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Image Transmission Circuit Design Based on Lora System

2023· article· en· W4409724549 on OpenAlexaff
Zhiyan Lin, Tao Hong, Zhihua Chen, Michel Kadoch

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicImage Processing Techniques and Applications
Canadian institutionsÉcole de Technologie Supérieure
FundersNational Natural Science Foundation of China
KeywordsComputer scienceTransmission (telecommunications)Transmission systemElectronic engineeringTelecommunicationsEngineering

Abstract

fetched live from OpenAlex

In recent years, China has faced severe impacts from typhoons, ranking among the countries with the highest losses globally due to these natural disasters. Since 1972, China has prioritized the investigation of typhoon formation mechanisms, trajectory forecasting, and intensity prediction. Current research efforts have concentrated on precise typhoon detection, aiming to conduct fine direct observations within the typhoon core. This paper presents the design of a wireless image transmission circuit utilizing LoRa technology, specifically tailored for downcast sounding applications. Comprising a main control chip's minimum system, a camera module, and an RF antenna circuit, the system integrates the STM32WLE5J8 chip—the world's first microprocessor and RF subsystem two-in-one chip supporting various modulation modes, along with the low-power and compact U.S. Howe Technology OV5640 camera module. The RF antenna, designed with a PE4259 RF switch structure and filter, facilitates mode switching and mitigates clutter to a certain extent. The entire hardware design of the wireless image transmission system is accomplished within the unified design environment of Altium Designer printed circuit boards, encompassing component selection, schematic design, and PCB layout. The final product is a compact, low-power PCB board measuring 5.1cm in length and 4.7cm in width, adaptable to STM32 platform development and proficient in utilizing LoRa communication technology for image data transfer in typhoon environments—offering significant practical insights for application.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.886
Threshold uncertainty score0.418

Codex and Gemma teacher scores by category

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

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 head0.027
GPT teacher head0.242
Teacher spread0.215 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreMethods

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

Citations0
Published2023
Admission routes1
Has abstractyes

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