Zobrazeno 1 - 10
of 2 737
pro vyhledávání: '"Pham Hung"'
Publikováno v:
Nuclear Technology and Radiation Protection, Vol 39, Iss 1, Pp 37-46 (2024)
This paper presents the thermoluminescence properties of K2GdF5:Tb material irradiated in a reference neutron-gamma field and its possibility to be used in neutron dosimetry. Double fluoride of K2GdF5 doped with 10 at% Tb3+ ions was synthesized un
Externí odkaz:
https://doaj.org/article/b9932e81b5054c4ca10b68815a1b7012
Effect of time-variant NDVI on landside susceptibility: A case study in Quang Ngai province, Vietnam
Publikováno v:
Open Geosciences, Vol 15, Iss 1, Pp 1913-23 (2023)
Normalized difference vegetation index (NDVI) is a conditioning factor that significantly affects slope stabilization, as the low vegetation coverage can create conducive conditions for landslide occurrence. In previous studies, NDVI was often calcul
Externí odkaz:
https://doaj.org/article/4326d226457a46d1b0ea99164b8cdb69
Autor:
Thi Ngoc Tran, Chien Thang Doan, Thi Kieu Loan Dinh, Thi Hai Ninh Duong, Thi Thuc Uyen Phan, Thi Thuy Loan Le, Trung Dung Tran, Pham Hung Quang Hoang, Anh Dzung Nguyen, San-Lang Wang
Publikováno v:
Recycling, Vol 9, Iss 3, p 50 (2024)
Xylanases, key enzymes for hydrolyzing xylan, have diverse industrial applications. The bioprocessing of agricultural byproducts to produce xylanase through fermentation approaches is gaining importance due to its significant potential to reduce enzy
Externí odkaz:
https://doaj.org/article/edc0efa7a9b0435da6d9b366d54e4988
Autor:
Tran Thi Thuy, Dinh Ngoc Duong, Nguyen Quynh Vi, Nguyen Duc Duong, Tran Duc Thinh, Nguyen Cong Bang, Pham Hung Vuong, Nguyen Ngoc Mai
Publikováno v:
Bulletin of Chemical Reaction Engineering & Catalysis, Vol 17, Iss 3, Pp 554-564 (2022)
A novel regenerated cellulose (RC) membrane containing cerium oxide (CeO2) nanoparticles is described in detail. In this work, CeO2 nanoparticles with high surface area and mesoporosity were prepared by a modified template-assisted precipitation meth
Externí odkaz:
https://doaj.org/article/aa1bd0b0ae8040b1bbcda52e77f76090
Autor:
Pham, Hung Viet, Nguyen, Tung Thanh
Traditional defect prediction approaches often use metrics that measure the complexity of the design or implementing code of a software system, such as the number of lines of code in a source file. In this paper, we explore a different approach based
Externí odkaz:
http://arxiv.org/abs/2409.18365
Large Language Models (LLMs) have demonstrated remarkable abilities across various tasks, leveraging advanced reasoning. Yet, they struggle with task-oriented prompts due to a lack of specific prior knowledge of the task answers. The current state-of
Externí odkaz:
http://arxiv.org/abs/2409.16418
Large Language Models (LLMs) have demonstrated impressive performance in software engineering tasks. However, improving their accuracy in generating correct and reliable code remains challenging. Numerous prompt engineering techniques (PETs) have bee
Externí odkaz:
http://arxiv.org/abs/2409.16416
Autor:
Nguyen Duc Thanh, Bui Thi My Anh, Chu Huyen Xiem, Pham Quynh Anh, Pham Hung Tien, Nguyen Thi Phuong Thanh, Cao Huu Quang, Vu Thu Ha, Phung Thanh Hung
Publikováno v:
International Journal of Public Health, Vol 67 (2022)
Introduction: Patient satisfaction is one of the most important components of measuring healthcare quality.Objectives: The study aimed to evaluate the validity and reliability of the patient satisfaction scale with the quality of health services and
Externí odkaz:
https://doaj.org/article/77391d1f466342c4a37f2e723dcf5e13
Large Language Models (LLMs) have seen increasing use in various software development tasks, especially in code generation. The most advanced recent methods attempt to incorporate feedback from code execution into prompts to help guide LLMs in genera
Externí odkaz:
http://arxiv.org/abs/2408.11198
The accuracy of phaseless auxiliary-field quantum Monte Carlo (ph-AFQMC) can be systematically improved with better trial states. Using multi-Slater determinant trial states, ph-AFQMC has the potential to faithfully treat strongly correlated systems,
Externí odkaz:
http://arxiv.org/abs/2406.08314