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In the ship information big data system, aiming at the problems such as long time consuming, distortion of thermal map effect and poor tracking or lag in the roaming of map software when the client requests a large amount of historical data from the server and draws heat map in real time, this paper proposes an improved real-time generation strategy of map map of ship history activity. Based on the thermal map generation method with the idea of pixel clustering, this strategy uses the image enhancement algorithm based on nonlinear transformation and pixel complement method to correct and optimize the display distortion problems existing in the head map. On this basis, the dynamic loading and drawing strategy and multi-thread real-time mapping strategy are proposed to generate the heat map of the ship’s historical activities. Experiments show that the strategy proposed in this paper has been improved in the efficiency of heat map drawing, mapping effect and interactive experience of map software. [ABSTRACT FROM AUTHOR]

Clinical prediction models can predict individual outcomes or risks based on effect evidence obtained from the population, serving as a powerful tool linking evidence-based medicine and precision medicine. With the continuous advancement of data measurement, storage, interoperability, and analytical techniques, the application prospect for clinical prediction models is becoming increasingly clear. However, it also faces many problems and challenges. This paper aims to provide an overview of the fundamental concepts, application scenarios, current dilemmas, and development opportunities of clinical prediction models [ABSTRACT FROM AUTHOR]

At present, artificial intelligence continues to heat up. Large language models have attracted much attention and set off a wave of enthusiasm around the world. The success of artificial intelligence is not essentially a "miracle" of large computing power, but a change in computing models. Firstly, this paper affirms the fundamental role of data in AI, and points out that synthetic data will be the main source of data in the future. Then, this paper reviews the development of computing models, highlights the historic competition between neural network models and Turing models. We points out that the important hallmark of large language models is the emergence of intelligence in machines, emphasizes that the essence of large language models is "compression", and analyzes the reasons for the "illusion" of large language models. Finally, we call on the scientific community to attach importance to large scientific models in "AI for research(AI4R)". [ABSTRACT FROM AUTHOR]

[Purpose/Significance] In recent years, the national leadership has attached great importance to the inheritance and innovation of China's excellent traditional culture, and the concepts of creative transformation and innovative development are constantly evolving. The Ministry of Science and Technology of China, among six departments, jointly formulated the "Guidelines for Promoting the Deep Integration of Culture and Technology", proposing to form a "cultural and technological integration innovation system covering key areas and critical links, to achieve the goal of in-depth integration of culture and technology". Intangible cultural heritage (ICH), as an essential part of China's excellent traditional culture, plays a crucial role in consolidating the sense of the Chinese national community and enhancing cultural self-confidence. This paper discusses the research paths for the creative transformation and innovative development of ICH in the context of culture and technology integration, emphasizing the significant role of modern technology in promoting the transformation and development of ICH. [Method/Process] The paper first interprets the connotation of "creative transformation and innovative development" in ICH, and clarifies the theoretical foundation and guiding principles of "creative transformation and innovative development" in ICH. It then analyzes the significant contributions of "creative transformation and innovative development" in ICH to society, economy, and cultural diversity, as well as the categorized scenarios of technology empowerment in "creative transformation and innovative development" of ICH. It discusses six types of common key technologies that enable technology-driven "creative transformation and innovative development" in ICH, including digital technology, virtual and augmented reality, big data analysis, artificial intelligence, cloud computing, and the Internet of Things. It summarizes a three-tier framework system for technology-driven "creative transformation and innovative development" in ICH, namely the method layer, technology layer, and object layer, forming a progressive relationship from theory to technology and then to specific practices. Finally, by integrating the specific example of the traditional craft of Wuhu iron painting, it demonstrates the facilitating role of modern technology in the "creative transformation and innovative development" of ICH and its impact on the protection, inheritance, and innovative development of ICH. [Results/Conclusions] The findings suggest that technological means can effectively protect and inherit ICH, facilitating its creative transformation and innovative development. However, it also requires careful consideration and precautions against the potential risks and challenges that modern technology poses to ICH projects in terms of intellectual property rights, the digital divide, and the indirect nature of experiences. Looking to the future, with the emergence of more innovative technologies, modern technology will not only help to protect and pass on traditional culture but also give new connotations and expressions to traditional culture, ensuring that its unique value and charm continue to play out in an ever-changing world. [ABSTRACT FROM AUTHOR]

Aiming at the difficulties in the quantitative verification and evaluation of underwater countermeasures for our underwater platform and the lack of a guided maneuvering evasive combat model, a prediction model of underwater countermeasures based on big data learning is designed. Firstly, the underwater countermeasure modeling of the underwater platform is carried out, and the large data set of avoidance probability is obtained by several rounds of simulation based on Monte Carlo method. At the same time, in order to solve the problem of poor time efficiency under massive simulation, BP neural network prediction algorithm is proposed for big data learning to provide accurate, fast and visual antagonistic results. The test results show that under the test environment set in this paper, the average prediction error of BP neural network prediction algorithm is 7. 28% respectively, which can effectively predict the avoidance probability of the underwater platform and provide data support for the commander's command decision. [ABSTRACT FROM AUTHOR]

[Purpose/Significance] Talent data have become the most important production factor and strategic resource. Building a scientific and technological (S&T) talent database has become an inevitable way to narrow the digital divide and accelerate the digital and intelligent transformation of talent work. Therefore, this study builds an S&T talent database to promote scientific decision-making for talent development, precision in attracting new quality technical talent, reform in evaluating S&T talents, and building talent system for new quality productive forces. [Method/Process] By analyzing the practical requirements and significance of building an S&T talent database, this study first explores and analyzes the intrinsic logic of promoting the development of new quality productive forces through an S&T talent database. It then summarizes the challenges facing the current construction of a S&T talent database, including the scattering and concealment of S&T talent data, the lack of policies and standardized systems for S&T talent data, the inadequate exploration of value-added S&T talent data, the need to expand the application of digital technology in talent work, and the security risks of S&T talent data. In response to these challenges, this paper finally proposes the idea of building an S&T talents database, and introduces the research exploration and application practice on it, including the construction of big data database for S&T talent aimed at the development of new quality productive forces, the development of AI-powered talent data computing engine, research into the system for profiling new quality technical talent, the analysis of talent growth paths for the training of new quality technical talent, the identification method of new quality talented professionals based on big data, the development of an efficient digital platform for talent management, and the development of a strategic analysis platform for technical talent. [Results/Conclusions] The construction of S&T talent database is an objective requirement for the development of the digital era and an inevitable requirement for the formation of new quality productive forces. Building big data for S&T talent, empowering talent workflow with big data and artificial intelligence technology can help empower talent workflow, release the enormous energy contained in digitalization, effectively activate the internal momentum of talented professionals, institutions, society, and government, and then continuously improve the efficiency of talent resource allocation, the operational efficiency of talent work, the overall effectiveness of talent development governance, and promote the development of new quality productive forces. [ABSTRACT FROM AUTHOR]