Volt/var Chain Process*

2021 ◽  
pp. 157-340
Author(s):  
Daniel-Leon Schultis ◽  
Albana Ilo
Keyword(s):  
Chain Process

scholarly journals Calibration of Transition Intensities for a Multistate Model: Application to Long-Term Care

Risks ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 37
Author(s):  
Manuel L. Esquível ◽  
Gracinda R. Guerreiro ◽  
Matilde C. Oliveira ◽  
Pedro Corte Real
Keyword(s):  
Markov Chain ◽  
Continuous Time ◽  
Long Term Care ◽  
Transition Probabilities ◽  
Markov Chain Model ◽  
Chain Model ◽  
Chain Process ◽  
Term Care ◽  
National Network

We consider a non-homogeneous continuous time Markov chain model for Long-Term Care with five states: the autonomous state, three dependent states of light, moderate and severe dependence levels and the death state. For a general approach, we allow for non null intensities for all the returns from higher dependence levels to all lesser dependencies in the multi-state model. Using data from the 2015 Portuguese National Network of Continuous Care database, as the main research contribution of this paper, we propose a method to calibrate transition intensities with the one step transition probabilities estimated from data. This allows us to use non-homogeneous continuous time Markov chains for modeling Long-Term Care. We solve numerically the Kolmogorov forward differential equations in order to obtain continuous time transition probabilities. We assess the quality of the calibration using the Portuguese life expectancies. Based on reasonable monthly costs for each dependence state we compute, by Monte Carlo simulation, trajectories of the Markov chain process and derive relevant information for model validation and premium calculation.

HYDROLOGICAL DROUGHT FORECASTS USING MARKOV CHAINS AND REGRESSION MODELS (A CASE STUDY FOR NORTHWEST OF ALGERIA)

2021 ◽  
pp. 90-103
Author(s):  
A. RAHMOUNI ◽  
◽  
M. MEDDI ◽  
A. HAMOUDI SAAED ◽  
◽  
...  
Keyword(s):  
Lead Time ◽  
Robust Regression ◽  
Forecast Accuracy ◽  
Hydrological Drought ◽  
Lead Times ◽  
Chain Process ◽  
Markov Switching Model ◽  
North West ◽  
Switching Model ◽  
The North

An effective drought forecast is an important measure to mitigate some of its most damaging impacts. In this study we compare the effectiveness of two models: Markov Switching Model (MSM) and Robust Regression Model (RRM) with three different approaches to forecast hydrological drought events in the north-west of Algeria using Standardized Runoff Index (SRI). The validation of these models is carried out by hydro-climatic series of 41 stations for the period of 1968-2009. The values of SRI 3, SRI 6, and SRI 12 have been forecasted over lead times of 1 and 6 months. The performance of forecast results is measured using R2 and RMSE. For the lead time of 1 month, the results are quite similar for both models with slight superiority for the Markov chain process. The addition of the SPI or RDI indices as independent variables improves this performance for some stations while it decreases accuracy for other stations. However, forecast accuracy declines significantly as the lead time increases to 6 months particularly for regression results.

Blockchain and 6G-Based Supply Chain Management Framework for Oil and Gas Shipment

2021 ◽  
Author(s):  
Md Abdur Rahman ◽  
Syed M. Belal
Keyword(s):  
Supply Chain ◽  
Supply Chain Management ◽  
Oil And Gas ◽  
Current System ◽  
Oil And Gas Industry ◽  
Chain Process ◽  
Chain Management ◽  
It Systems ◽  
Supply Chain Management System ◽  
Gas Supply

Abstract Keeping track of the oil and gas supply chain is challenging task as the route and transportation requires sophisticated security environment - both physical systems’ and IT systems’ security. Thanks to the recent advancement in IoT, specialized sensors can keep track of the required supply chain environment. With the help of blockchain, the supply chain data can be immutably saved for further sharing with stakeholders. Due to the introduction of AI as an embedded element within 6G networks, the end-to-end supply chain process can now be automated for safety, security, and efficiency purposes. By leveraging 6G, AI, blockchain, and IoT, the supply chain data during the transportation or at rest can be monitored for any changed environment during the movement of the ship through national or international routes. In this paper, we study the requirements of such intelligent and secure supply chain management system conducive to the oil and gas industry. We also show our proof-of-concept implementation and initial test results. Our obtained results show promising prospect of the current system to be deployed to safeguard the oil and gas supply chain.

Applying Industry 4.0 technologies in the COVID–19 sustainable chains

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Carina Acioli ◽  
Annibal Scavarda ◽  
Augusto Reis
Keyword(s):  
Supply Chain ◽  
Supply Chains ◽  
Industry 4.0 ◽  
Supply Chain Performance ◽  
Chain Process ◽  
Sustainable Supply Chain ◽  
Content Type ◽  
Sustainable Performance ◽  
The Social ◽  
New Research

PurposeThe purpose of this paper is 1) to investigate the effects on the crucial Industry 4.0 technological innovations that interact between the real and virtual worlds and that are applied in the sustainable supply chain process; 2) to contribute to the identification of the opportunities, the challenges and the gaps that will support the new research study developments and 3) to analyze the impact of the Industry 4.0 technologies as facilitators of the sustainable supply chain performance in the midst of the Coronavirus (COVID-19).Design/methodology/approachThis research is performed through a bibliographic review in the electronic databases of the Emerald Insight, the Scopus and the Web of Science, considering the main scientific publications on the subject.FindingsThe bibliographic search results in 526 articles, followed by two sequential filters for deleting the duplicate articles (resulting in 487 articles) and for selecting the most relevant articles (resulting in 150 articles).Practical implicationsThis article identifies the opportunities and the challenges focused on the emerging Industry 4.0 theme. The opportunities can contribute to the sustainable performance of the supply chains and their territories. The Industry 4.0 can also generate challenges like the social inequalities related to the position of the man in the labor market by replacing the human workforce with the machines. Therefore, the man-machine relationship in the Industry 4.0 era is analyzed as a gap in the literature. Therefore, as a way to fill this gap, the authors of this article suggest the exploration of the research focused on the Society 5.0. Also known as “super-smart society,” this recent theme appeared in Japan in April 2016. According to Fukuda (2020), in addition to the focus on the technological development, the Society 5.0 also aims at the quality of life and the social challenge resolutions.Originality/valueThis article contributes to the analysis of the Industry 4.0 technologies as facilitators in the sustainable supply chain performance. It addresses the impacts of the Industry 4.0 technologies applied to the supply chains in the midst of the COVID-19 pandemic, and it analyzes the research gaps and limitations found in the literature. The result of this study can add value and stimulate new research studies related to the application of the Industry 4.0 technologies as facilitators in the supply chain sustainable performance. It can encourage the studies related to the COVID-19 impacts on the sustainable supply chains, and it can promote the research development on the relationship among the man, the machine and the labor in the Fourth Industrial Revolution.

How novice analysts understand supply chain process models: an experimental study of using diagrams and texts

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Joerg Leukel ◽  
Vijayan Sugumaran
Keyword(s):  
Supply Chain ◽  
Information Acquisition ◽  
Empirical Evaluation ◽  
Process Models ◽  
Chain Process ◽  
Content Type ◽  
Textual Representations ◽  
Scor Model ◽  
Supply Chain Process ◽  
Diagram Group

PurposeProcess models specific to the supply chain domain are an important tool for the analysis of interorganizational interfaces and requirements of information technology (IT) systems supporting supply chain decision-making. The purpose of this study is to examine the effectiveness of supply chain process models for novice analysts in conveying domain semantics compared to alternative textual representations.Design/methodology/approachA laboratory experiment with graduate students as proxies for novice analysts was conducted. Participants were randomly assigned to either the diagram group, which worked with “thread diagrams” created from the modeling grammar “Supply Chain Operation Reference (SCOR) model”, or the text group, which worked with semantically equivalent textual representations. Domain understanding was measured using cognitively demanding information acquisition for two different domains.FindingsDiagram users were more accurate in identifying product-related information and organizing this information in a graph compared to those using the textual representation. The authors found considerable improvements in domain understanding, and using the diagrams was perceived as easy as using the texts.Originality/valueThe study's findings are unique in providing empirical evidence for supply chain process models being an effective representation for novice analysts. Such evidence is lacking in prior research because of the evaluation methods used, which are limited to scenario, case study and informed argument. This study adds the diagram user's perspective to that literature and provides a rigorous empirical evaluation by contrasting diagrammatic and textual representations.

Value creation through expanding the online distribution channel

2020 ◽  
Vol 120 (4) ◽  
pp. 714-729
Author(s):  
Frank Wiengarten ◽  
Hugo K.S. Lam ◽  
Di Fan
Keyword(s):  
Supply Chain ◽  
Stock Market ◽  
Value Creation ◽  
Distribution Channel ◽  
Chain Process ◽  
Market Reactions ◽  
Content Type ◽  
Creation Process ◽  
Stock Market Reactions ◽  
Value Creation Process

PurposeCurrent literature provides limited insights into the supply chain contexts within which e-commerce can create higher value for firms. To address this literature gap, this research explores the value potential, and thus value creation process, of e-commerce initiatives for supply chain distribution channel expansions.Design/methodology/approachUsing secondary data collected from multiple sources, this research conducted an event study to examine the stock market reactions to the announcements of e-commerce initiatives of Chinese firms.FindingsThe results indicate that the e-commerce initiatives increase average firm value by CNY 295.29 million in a three-day window around the initiative's announcement date. Moreover, we find that such stock market reactions are more positive for firms with poor operating performance, and more negative when firms deploy initiatives on their own (rather than third-party) platforms. Further, companies that integrate or complement their online sales with an offline sales channel experience more positive stock market reactions.Originality/valueThis study provides new insights into the value creation process of e-commerce from an operation and supply chain process perspective.

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