Design a graphic concept for a vending machine and its surrounding area (5x6 meters) featuring INGU skincare products
เพื่อให้พัฒนาความเข้าใจ ความคิด การออกแบบ ให้สอดคล้องกับแบรนด์
คณะวิทยาศาสตร์
The species Enterococcus lactis is closely related to E. faecium and is known for its beneficial and probiotic effects. In this study, strain RRS4 was isolated from Raphanus sativus Linn. and identified based on both phenotypic and genotypic characteristics. Strain RRS4 exhibited cell viability in environments with 2-8% NaCl, pH ranging from 4 to 9, and temperatures between 4°C and 45°C. Through comprehensive genomic analysis, strain RRS4 was confirmed to be E. lactis. E. lactis RRS4 demonstrated inhibitory effects against Vancomycin-resistant E. faecalis JCM 5803. Safety assessments via in silico methods, including KEGG annotation, indicated the absence of virulent and undesirable genes in E. lactis RRS4. VirulenceFinder analysis aligned virulence-related genes with those from three strains of E. lactis and four strains of E. faecium. While antibiotic resistance genes were found to be conserved, they did not correlate with key pathogenicity traits. Furthermore, safety evaluations highlighted that E. lactis RRS4 is generally safe, despite the presence of genes associated with antibiotic resistance. Lastly, we propose guidelines for assessing the safety of microbial strains using whole-genome analysis. These findings represent advancements in probiotic research.
คณะสถาปัตยกรรม ศิลปะและการออกแบบ
A Photographic series that expresses the abstract states of myself, towards the question of existence that results from being surrounded by expectations of both surrender and freedom of expression, this series focuses on my own subjectivities in order to bring back memories of almost forgotten feelings and make them clear once more.
คณะวิทยาศาสตร์
Recruitment is a crucial process that enables organizations to select candidates whose qualifications match the requirements of a given position. However, this process often faces challenges related to data management, delays, and human bias. This research aims to design and develop an intelligent web application for employee recruitment using artificial intelligence (AI) technology to evaluate and score candidates' suitability for job positions. The system leverages data analysis techniques on resumes and a qualification-matching process based on predefined criteria. Developed using Agile principles, the system employs Natural Language Processing (NLP) to analyze resumes, assess candidates’ qualifications, skills, and experience, and utilizes Machine Learning to predict and rank suitability. The system consolidates data from multiple sources into a unified database to reduce redundancy and input errors. Additionally, it presents insights through a dashboard, enabling HR teams to make more effective hiring decisions.