Research Article
An Optimised Hoffman Algorithm for Testing Linear Code Equivalency
Issue:
Volume 9, Issue 2, April 2024
Pages:
26-35
Received:
26 March 2024
Accepted:
10 April 2024
Published:
29 April 2024
Abstract: The Hoffman’s algorithm to test equivalency of linear codes is one of the techniques that have been used over the years; it is achieved by a comparison of codewords of the linear codes. However, this comparison technique becomes ineffective in instances where it is applied to linear codes with larger dimensions as it requires much run time complexity, space and size in comparing the codewords of each linear code. This paper proposes an optimised algorithm for testing the equivalency of linear codes, specifically addressing the limitations of the Hoffman method. To assess and compare the efficiencies of the Hoffman algorithm and the optimised algorithm, a set of nine carefully selected linear codes were subjected to equivalency testing. The CPU runtime of both algorithms was recorded using the C++ chrono library. The recorded runtime data was then utilized to create a scatter plot, offering a visual representation of the contrasting trends in CPU runtime between the two algorithms. The plot clearly indicate exponential growth in CPU runtime for the Hoffman algorithm as the length and dimension of the linear codes increases, in contrast, the proposed algorithm showcased a minimal growth in CPU runtime, indicating its superior efficiency and optimised performance.
Abstract: The Hoffman’s algorithm to test equivalency of linear codes is one of the techniques that have been used over the years; it is achieved by a comparison of codewords of the linear codes. However, this comparison technique becomes ineffective in instances where it is applied to linear codes with larger dimensions as it requires much run time complexi...
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Research Article
An Artificial Intelligence Interactive Platform for Automated Chatbot with AI-Driven Innovation in Recipe Searching
Deep Jigneshkumar Ka Patel Patel*
,
Shideh Yavary Mehr
Issue:
Volume 9, Issue 2, April 2024
Pages:
36-45
Received:
16 May 2024
Accepted:
3 June 2024
Published:
19 June 2024
DOI:
10.11648/j.mcs.20240902.12
Downloads:
Views:
Abstract: Hunger's Heaven is an innovative culinary app that uses artificial intelligence to customize and enhance the experience of cooking at home. The app's robust data handling and seamless functioning are ensured by its development with Node.js and MongoDB. It stands out for having AI-driven features that adjust to users' unique dietary restrictions and taste profiles, providing dynamic recipe recommendations and astute, dynamic search capabilities. Not only do these features address individual preferences and health, but they also make careful meal planning and nutritional monitoring easier. To enhance the user experience even more, the app incorporates social networking features that let users interact with a community of experienced chefs and rookie cooks, as well as share culinary accomplishments. Further interactive components like cooking challenges with AI enhancements and achievement badges inspire users and provide a lively learning environment. Hunger's Heaven is the ultimate example of fusing technology and culinary art, offering a dynamic platform that puts community, safety, and the appreciation of inventive cooking first.
Abstract: Hunger's Heaven is an innovative culinary app that uses artificial intelligence to customize and enhance the experience of cooking at home. The app's robust data handling and seamless functioning are ensured by its development with Node.js and MongoDB. It stands out for having AI-driven features that adjust to users' unique dietary restrictions and...
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