Efficient data management in healthcare is essential for providing timely and accurate patient care, yet traditional partitioning methods in relational databases often struggle with the high volume, heterogeneity, and...Efficient data management in healthcare is essential for providing timely and accurate patient care, yet traditional partitioning methods in relational databases often struggle with the high volume, heterogeneity, and regulatory complexity of healthcare data. This research introduces a tailored partitioning strategy leveraging the MD5 hashing algorithm to enhance data insertion, query performance, and load balancing in healthcare systems. By applying a consistent hash function to patient IDs, our approach achieves uniform distribution of records across partitions, optimizing retrieval paths and reducing access latency while ensuring data integrity and compliance. We evaluated the method through experiments focusing on partitioning efficiency, scalability, and fault tolerance. The partitioning efficiency analysis compared our MD5-based approach with standard round-robin methods, measuring insertion times, query latency, and data distribution balance. Scalability tests assessed system performance across increasing dataset sizes and varying partition counts, while fault tolerance experiments examined data integrity and retrieval performance under simulated partition failures. The experimental results demonstrate that the MD5-based partitioning strategy significantly reduces query retrieval times by optimizing data access patterns, achieving up to X% better performance compared to round-robin methods. It also scales effectively with larger datasets, maintaining low latency and ensuring robust resilience under failure scenarios. This novel approach offers a scalable, efficient, and fault-tolerant solution for healthcare systems, facilitating faster clinical decision-making and improved patient care in complex data environments.展开更多
Accurate and reliable nuclear decay databases are essential for fundamental and applied nuclear research studies.However,decay data are not usually as accurate as expected and need improvement.Hence,a new Chinese nucl...Accurate and reliable nuclear decay databases are essential for fundamental and applied nuclear research studies.However,decay data are not usually as accurate as expected and need improvement.Hence,a new Chinese nuclear decay database in the fission product mass region(A=66−172)based on several major national evaluated data libraries has been developed under joint efforts in the CNDC working group.A total of 2358 nuclides have been included in this decay database.Two main data formats,namely ENSDF and ENDF,have been adopted.For the total meanβandγenergies,available data from total absorption gamma ray spectroscopy measurements have been adopted.For some nuclides without experimental measurements,theoretically calculated values have been added.展开更多
文摘Efficient data management in healthcare is essential for providing timely and accurate patient care, yet traditional partitioning methods in relational databases often struggle with the high volume, heterogeneity, and regulatory complexity of healthcare data. This research introduces a tailored partitioning strategy leveraging the MD5 hashing algorithm to enhance data insertion, query performance, and load balancing in healthcare systems. By applying a consistent hash function to patient IDs, our approach achieves uniform distribution of records across partitions, optimizing retrieval paths and reducing access latency while ensuring data integrity and compliance. We evaluated the method through experiments focusing on partitioning efficiency, scalability, and fault tolerance. The partitioning efficiency analysis compared our MD5-based approach with standard round-robin methods, measuring insertion times, query latency, and data distribution balance. Scalability tests assessed system performance across increasing dataset sizes and varying partition counts, while fault tolerance experiments examined data integrity and retrieval performance under simulated partition failures. The experimental results demonstrate that the MD5-based partitioning strategy significantly reduces query retrieval times by optimizing data access patterns, achieving up to X% better performance compared to round-robin methods. It also scales effectively with larger datasets, maintaining low latency and ensuring robust resilience under failure scenarios. This novel approach offers a scalable, efficient, and fault-tolerant solution for healthcare systems, facilitating faster clinical decision-making and improved patient care in complex data environments.
基金Supported by the National Key R&D Program of China(2022YFA1602000)。
文摘Accurate and reliable nuclear decay databases are essential for fundamental and applied nuclear research studies.However,decay data are not usually as accurate as expected and need improvement.Hence,a new Chinese nuclear decay database in the fission product mass region(A=66−172)based on several major national evaluated data libraries has been developed under joint efforts in the CNDC working group.A total of 2358 nuclides have been included in this decay database.Two main data formats,namely ENSDF and ENDF,have been adopted.For the total meanβandγenergies,available data from total absorption gamma ray spectroscopy measurements have been adopted.For some nuclides without experimental measurements,theoretically calculated values have been added.
