Selection of digital terrain data base parameters for radiocommunication system planning applications

1993 ◽  
Vol 39 (3) ◽  
pp. 335-343 ◽  
Author(s):  
F. Perez Fontan ◽  
J.M. Hernando Rabanos
Keyword(s):  
Data Base ◽  
System Planning ◽  
Digital Terrain ◽  
Base Parameters ◽  
Selection Of

Marketing Literature Review

1987 ◽  
Vol 51 (2) ◽  
pp. 121-133
Author(s):  
Paul S. Speck
Keyword(s):  
Literature Review ◽  
Data Base ◽  
Line Search ◽  
Marketing Literature ◽  
On Line ◽  
Business Data ◽  
Selection Of

This section is based on a selection of article abstracts from a comprehensive business literature data base. Marketing-related abstracts from over 125 journals (both academic and trade) are reviewed by JM staff. Descriptors for each entry are assigned by JM staff. Each issue of this section represents three months of entries into the data base. JM wishes to thank Data Courier Inc for use of the ABI/INFORM business data base. Each entry has an identifying number. Cross-references appear immediately under each subject heading. Requests for specific articles should be directed to the specific publication named or to Data Courier Inc. (800/626–2823). Abstracts of the articles are contained in the ABI/INFORM data base which is available through many on-line search vendors.

Decontamination Method Data Base

2001 ◽  
Author(s):  
E. P. Emets ◽  
G. Yu. Kolomeytsev ◽  
P. P. Polouektov ◽  
V. V. Shirokov ◽  
A. N. Yakovets
Keyword(s):  
Specific Surface ◽  
Data Base ◽  
Relational Model ◽  
Selection Algorithm ◽  
Literature Source ◽  
Computer Based ◽  
Record Selection ◽  
Decision Making Tool ◽  
Major Data ◽  
Selection Of

Abstract The Decontamination Method Data-Base (DMDb) is a versatile decision support information system. It is a computer based decision making tool which assists in the selection of best choice of metal surface decontamination technologies, procedures and agents. It is meant for educated and skilled experts in radiochemistry and for specialists in physics, chemistry, physical chemistry and other fields. The database has been developed to meet typical demands of users specialising in the decontamination of radiolagically contaminated materials and considers: • detergent compositions for a specific contaminant; • detergent compositions for a specific surface being decontaminated; • detergent compositions for cleaning a specific surface of a specific contaminant; • decontamination parameters in view of the composition of a detergent; • corrosion effects in different conditions; • etc. In this connection, the major data entity of the database is a unit record describing a decontamination technology for a specific contaminated surface. The unit record contains information on the surface material, contamination, decontamination effectiveness, corrosion impacts and a literature source. The data presentation makes possible the realization of a record selection algorithm for a “lay” user to support the decontamination decision approaching the best one. The analysis of the unit record subject and structure served as the basis for developing relational model “Tables – Relationships” and a tentative alternative of a user interface. Experimental records were entered to optimize users’ inquiries on the composition and corrosion effects of detergents under various conditions.

Hygrothermal Material Properties Database

2015 ◽  
Vol 365 ◽  
pp. 166-171
Author(s):  
João M.P.Q. Delgado
Keyword(s):  
Data Analysis ◽  
Data Base ◽  
Material Properties ◽  
Raw Data ◽  
Material Data ◽  
Stochastic Data ◽  
Definition Of ◽  
Selection Of

The principles and tools for the development of a stochastic data base that can be useful for researchers and practitioners is an objective of this work. This paper explores the construction of that data base, focusing on material properties. Principles for that construction are proposed, including: selected properties, required raw data and deliverable format. These principles are derived from possible applications of the data base and available tools for data analysis. The selection of statistics tools that can be used in the construction of a material data base is addressed. The definition of the statistic distribution for selected properties was pursued. Available raw data was analysed resulting in conclusions on difficulties and opportunities that arise from that.

Comments on the use of Conversational Features in Studies of the Vocalization Behaviours of Mothers and Infants

1984 ◽  
Vol 7 (2) ◽  
pp. 177-191 ◽  
Author(s):  
Gordon Elias ◽  
Jack Broerse ◽  
Alan Hayes ◽  
Ken Jackson
Keyword(s):  
Data Base ◽  
Statistical Inference ◽  
Odds Ratio ◽  
Unit Of Analysis ◽  
Infant Vocalization ◽  
Alternative Approaches ◽  
Expected Values ◽  
Selection Of

Observations of six mother-infant dyads at infant ages of approximately 13 weeks, 20 weeks, 27 weeks and 35 weeks served as a data base to examine difficulties associated with the use of conversational features (such as the avoidance of coaction) in the analysis of mother-infant vocalization episodes. The difficulties are associated with procedures involving: (i) The pooling of data, (ii) The unit of analysis, and (iii) The selection of appropriate 'expected' values for dyadic parameters used in tests of statistical inference. To illustrate these difficulties, the use of the odds ratio statistic as a means of determining such dependence is examined and alternative approaches are suggested.

scholarly journals Analysis of Influencing Factors of Heat Load of Heating Power Station

2021 ◽  
Vol 252 ◽  
pp. 01042
Author(s):  
Yu Lu ◽  
Rui Li
Keyword(s):  
Influencing Factors ◽  
Heat Load ◽  
Load Forecasting ◽  
Heating System ◽  
Heating Power ◽  
Power Station ◽  
System Planning ◽  
Factors Affecting ◽  
Heating Load ◽  
Selection Of

Heating system load forecasting is very important in heating system planning and formulating heating plans. More accurate load forecasting can obtain greater economic and social benefits for the heating power station. The selection of influencing factors affecting heating load forecasting has a decisive effect on the accuracy of load forecasting. Based on the analysis of heat load of typical heating power station, this paper compares and analyses the influence of outdoor temperature, wind speed and load of previous days, etc. The main factors that should be considered in heating load forecasting are obtained.

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