scholarly journals Bayesian Network Approach to Customer Requirements to Customized Product Model

2019 ◽  
Vol 2019 ◽  
pp. 1-16 ◽  
Author(s):  
Qin Yang ◽  
Zhirui Li ◽  
Haisen Jiao ◽  
Zufang Zhang ◽  
Weijie Chang ◽  
...  
Keyword(s):  
Bayesian Network ◽  
Customer Requirements ◽  
Customer Demand ◽  
Product Model ◽  
Customer Needs ◽  
Related Information ◽  
Demand Node ◽  
Product Method ◽  
Key Factor ◽  
Customized Products

Customizing products based on customer needs is an irreversible trend, and many companies strive to provide customized products to customers in less time. Customer requirements are a key factor in the company's ability to provide customized products. In order to better meet customer needs, solve the problem of incomplete and inaccurate expression, and improve the correlation between customized product performance and customer demand, a customized product method based on Bayesian network is proposed. First, the company built a custom product model based on Bayesian networks. According to the model, the customer selects some nodes and their related information. Then, we can accurately predict the final product model through the link tree algorithm, test the customer demand node to determine the focus of the customer's needs, and optimize the model. Finally, an example of a multifunctional nursing bed is used to illustrate the effectiveness of the method.

WMS: Revenue Model Innovation for Gaming Solutions

2016 ◽  
pp. 1-16
Author(s):  
Mohanbir Sawhney ◽  
Pallavi Goodman ◽  
Ori Broit
Keyword(s):  
Financial Crisis ◽  
Software Industry ◽  
Slot Machines ◽  
Customer Demand ◽  
Customer Needs ◽  
Technology Markets ◽  
Revenue Model ◽  
Product Manager ◽  
Revenue Models ◽  
The Right

In 2014 WMS Gaming, a manufacturer and seller of slot machines to casinos, was considering a redesign of its existing revenue model. As technology evolved and customer demand for gaming solutions intensified, new and innovative revenue models were being adopted in other technology markets. Most notably, the subscription revenue model, in which customers paid a monthly subscription fee rather than a large upfront fee, was becoming widely adopted in the software industry. Product manager Dayna Stone had the task of evaluating several revenue models and recommending one that most suited WMS's business needs and at the same time took customer needs and wishes into consideration. Complicating this decision were several factors that would have to be kept in mind. Americans' love of gaming had led to a mushrooming of casinos, which meant increased competition for casino dollars. Yet the financial crisis of 2008 and its aftermath had weakened demand for casinos. In addition, casinos, depending on the type of customers they attracted, differed in their appetite for innovation and maintenance of their slot machines. Students will step into the shoes of Dayna Stone as she undertakes the task of weighing these factors and selecting the right revenue model.

scholarly journals ExTaxsI: an exploration tool of biodiversity molecular data

2020 ◽  
Author(s):  
Giulia Agostinetto ◽  
Anna Sandionigi ◽  
Adam Chahed ◽  
Alberto Brusati ◽  
Elena Parladori ◽  
...  
Keyword(s):  
Molecular Data ◽  
Data Availability ◽  
Future Research ◽  
Distribution Data ◽  
Biodiversity Data ◽  
Related Information ◽  
New Information ◽  
Starting Point ◽  
Key Factor ◽  
New Research

AbstractBackgroundThe increasing availability of multi omics data is leading to continually revise estimates of existing biodiversity data. In particular, the molecular data enable to characterize novel species yet unknown and to increase the information linked to those already observed with new genomic data. For this reason, the management and visualization of existing molecular data, and their related metadata, through the implementation of easy to use IT tools have become a key point for the development of future research. The more users are able to access biodiversity related information, the greater the ability of the scientific community to expand the knowledge in this area.ResultsIn our research we have focused on the development of ExTaxsI (Exploring Taxonomies Information), an IT tool able to retrieve biodiversity data stored in NCBI databases and provide a simple and explorable visualization. Through the three case studies presented here, we have shown how an efficient organization of the data already present can lead to obtaining new information that is fundamental as a starting point for new research. Our approach was also able to highlight the limits in the distribution data availability, a key factor to consider in the experimental design phase of broad spectrum studies, such as metagenomics.ConclusionsExTaxI can easily produce explorable visualization of molecular data and its metadata, with the aim to help researchers to improve experimental designs and highlight the main gaps in the coverage of available data.

A New Concept for Requirements Driven Project Planning in an Integrated PLM Environment

2008 ◽  
Author(s):  
Michael Maletz ◽  
Dan Brisson ◽  
Yong Zeng
Keyword(s):  
Process Model ◽  
Project Planning ◽  
Domain Specific ◽  
Related Information ◽  
System A ◽  
Requirements Modeling ◽  
Methodical Approach ◽  
Key Factor ◽  
Natural Language Requirements ◽  
Product And Process

Integration in today’s heterogeneous PLM environments is a key factor in all development phases. This paper describes a methodical approach to integrating requirements modeling into a PLM environment. The specific focus of integration aspects is on project planning of complex mechatronic products with recurrent character based on requirements specification documents. Function and process orientation serves as a basis for the integration. It is discussed how development projects teams can benefit by generating project plans including resource estimations and predefined interfaces to bordering disciplines along the development process. With the help of semantic parsing methods of natural language requirements and through a generic classification system a requirement based product and process model is generated. This model is then taken as the basis for deriving product and process related information. Through domain specific ontology’s generic project and resource plans are generated with the help of the proposed methodology.

scholarly journals Product Dictionary Learning-Based SAR Target Configuration Recognition

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Ming Liu ◽  
Shichao Chen ◽  
Fugang Lu ◽  
Junsheng Liu
Keyword(s):  
Synthetic Aperture Radar ◽  
Sparse Representation ◽  
Dictionary Learning ◽  
Synthetic Aperture ◽  
Sar Image ◽  
Product Model ◽  
Sar Images ◽  
Stationary Target ◽  
Target Configuration ◽  
Key Factor

Dictionary construction is a key factor for the sparse representation- (SR-) based algorithms. It has been verified that the learned dictionaries are more effective than the predefined ones. In this paper, we propose a product dictionary learning (PDL) algorithm to achieve synthetic aperture radar (SAR) target configuration recognition. The proposed algorithm obtains the dictionaries from a statistical standpoint to enhance the robustness of the proposed algorithm to noise. And, taking the inevitable multiplicative speckle in SAR images into account, the proposed algorithm employs the product model to describe SAR images. A more accurate description of the SAR image results in higher recognition rates. The accuracy and robustness of the proposed algorithm are validated by the moving and stationary target acquisition and recognition (MSTAR) database.

Equal access to online information? Google’s suicide-prevention disparities may amplify a global digital divide

2018 ◽  
Vol 21 (3) ◽  
pp. 562-582 ◽  
Author(s):  
Sebastian Scherr ◽  
Mario Haim ◽  
Florian Arendt
Keyword(s):  
Digital Divide ◽  
Health Information ◽  
Suicide Prevention ◽  
Information Access ◽  
Equal Access ◽  
Online Health Information ◽  
Online Information ◽  
Related Information ◽  
Key Factor ◽  
Global Digital Divide

Worldwide, people profit from equally accessible online health information via search engines. Therefore, equal access to health information is a global imperative. We studied one specific scenario, in which Google functions as a gatekeeper when people seek suicide-related information using both helpful and harmful suicide-related search terms. To help prevent suicides, Google implemented a “suicide-prevention result” (SPR) at the very top of such search results. While this effort deserves credit, the present investigation compiled evidence that the SPR is not equally displayed to all users. Using a virtual agent-based testing methodology, a set of 3 studies in 11 countries found that the presentation of the SPR varies depending on where people search for suicide-related information. Language is a key factor explaining these differences. Google’s algorithms thereby contribute to a global digital divide in online health-information access with possibly lethal consequences. Higher and globally balanced display frequencies are desirable.

scholarly journals Comparing the Content of Medical Tourism Facilitator Websites in Iran And Other Countries: A Correspondence Analysis

2019 ◽  
Vol 8 (1) ◽  
pp. 21
Author(s):  
Fatemeh Rangraz Jeddi ◽  
Fatemeh Atoof ◽  
Raziye Farrahi ◽  
Sara Chopannejad
Keyword(s):  
North America ◽  
Correspondence Analysis ◽  
Medical Tourism ◽  
Service Providers ◽  
General Information ◽  
Cost Comparison ◽  
Legal Information ◽  
Related Information ◽  
Analysis Technique ◽  
Key Factor

Introduction: Medical tourism is the most important aspect of health tourism. The responsibilities of this industry are mostly undertaken by agencies and facilitators acting as intermediaries between patients and service providers. As a key factor, websites provide extensive services to patients for a better presence in medical tourism market. The present study aimed to compare medical tourism websites and facilitators in Iran and other countries using correspondence analysis.Method: Websites were selected based on the specified criteria such as content of websites which were examined using content analysis technique. The data belonging to website content were classified into two groups including medical and tourism services and information and communication issues. Correspondence analysis was done using two R packages (FactoMineR for analysis and fact extra for data visualization).Results: Of 42 selected websites, 19 was belonged to Iran, 11 to North America, 7 to South and Central America, and 5 to Asia. Medical tourism facilitators in North America and Asia tend to provide modern contact and legal information. Against Iranians' facilitators tend to show traditional contact and general information. South American websites provide more information about hospital accreditation. Iranian websites emphasized tourism-related information. Whereas, North American’s are emphasized on cost-comparison lists.Conclusion: Results of the present study provide a snapshot of status of data provided on websites in terms of medical, tourist and communication services available in the studied websites and clearly showed that Iranian medical tourism facilitator websites act differently from those of other countries. Websites play important roles for guiding customers to make decisions regarding the medical journey. Therefore, Iranian medical tourism facilitator websites must reduce their differences with those of other countries in order to be more actively participate and earn more profit in this competitive market.   

scholarly journals Variability and Reproducibility of Directed and Undirected Functional MRI Connectomes in the Human Brain

Entropy ◽  
2019 ◽  
Vol 21 (7) ◽  
pp. 661 ◽  
Author(s):  
Allegra Conti ◽  
Andrea Duggento ◽  
Maria Guerrisi ◽  
Luca Passamonti ◽  
Iole Indovina ◽  
...  
Keyword(s):  
Human Brain ◽  
Functional Mri ◽  
Pearson Correlation ◽  
Related Information ◽  
Matrix Weights ◽  
Graph Metrics ◽  
Large N ◽  
Subject Variability ◽  
Key Factor ◽  
Global And Local

A growing number of studies are focusing on methods to estimate and analyze the functional connectome of the human brain. Graph theoretical measures are commonly employed to interpret and synthesize complex network-related information. While resting state functional MRI (rsfMRI) is often employed in this context, it is known to exhibit poor reproducibility, a key factor which is commonly neglected in typical cohort studies using connectomics-related measures as biomarkers. We aimed to fill this gap by analyzing and comparing the inter- and intra-subject variability of connectivity matrices, as well as graph-theoretical measures, in a large (n = 1003) database of young healthy subjects which underwent four consecutive rsfMRI sessions. We analyzed both directed (Granger Causality and Transfer Entropy) and undirected (Pearson Correlation and Partial Correlation) time-series association measures and related global and local graph-theoretical measures. While matrix weights exhibit a higher reproducibility in undirected, as opposed to directed, methods, this difference disappears when looking at global graph metrics and, in turn, exhibits strong regional dependence in local graphs metrics. Our results warrant caution in the interpretation of connectivity studies, and serve as a benchmark for future investigations by providing quantitative estimates for the inter- and intra-subject variabilities in both directed and undirected connectomic measures.

Variables Sequence Calculating Method in the Process of Bayesian Network Constructing for Battlefield Damage Diagnosis

2014 ◽  
Vol 701-702 ◽  
pp. 98-105
Author(s):  
Guang Yan Wang
Keyword(s):  
Bayesian Network ◽  
Statistical Method ◽  
Simulation Technology ◽  
Damage Diagnosis ◽  
Calculating Method ◽  
Key Factor ◽  
Maintenance Personnel

In order to improve damage diagnosis ability of maintenance personnel, constructing method of Bayesian network applied to weapon battlefield damage diagnosis is researched. Battlefield damage correlations among damaged parts of weapon are analyzed if one weapon is attacked by bombshells, and is the basis of damage diagnosis with the use of Bayesian network. Bayesian network for damage diagnosis is constructed based on K2 arithmetic. Variables sequence is the key factor of Bayesian network constructing, a statistical method of ascertaining variables sequence is presented with the use of weapon battlefield simulation technology.

scholarly journals Variability and Reproducibility of Directed and Undirected Functional MRI Connectomes in the Human Brain

2019 ◽  
Author(s):  
Allegra Conti ◽  
Andrea Duggento ◽  
Maria Guerrisi ◽  
Luca Passamonti ◽  
Iole Indovina ◽  
...  
Keyword(s):  
Human Brain ◽  
Functional Mri ◽  
Pearson Correlation ◽  
Related Information ◽  
Matrix Weights ◽  
Graph Metrics ◽  
Large N ◽  
Subject Variability ◽  
Key Factor ◽  
Global And Local

A growing number of studies focus on methods to estimate and analyze the functional connectome of the human brain. Graph theoretical measures are commonly employed to interpret and synthesize complex network-related information. While resting state functional MRI (rsfMRI) is often employed in this context, is known to exhibit poor reproducibility, a key factor which is commonly neglected in typical cohort studies using connectomics-related measures as biomarkers. We aimed to fill this gap by analyzing and comparing inter- and intra- subject variability of connectivity matrices as well as graph-theoretical measures in a large (n=1003) database of young healthy subjects which underwent four consecutive rsfMRI sessions. We analyzed both directed (Granger Causality and Transfer Entropy) and undirected (Pearson Correlation and Partial Correlation) time-series association measures and related global and local graph-theoretical measures. While matrix weights exhibit a higher reproducibility in undirected as opposed to directed methods, this difference disappears when looking at global graph metrics and, in turn, exhibits strong regional dependence in local graphs metrics. Our results warrant caution in the interpretation of connectivity studies, and serve as a benchmark for future investigations by providing quantitative estimates for the inter- and intra- subject variabilities in both directed and undirected connectomic measures.

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