THE OPERATIONAL FLOATING CURRENT CONVEYOR AND ITS APPLICATIONS
Bibliographic record
Abstract
A five-port general-purpose analog building block, termed as an Operational Floating Current Conveyor (OFCC), is described. The OFCC combines the features of current feedback operational amplifier, second-generation current conveyor and operational floating conveyor. An implementation scheme of the OFCC is described and its terminal operational characteristics are used to yield a working device. The OFCC is then used as a single block to realize the current conveyors (CCII+ and CCII-) as well as the four basic amplifiers (i.e., voltage, current, transconductance, and transresistance amplifiers). The applications of the OFCC are presented and discussed. In the field of the analog filter synthesis, we proposed a new active universal second order filter using OFCC. It has three inputs and one output employing two OFCC, two capacitors and three resistors and can realize lowpass, bandpass, highpass, notch, and all pass filters from the same configuration. The proposed universal filters offer the following advantageous features: using active elements for the same type (OFCC). No requirement for component matching or cancellation constraints, which makes the filter easier to design, orthogonal adjustment of ω0 and Q and the circuits have low sensitivity. The simulation and experimental results are obtained and discussed.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".