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Usage of single-chip computers for control MIMO systems

2017· article· en· W2729205070 on OpenAlexfundno aff
Jiří Czebe, Jaromír Škuta

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicWireless Sensor Networks for Data Analysis
Canadian institutionsnot available
FundersCanadian Patient Safety Institute
KeywordsComputer scienceMicrocontrollerMIMOEmbedded systemKey (lock)Control systemInterface (matter)Computer hardwareChipSCADAComputer networkOperating systemEngineeringTelecommunicationsElectrical engineering

Abstract

fetched live from OpenAlex

This paper deals with usage of single-chip computers for controlling MIMO systems. The aim is to design a general control system, which is easy to use and easy to implement for other MIMO systems. The performance of control system is limited by the performance of used MCU (PIC 16F876A) and its peripherals (2×PWM, 8×A/D, MAC, …). The key tasks of MCU are communication with upper level and implementation of required control action together with data collection. The serial interface provides communication between control system (PC) and MCU. SCADA/HMI system monitors a controlled system. The application is accessible via Internet browser in local area network (LAN).

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.031
GPT teacher head0.248
Teacher spread0.217 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations6
Published2017
Admission routes1
Has abstractyes

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