Journal of advances in information science and technology

ISSN: 2758-9293(Online)

Published by: Research Institute of Information Technology (Tokyo office), Hangzhou Domain Zones Technology Co., Ltd.
Koto-ku,Tokyo, Japan

Journal of advances in information science and technology


Volume 1, Issue 1, December 2023

1. Semantic Draw Engineering for Text-to-Image Creation
Yang Li, HuaQiang Jiang, YangKai Wu
Pages: 1 - 6

Text-to-image generation is conducted through Generative Adversarial Networks (GANs) or transformer models. However, the current challenge lies in accurately generating images based on textual descriptions, especially in scenarios where the content and theme of the target image are ambiguous. In this paper, we propose a method that utilizes artificial intelligence models for thematic creativity, followed by a classification modeling of the actual painting process. The method involves converting all visual elements into quantifiable data structures before creating images. We evaluate the effectiveness of this approach in terms of semantic accuracy, image reproducibility, and computational efficiency, in comparison with existing image generation algorithms.

2. Application of AI in Nutrition
Ritu Ramakrishnan, Tianxiang Xing, Tianfeng Chen, MingHao Lee, Jinzhu Gao
Pages: 7 - 12

In healthcare, artificial intelligence (AI) has been changing the way doctors and health experts take care of people. This paper will cover how AI is making major changes in the health care system, especially with nutrition. Various machine learning and deep learning algorithms have been developed to extract valuable information from healthcare data which help doctors, nutritionists, and health experts to make better decisions and make our lifestyle healthy. This paper provides an overview of the current state of AI applications in healthcare with a focus on the utilization of AI-driven recommender systems in nutrition. It will discuss the positive outcomes and challenges that arise when AI is used in this field. This paper addresses the challenges to develop AI recommender systems in healthcare, providing a well-rounded perspective on the complexities. Real-world examples and research findings are presented to underscore the tangible and significant impact AI recommender systems have in the field of healthcare, particularly in nutrition. The ongoing efforts of applying AI in nutrition lay the groundwork for a future where personalized recommendations play a pivotal role in guiding individuals toward healthier lifestyles.