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Record W4410602309 · doi:10.26636/jtit.2025.2.2085

Using a Half-mode SIW Loaded with Slots to Realize a Compact UWB Bandpass Filter

2025· article· en· W4410602309 on OpenAlexaff
Hussein Al-Jeshami, Hussam Al‐Saedi, Mohammed F. Hasan, Halah I. Khani, Muhannad Y. Muhsin, Wael M. Abdel‐Wahab

Bibliographic record

VenueJournal of Telecommunications and Information Technology · 2025
Typearticle
Languageen
FieldEngineering
TopicMicrowave Engineering and Waveguides
Canadian institutionsCanadian Water NetworkUniversity of Waterloo
Fundersnot available
KeywordsBand-pass filterMode (computer interface)Filter (signal processing)Electronic engineeringComputer scienceAcousticsMaterials sciencePhysicsEngineering

Abstract

fetched live from OpenAlex

This paper presents an ultra-wideband bandpass filter (UWB-BPF) based on a half-mode substrate-integrated waveguide (HMSIW) structure with a passband that spans from 4.12 to 11 GHz and has a center frequency of 7.56 GHz with a fractional bandwidth of 91%. Less than 0.3 dB of insertion loss was achieved through the passband, with the return loss being better than 19 dB. Two transmission zeros were generated, contributing to the 5.24 GHz out-of-band rejection. The proposed filter is compact, making it a good choice for space-constrained systems. In addition, a notch response has been utilized to comply with standards issued by applicable regulatory bodies, by blocking some bands located in the passband. Ansys EDT software was used to implement the design and determine the response of the proposed structure, while Keysight ADS was used to validate the results.

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)0.000
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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)0.0010.001

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 head0.011
GPT teacher head0.255
Teacher spread0.245 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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