Bibliographic record
Abstract
Traditionally, home automation systems use rudimentary forms of instrumentation and control. However, tremendous potential in this field coupled with research has produced more sophisticated solutions. This paper presents a project that provides a comprehensive home automation system using fuzzy logical control and 2-way voice communications. The fuzzy logic rules are based on human experience. The project has typical applications in a home (or in office). The digital communication for all discrete controls is based on X10 protocol, while the analog input for the Temperature control is based on 1-wire technology(TM). A desktop PC (Personal Computer) provides supervisory control. Additionally, the system can be interfaced via the Voice controller that provides interaction with the system through human voice. System commands can be input through the voice commands. Since the human voice pattern is unique, the software provides training to improve voice recognition. The code is written in Visual Basic 6 using Active X controls. Suitable user-friendly graphics are presented to operate the system easily. The goal of the system is to provide reliable control to the common and important household devices and also to conserve energy. (Abstract shortened by UMI.)Dept. of Electrical and Computer Engineering. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2002 .H37. Source: Masters Abstracts International, Volume: 41-04, page: 1152. Adviser: H. K. Kwan. Thesis (M.A.Sc.)--University of Windsor (Canada), 2002.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 0.004 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".