scholarly journals Sending data from excel to autocad

Author(s):  
Alexandru BABA ◽  

The interaction between Excel and AutoCad using VBA is useful for all engineers who use AutoCad, so in this article I want to show that using VBA in Excel candraw objects in AutoCad. Therefore, by programming in VBA from Excel, you can launch AutoCAD and with the help of a spreadsheet application we transmit the data in AutoCAD to draw objects

2012 ◽  
Vol 39 (9) ◽  
pp. 1072-1082 ◽  
Author(s):  
Ali Montaser ◽  
Ibrahim Bakry ◽  
Adel Alshibani ◽  
Osama Moselhi

This paper presents an automated method for estimating productivity of earthmoving operations in near-real-time. The developed method utilizes Global Positioning System (GPS) and Google Earth to extract the data needed to perform the estimation process. A GPS device is mounted on a hauling unit to capture the spatial data along designated hauling roads for the project. The variations in the captured cycle times were used to model the uncertainty associated with the operation involved. This was carried out by automated classification, data fitting, and computer simulation. The automated classification is applied through a spreadsheet application that classifies GPS data and identifies, accordingly, durations of different activities in each cycle using spatial coordinates and directions captured by GPS and recorded on its receiver. The data fitting was carried out using commercially available software to generate the probability distribution functions used in the simulation software “Extend V.6”. The simulation was utilized to balance the production of an excavator with that of the hauling units. A spreadsheet application was developed to perform the calculations. An example of an actual project was analyzed to demonstrate the use of the developed method and illustrates its essential features. The analyzed case study demonstrates how the proposed method can assist project managers in taking corrective actions based on the near-real-time actual data captured and processed to estimate productivity of the operations involved.


1999 ◽  
Vol 14 (2) ◽  
pp. 233-253 ◽  
Author(s):  
Mark Rusbarsky ◽  
David B. Vicknair

This article explains how to apply brokers' valuation methods to accounting for bonds when interest payments do not coincide with settlement or balance sheet dates. We show how to calculate a bond's present value on these dates using a simple approach that conforms with the method used by brokerage institutions to compute the bond's “actual price.” We then clarify how a broker subtracts accrued interest from this actual price to arrive at the quoted price, and how this quoted price relates to the bond's carrying amount and “fair value” (per SFAS Nos. 107, 115 and 124). We also precisely compute the change in a bond's carrying amount over fractional periods after settlement and around balance sheet dates. Finally, we demonstrate how to integrate these refinements into intermediate textbook illustrations. Throughout, we provide instructions for computing bond valuations using spreadsheet application functions.


2006 ◽  
Vol 52 (5) ◽  
pp. 880-885 ◽  
Author(s):  
Graham Ross Dallas Jones

Abstract Background: The reporting interval is the bin size used to report numerical pathology results and must be determined for every analyte. The influence of the size of the reporting interval on the critical difference (CD) between two results from the same patient has not been addressed previously. Methods: The effect of changing the reporting-interval size (RIS) on CDs was modeled by use of a spreadsheet application. The findings were applied to data on CDs with analytical precision values from our laboratory. Results: As the RIS increases relative to the combined analytical and within-person biological variation, there is an approximately linear increase in the CD from the value determined by use of published techniques. The revised estimate is as follows: CD = 21/2 × z × (SDa2 + SDi2)1/2 + 1.5 × RIS, where CD, SD, and RIS are all in the same units. This effect is seen for any probability associated with the critical difference and for both uni- and bidirectional changes. Conclusions: The choice of reporting interval should be made in the light of assay requirements. Where there is a clinical need for detection of small changes in analyte concentration, the reporting interval should be kept small relative to the combined variation attributable to assay precision and within-person biological variation.


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