A Comparison of Numeric Data Entry with Touch-Sensitive and Conventional Numeric Keypads

1985 ◽  
Author(s):  
D. G. Leupp ◽  
S. Kelly ◽  
D. E. Bridges
Keyword(s):  
Data Entry ◽  
Numeric Data

P‐28: Investigating the Usability of Touchscreen Interfaces in a Turbulent Flight Deck – For Panning and Numeric Data Entry Tasks

2020 ◽  
Vol 51 (1) ◽  
pp. 1438-1441
Author(s):  
Mark A. Smith ◽  
Katherine L. Plant ◽  
Katie J. Parnell ◽  
Rachael A. Wynne ◽  
Neville A. Stanton
Keyword(s):  
Data Entry ◽  
Numeric Data ◽  
Flight Deck

An Investigation of Techniques for Occasional Numeric Data Entry

1989 ◽  
Vol 33 (5) ◽  
pp. 310-314
Author(s):  
Joel S. Greenstein ◽  
Anish Baijal
Keyword(s):  
Data Entry ◽  
The Other ◽  
Numeric Data

This work tested six techniques for the occasional entry of unstructured numeric data in the context of a primarily mouse-based, cursor-positioning, human-computer dialogue. Two of the techniques used a separate keypad for numeric data entry. The other four techniques used the mouse already being used for the cursor positioning dialogue. The keypad techniques were more efficient than the mouse techniques for all of the numeric sequence lengths considered. There were no significant differences in efficiency between the two keypad techniques. Among the mouse-based techniques, an approach based on a displayed image of a calculator keypad was consistently among the most efficient.

SPECTRA: A program for processing electron images of crystals

1992 ◽  
Vol 50 (1) ◽  
pp. 132-133
Author(s):  
M.F. Schmid ◽  
R. Dargahi ◽  
M. W. Tam
Keyword(s):  
Lattice Distortion ◽  
Data Transfer ◽  
Reciprocal Lattice ◽  
Data Entry ◽  
Image Data ◽  
Distortion Correction ◽  
Specimen Preparation ◽  
Electron Image ◽  
Computer Controlled ◽  
Program Modules

Electron crystallography is an emerging field for structure determination as evidenced by a number of membrane proteins that have been solved to near-atomic resolution. Advances in specimen preparation and in data acquisition with a 400kV microscope by computer controlled spot scanning mean that our ability to record electron image data will outstrip our capacity to analyze it. The computed fourier transform of these images must be processed in order to provide a direct measurement of amplitudes and phases needed for 3-D reconstruction.In anticipation of this processing bottleneck, we have written a program that incorporates a menu-and mouse-driven procedure for auto-indexing and refining the reciprocal lattice parameters in the computed transform from an image of a crystal. It is linked to subsequent steps of image processing by a system of data bases and spawned child processes; data transfer between different program modules no longer requires manual data entry. The progress of the reciprocal lattice refinement is monitored visually and quantitatively. If desired, the processing is carried through the lattice distortion correction (unbending) steps automatically.

Better Data Entry: Double Entry Is Superior to Visual Checking

2008 ◽  
Author(s):  
Kimberly A. Barchard ◽  
Jenna Scott ◽  
David Weintraub ◽  
Larry A. Pace
Keyword(s):  
Data Entry ◽  
Double Entry

A Model for Structured Data Entry Based on Explicit Descriptional Knowledge

1994 ◽  
Vol 33 (05) ◽  
pp. 454-463 ◽  
Author(s):  
A. M. van Ginneken ◽  
J. van der Lei ◽  
J. H. van Bemmel ◽  
P. W. Moorman
Keyword(s):  
Domain Knowledge ◽  
Data Entry ◽  
Knowledge Bases ◽  
Structured Data ◽  
Research Quality ◽  
Free Text ◽  
Specific Knowledge ◽  
User Input ◽  
The One ◽  
Research Quality Assessment

Abstract:Clinical narratives in patient records are usually recorded in free text, limiting the use of this information for research, quality assessment, and decision support. This study focuses on the capture of clinical narratives in a structured format by supporting physicians with structured data entry (SDE). We analyzed and made explicit which requirements SDE should meet to be acceptable for the physician on the one hand, and generate unambiguous patient data on the other. Starting from these requirements, we found that in order to support SDE, the knowledge on which it is based needs to be made explicit: we refer to this knowledge as descriptional knowledge. We articulate the nature of this knowledge, and propose a model in which it can be formally represented. The model allows the construction of specific knowledge bases, each representing the knowledge needed to support SDE within a circumscribed domain. Data entry is made possible through a general entry program, of which the behavior is determined by a combination of user input and the content of the applicable domain knowledge base. We clarify how descriptional knowledge is represented, modeled, and used for data entry to achieve SDE, which meets the proposed requirements.

Information System for Post-marketing Drug Surveillance Scheme on Small Computers

1982 ◽  
Vol 21 (04) ◽  
pp. 181-186 ◽  
Author(s):  
M. A. A. Moussa
Keyword(s):  
Information System ◽  
Data Base ◽  
Data Transfer ◽  
Data Entry ◽  
Drug Reactions ◽  
Adverse Drug Reaction Monitoring ◽  
Desktop Computers ◽  
Post Marketing ◽  
The State Of Kuwait ◽  
Disc Drive

A drug information system (DARIS) has been created for handling reports on suspected drug reactions. The system is suitable for being run on desktop computers with a minimum of hardware requirements: 187 K read/write memory, flexible or hard disc drive and a thermal printer. The data base (DRUG) uses the QUERY and IMAGE programming capabilities for data entry and search. The data base to statistics link program (DBSTAT) enables data transfer from the data base into a file for statistical analysis and signalling suspected adverse drug reactions.The operational, medical and statistical aspects of the general population voluntary adverse drug reaction monitoring programme—recently initiated in the State of Kuwait—are described.

Improving Coded Data Entry by an Electronic Patient Record System

1996 ◽  
Vol 35 (02) ◽  
pp. 108-111 ◽  
Author(s):  
F. Puerner ◽  
H. Soltanian ◽  
J. H. Hohnloser
Keyword(s):  
Phase I ◽  
Electronic Patient Record ◽  
Data Entry ◽  
Discharge Summary ◽  
Patient Record ◽  
Phase Iii ◽  
Electronic Patient Record System ◽  
Record System ◽  
Data Encoding ◽  
Discharge Summaries

AbstractData are presented on the use of a browsing and encoding utility to improve coded data entry for an electronic patient record system. Traditional and computerized discharge summaries were compared: during three phases of coding ICD-9 diagnoses phase I, no coding; phase II, manual coding, and phase III, computerized semiautomatic coding. Our data indicate that (1) only 50% of all diagnoses in a discharge summary are encoded manually; (2) using a computerized browsing and encoding utility this percentage may increase by 64%; (3) when forced to encode manually, users may “shift” as much as 84% of relevant diagnoses from the appropriate coding section to other sections thereby “bypassing” the need to encode, this was reduced by up to 41 % with the computerized approach, and (4) computerized encoding can improve completeness of data encoding, from 46 to 100%. We conclude that the use of a computerized browsing and encoding tool can increase data quality and the percentage of documented data. Mechanisms bypassing the need to code can be avoided.

Structured Data Entry for Reliable Acquisition of Pharmacokinetic Data

1996 ◽  
Vol 35 (03) ◽  
pp. 261-264 ◽  
Author(s):  
T. Schromm ◽  
T. Frankewitsch ◽  
M. Giehl ◽  
F. Keller ◽  
D. Zellner
Keyword(s):  
Text Processing ◽  
Data Entry ◽  
Processing System ◽  
Database System ◽  
Structured Data ◽  
Pharmacokinetic Parameters ◽  
Pharmacokinetic Data ◽  
Probability Of Error ◽  
Error Frequency ◽  
Estimated Error

Abstract:A pharmacokinetic database was constructed that is as free of errors as possible. Pharmacokinetic parameters were derived from the literature using a text-processing system and a database system. A random data sample from each system was compared with the original literature. The estimated error frequencies using statistical methods differed significantly between the two systems. The estimated error frequency in the text-processing system was 7.2%, that in the database system 2.7%. Compared with the original values in the literature, the estimated probability of error for identical pharmacokinetic parameters recorded in both systems is 2.4% and is not significantly different from the error frequency in the database. Parallel data entry with a text-processing system and a database system is, therefore, not significantly better than structured data entry for reducing the error frequency.

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