GitHub topics: smell

Repositories

cnumr/best-practices-mobile

📱 Mobile Ecodesign Best Practices (for developers)

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seanpm2001/CompuSmell_Docs

♨️👃️🐽️💄️📖️ The official documentation source repository for the CompuSmell computer scent project.

Language: Markdown - Size: 2.03 MB - Last synced at: about 3 hours ago - Pushed at: 12 months ago - Stars: 2 - Forks: 1

troessner/reek

Code smell detector for Ruby

Language: Ruby - Size: 5.7 MB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 4,079 - Forks: 281

Aim of this research is to identify code smells in the Python dataset by combining sophisticated data resampling techniques with ensemble learning approaches. We looked into the most effective ensemble learning techniques for identifying smells in the Python code. Next, we enhance the performance of conventional machine learning models.

Language: Jupyter Notebook - Size: 3.08 MB - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 0 - Forks: 0

seanpm2001/ARCHIVE_CompuSmell.github.io

🗄️🌐️ Archive of the former seanpm2001 site, CompuSmell.github.io

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seanpm2001/CompuSmell

The official repository for the CompuSmell project, aiming to bring programmed scent emission to computing.

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GeoffreyHecht/paprika

Paprika is a powerfull toolkit to detect some code smells in analysed Android applications.

Language: Java - Size: 341 MB - Last synced at: 5 days ago - Pushed at: almost 6 years ago - Stars: 74 - Forks: 16

JAYDIPSINH27/FurrEverHome

FurreverHome is a web-based pet adoption platform connecting animal shelters with potential adopters.This platform streamlines the pet adoption process by providing a user-friendly interface for shelters to manage pet listings and for adopters to find their perfect companions. Built with React.js and Spring Boot using Test Driven Development

Language: Java - Size: 24.7 MB - Last synced at: 3 months ago - Pushed at: 11 months ago - Stars: 0 - Forks: 0

omorest/raycast-code-smells

Raycast extension to search code smells bases on Code Smells Catalog by

Language: TypeScript - Size: 11.3 MB - Last synced at: 12 months ago - Pushed at: 12 months ago - Stars: 0 - Forks: 0

kzaikin/test-smells

Test Smells for Android developers

Language: Java - Size: 140 KB - Last synced at: 24 days ago - Pushed at: about 6 years ago - Stars: 124 - Forks: 8

krishan57gupta/The-cellular-basis-of-the-loss-of-smell-in-2019-nCoV-infected-individuals

A prominent clinical symptom of 2019-nCoV infection is hyposmia/anosmia (decrease or loss of sense of smell), along with general symptoms such as fatigue, shortness of breath, fever, and cough. The identity of the cell lineages that underpin infection associated with loss of olfaction could be critical for the diagnostics/clinical management of 2019-nCoV infected individuals. Angiotensin I Converting Enzyme 2 (ACE2), and Transmembrane protease serine 2 (TMPRSS2) are emerging as associated host receptors vital for viral entry. Accordingly, the ongoing medical examinations and the autopsy reports of the deceased individuals strongly corroborate with the organ/cell-type-specific expression of ACE2, TMPRSS2, and other putative viral entry-associated genes. To determine the cellular basis of anosmia upon 2019-nCoV infection, we employed a targeted bioinformatic analysis of single-cell expression profiles of human olfactory epithelium cell-types. Our results underscored selective expression of these viral entry-associated genes in a subset of sustentacular cells, Bowman’s gland cells, and stem cells of the olfactory epithelium. Co-expression analysis of ACE2 and TMPRSS2 and protein-protein interaction among the host and viral proteins elected regulatory cytoskeleton protein-enriched sustentacular cells as the most vulnerable cell-type of the olfactory epithelium. Furthermore, expression, structural and docking analyses of these viral-entry moieties revealed the potential risk of olfactory dysfunction in four additional mammalian species, revealing an evolutionarily conserved susceptibility. In summary, our findings suggest the molecular and cellular rationale of loss of smell in 2019-nCoV infected patients.

Language: R - Size: 27.6 MB - Last synced at: 4 months ago - Pushed at: over 1 year ago - Stars: 3 - Forks: 1

CMU-CREATE-Lab/smell-pittsburgh-prediction

Predicting and Interpreting Smell Data Obtained from Smell Pittsburgh

Language: Python - Size: 16.1 MB - Last synced at: about 1 year ago - Pushed at: about 2 years ago - Stars: 5 - Forks: 9

jdthamores/BioEssence

BioEssence is an olfactory wearable display that monitors cardio-respiratory information. This work is an evolution of the previous "Essence" prototype. The current display delivers up to three scents simultaneously and provides a self-contained solution for physiological sensing. Therefore, the current device allows not only to provide a wider range of stimuli but also to comfortably monitor the physiology of the wearer throughout the process. Developed by Judith Amores, Javier Hernandez, Artem Dementyev and Xiqing Wang.

Size: 21.5 KB - Last synced at: over 1 year ago - Pushed at: over 6 years ago - Stars: 1 - Forks: 1