Parallel Visualisation of Computational Engineering Data

2009 ◽  
Author(s):  
J.W. Jones ◽  
N.P. Weatherill
Keyword(s):  
Computational Engineering ◽  
Engineering Data

ASONIKA-UM: management of electronics modeling on external influencing factors during design

2020 ◽  
pp. 51-56
Keyword(s):  
Influencing Factors ◽  
Electronic Equipment ◽  
Radio Electronic ◽  
Engineering Data

Information about ASONIKA-UM are adduced: a subsystem for controlling the modeling of radio-electronic equipment, assigned to collect engineering data in an integrated database that occurs during the design, manufacture and operation of electronic equipment, as well as to ensure the joint usage of these data. Keywords radio-electronic equipment; modeling; database; PDM system

Food Services Menu Engineering: Preference, Acceptability, and Popularity Index of Local Food Package Menus to Control the Glycemic Responses of T2DM Subjects

2020 ◽  
Vol 16 (7) ◽  
pp. 1119-1129
Author(s):  
Nurul Hakimah ◽  
Nur Rahman ◽  
Sucipto Sucipto ◽  
Wignyanto Wignyanto ◽  
Aulanni'am Aulanni'am
Keyword(s):  
Local Food ◽  
Food Service ◽  
Nutrient Content ◽  
Portion Size ◽  
Food Type ◽  
Glycemic Response ◽  
Good Glycemic Control ◽  
Engineering Data ◽  
Food Package ◽  
Post Test

Background: The purpose of this study was to analyze the menu engineering data: preferences, acceptances, and popularity indexes of local food package menus with low to moderate glycemic index and how these variables affect the glycemic response of subjects with type 2 diabetes mellitus (T2DM). Methods: This study was a one group pre and post-test experimental study with 21 T2DM participants. A total of 1,764 menu engineering data were obtained during the two-week study period. Fifteen food service survey questions were distributed and anthropometric and glycemic responses were measured. Results: The popularity indexes of the main and snack package menus were significantly different (p=0,000). There was a significant decrease (p<0.05) in Δ RBG levels by 59.6±115.8 mg/ dL (26.7%) and Δ % albumin glycated by 1.5±1.0 (6.1%) (p = 0.000) on 38% subjects with good glycemic control who consumed less food outside the study (12.5%). Price, type of food, type of foodstuff, nutrient content, portion size, food appearance, food texture, GI values, food menu name, and menu conformity to the environment were important considerations in the menu preference and popularity. Conclusion: This study showed that the local food package menu can control the glycemic response of T2DM participants while having a high popularity index. This finding provides an opportunity for the foodservice industry to operate sustainably by considering the factors desired by consumers with T2DM in controlling their long-term glycemic response.

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