MétaCan
Menu
Back to cohort
Record W4406494786 · doi:10.18260/1-2-1153-49662

21st Century Challenges: Integrating Fundamentals Into State-Of-The-Art Technology Curricula Complimented by Hands on Experience in Laboratories

2025· article· en· W4406494786 on OpenAlexaboutno aff
Kanti Prasad

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicExperimental Learning in Engineering
Canadian institutionsnot available
Fundersnot available
KeywordsCurriculumState (computer science)Computer scienceEngineering ethicsEngineering managementEngineeringPsychologyProgramming languagePedagogy

Abstract

fetched live from OpenAlex

In order to prepare the workforce for VLSI program, theoretical instructions must integrate fundamentals and be complemented with adequate laboratory facilities in order to validate the design from its conception to the finished chip along with its real time testing.This comprises of four distinct and disparate phases namely-Phase 1: Chip design -This basically involves the design of the chip based on specifications provided by the customer, Phase 2: Mask Set -It involves the conversion of design's layout and placement into set of masks e.g.diffusion, contact, and metallization masks etc., Phase 3: Mask Transfer -This involves transferring the mask set onto a wafer substrate such as Si or GaAs etc., Phase 4: Packaged Chip -This incorporates inscribing, dicing, die bonding, wire bonding and encapsulating chip.The author proposed an innovative Education Model at Canadian Conference of Engineering Education held at Helifax (Canada) in 1994.It incorporates (1) Fundamentals, (2) Materials, (3) Devices, (4) Circuits, and (5) Systems, which are of vial importance.The author has been providing such an integral Education since 1984 wherein he has received significant amount of funding over the years from Massachusetts Microelectronics Center, MA/Com., Intel Corporation, Raytheon Company, and Sander's Corporation etc.He is still receiving substantial amount of funding from Skyworks Solutions and Analog Devices since the establishment of Microelectronics center at University of Massachusetts Lowell in 1986, the author being the founding director.For in-depth microelectronics education, State-of-the-Art laboratory facilities are required to complement theoretical instructions in order to validate the modeled microelectronic design from its conception to the finished chip along with its real time testing.The system design in general and VLSI system design in particular needs multi disciplinary skills.These Microelectronics/VLSI models address their problem adequately.In order to become an integral Microelectronics/VLSI designer one needs to inculcate skills in design, simulation, testing, verification and validation.This requires a special commitment of funds, which are beyond budgetary allocations of most of the schools.It is because of this reason forging a partnership between academia and industry is of vital importance.The author is not only successful in forging such a partnership with the industry but has also developed curriculum along state-of-the-art facilities in VLSI design and fabrication.

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)0.010
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.017
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.009
Scholarly communication0.0170.013
Open science0.0020.018
Research integrity0.0050.006
Insufficient payload (model declined to judge)0.0090.003

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 head0.006
GPT teacher head0.250
Teacher spread0.244 · 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 designTheoretical or conceptual
Domainnot available
GenreCommentary

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
Published2025
Admission routes1
Has abstractyes

Explore more

Same topicExperimental Learning in EngineeringFrench-language works237,207