Incremental Analysis

2021 ◽  
pp. 271-285
Author(s):  
Teddy Steven Cotter
Keyword(s):  
Incremental Analysis

Incremental analysis for generalized TODIM

2015 ◽  
Vol 24 (4) ◽  
pp. 901-922 ◽  
Author(s):  
Yuan-Sheng Lee ◽  
Hsu-Shih Shih
Keyword(s):  
Incremental Analysis

scholarly journals Analisis Kelayakan Investasi Perluasan Pabrik dengan Metode Cost-Volume-Profit dan Incremental pada PT XYZ, Jakarta

2012 ◽  
Vol 3 (1) ◽  
pp. 524
Author(s):  
Jonny Jonny
Keyword(s):  
Limited Capacity ◽  
Operational Cost ◽  
Incremental Analysis ◽  
Corporate Profit ◽  
A Value ◽  
Plant Expansion

PT XYZ received an offer of toll manufacturing services from its client as much as 360 units at a price of Rp14.000 for four years. To be able to fulfill the offer, the company must issue an investment of Rp1,3 billion for the plant expansion regarding to the limited capacity and specificity of the engine that must be purchased separately. There is also some additional operational cost for the company. Based on the analysis of costvolume-profit (CVP) the company realized that the price offered is far below the desired corporate profit by 27% so that the new price agreed upon in the negotiation is Rp16.000. Meanwhile, using the price agreement and macroeconomic assumption for the next four years, the company can finally concluded to accept the offer of its client with a value weighted NPV up to Rp306, 5 million based on the incremental analysis.

Marginal and incremental analysis

2005 ◽  
pp. 310-341
Author(s):  
Hans G. Daellenbach ◽  
Donald C. McNickle
Keyword(s):  
Incremental Analysis

scholarly journals Temporal Label Walk for Community Detection and Tracking in Temporal Network

2019 ◽  
Vol 9 (15) ◽  
pp. 3199 ◽  
Author(s):  
Zheliang Liu ◽  
Hongxia Wang ◽  
Lizhi Cheng ◽  
Wei Peng ◽  
Xiang Li
Keyword(s):  
Community Detection ◽  
Time Window ◽  
Window Size ◽  
Real Data ◽  
Initial Structure ◽  
Data Sets ◽  
Temporal Network ◽  
Incremental Analysis ◽  
Detection And Tracking

The problem of temporal community detection is discussed in this paper. Main existing methods are either structure-based or incremental analysis. The difficulty of the former is to select a suitable time window. The latter needs to know the initial structure of networks and the changing of networks should be stable. For most real data sets, these conditions hardly prevail. A streaming method called Temporal Label Walk (TLW) is proposed in this paper, where the aforementioned restrictions are eliminated. Modularity of the snapshots is used to evaluate our method. Experiments reveal the effectiveness of TLW on temporal community detection. Compared with other static methods in real data sets, our method keeps a higher modularity with the increase of window size.

Numerical Modelling of Masonry Barrel Vaults Reinforced with Textile Reinforced Mortars

2017 ◽  
Vol 747 ◽  
pp. 11-19 ◽  
Author(s):  
Giancarlo Ramaglia ◽  
Gian Piero Lignola ◽  
Francesco Fabbrocino ◽  
Andrea Prota
Keyword(s):  
Numerical Modelling ◽  
Seismic Vulnerability ◽  
Masonry Buildings ◽  
Strengthening Effect ◽  
Ultimate Capacity ◽  
Incremental Analysis ◽  
Heritage Buildings ◽  
Complex Architecture ◽  
Textile Reinforced Mortar ◽  
Barrel Vaults

Among masonry buildings characterized by a complex architecture, a significant portion is represented by heritage buildings. A significant seismic vulnerability is due to the presence of thrusting elements like as arches and vaults. Their ultimate capacity can be improved by means of several strengthening techniques. However the advantages of using Textile Reinforced Mortars (TRM) are well highlighted in the scientific literature.The present work focuses on ultimate behaviour of masonry barrel vaults, in the framework of incremental analysis, including the strengthening effect. The analytical model is compared in terms of ultimate capacity and failure mode with a full scale masonry barrel vault dynamically tested. After the first tests, the vault has been strengthened with Textile Reinforced Mortar (TRM) and tested again.

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