hui Zhang ◽  
Hui Sun
Keyword(s):  
Emotional Expression ◽  
Affective Computing ◽  
Quantitative Relationship ◽  
Emotional Information ◽  
Computing Model ◽  
Software Interface ◽  
Emotional Interaction ◽  
Interaction System ◽  
Emotional Model ◽  
Relationship Of

An emotional interaction system is designed by using the theories about affective computing in this paper, which includes the emotional information capturing, machine emotional model and emotional expression. This paper focuses on the problem of building machine emotional model, not only gives the basic definitions of personality space, mood space, and emotion space, but also establishes the quantitative relationship of personality mood and emotion. At last, this paper builds a machine affective model which can reflect the transformation law of the mood, emotion and personality. Related simulation results show that the model can effectively simulates the change law of human emotion. Finally, this paper designs the software interface of the emotional interaction system.

scholarly journals Using control charts to understand community variation in COVID-19

PLoS ONE ◽  
2021 ◽  
Vol 16 (4) ◽  
pp. e0248500
Author(s):  
Moira Inkelas ◽  
Cheríe Blair ◽  
Daisuke Furukawa ◽  
Vladimir G. Manuel ◽  
Jason H. Malenfant ◽  
...  
Keyword(s):  
Process Control ◽  
Statistical Process Control ◽  
Control Charts ◽  
Ease Of Use ◽  
Decision Makers ◽  
Statistical Process ◽  
Policy Makers ◽  
Disaggregate Data ◽  
Community Variation ◽  
Neighborhood Level

Decision-makers need signals for action as the coronavirus disease 2019 (COVID-19) pandemic progresses. Our aim was to demonstrate a novel use of statistical process control to provide timely and interpretable displays of COVID-19 data that inform local mitigation and containment strategies. Healthcare and other industries use statistical process control to study variation and disaggregate data for purposes of understanding behavior of processes and systems and intervening on them. We developed control charts at the county and city/neighborhood level within one state (California) to illustrate their potential value for decision-makers. We found that COVID-19 rates vary by region and subregion, with periods of exponential and non-exponential growth and decline. Such disaggregation provides granularity that decision-makers can use to respond to the pandemic. The annotated time series presentation connects events and policies with observed data that may help mobilize and direct the actions of residents and other stakeholders. Policy-makers and communities require access to relevant, accurate data to respond to the evolving COVID-19 pandemic. Control charts could prove valuable given their potential ease of use and interpretability in real-time decision-making and for communication about the pandemic at a meaningful level for communities.

Application of OLAP Technology in the Environment of Electronic Demography

2021 ◽  
Vol 27 (10) ◽  
pp. 542-549
Author(s):  
G. Ch. Nabibayova ◽  
Keyword(s):  
Decision Makers ◽  
Practical Application ◽  
Demographic Research ◽  
Computing Model ◽  
Interdisciplinary Field ◽  
Parallel Data ◽  
Data Marts ◽  
Data Volume ◽  
Analytical Processing ◽  
High Level

The article proposes an approach to the development of an electronic demographic decision support system using technologies of Data Warehouse (DW) and Interactive Analytical Processing OLAP. This makes it possible to conduct high-level demographic research and provide support to decision-makers in demographic sphere. The article notes that demography is an interdisciplinary field of research and is defined as a complex science. Each industry of demography has many indicators. A sample list of these indicators is presented. The main characteristics of the DW, which should be taken into account when developing its architecture, are stated. Among these characteristics, one can find the main defining characteristics of Big Data — volume, velocity, variety, veracity, variability, visualization, value etc. For a more rational and efficient use of a large amount of information, taking into account its constant increase, to ensure the speed of execution of requests for a given system, it is proposed to use a Bus of Interconnected Data Marts (DM) as an architecture of DW. One of the advantages of using DM is that their use assumes distributed parallel data processing. This architecture allows for much faster results generation. It is based on the MapReduce distributed computing model and the Hadoop project. In addition, to effectively use large amounts of data, it is also proposed to use OLAP operations such as roll-up and drill-down, as well as fuzzy set theory, based on the technique of computing with words. The article also shows the practical application of interconnected DM. An OLAP cube is built on the basis of these DM. OLAP operations provide the ability to view cubes in different slices and provide aggregate data.

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