From collection resources to intelligent data: Construction of intelligent digital humanities platform for local historical documents of Shanghai Jiao Tong University

Local historical documents originated from daily life of people belong to special collection resources that were not published publicly. They are valuable assets of universities and libraries. At present, most documents had only finished digitalization or partial datalization work. However, the requirements of deep knowledge mining in documents data, providing visual analysis, and effectively supporting the research of historic humanities scholars had not been fully met. Taking the local historical documents project of Shanghai Jiao Tong University as an example, using relevant techniques of digital humanities (DH), the in-depth analysis and utilization research of documents data were carried out. On the one hand, the core database of the documents was established based on standardizing metadata cataloguing and establishing metadata association. On the other hand, based on the core database, an intelligent DH system platform was constructed. The platform is to realize full-field retrieval and display of the documents, text analysis, association analysis, statistics, and visual presentation of knowledge. In addition, in the process of using the platform for research, humanities scholars can continuously expand the data dimensions and the relationships between data, achieve intelligent supplementation of documents data and platform self-learning. The concept of DH has led to a new direction of database construction and platform development. In the exploration and practice of DH, libraries should continue to widen thinking, improve service and innovation capabilities, and provide better research perspectives, research environments, research support, and research experience for humanities scholars.GECEM Project (ERC-Starting Grant), ref. 679371, Horizon 2020, project hosted at UPOCenter for Digital Sources of Chinese History, Library at Shanghai Jiao Tong Universit

Online Rapid Detection Method of Fertilizer Solution Information Based on Characteristic Frequency Response Features

Online rapid detection of a fertilizer solution’s type and concentration is crucial for intelligent water and fertilizer machines to realize intellectual precision variable fertilization. In this paper, a cylindrical capacitance sensor was designed based on the dielectric properties of the fertilizer solution, and an online rapid detection method of fertilizer type and concentration was proposed based on the characteristic frequency response mode. Three fertilizer solutions, potassium chloride, calcium superphosphate, and urea, were used as test objects. Ten concentrations of each fertilizer solution in the 10~100 g/L range were taken as the test fertilizer solution. Then, under the action of a series of sine wave excitation signals from 1 kHz to 10 MHz, the sensor’s amplitude-frequency/phase-frequency response data were obtained. The detection strategy of ‘first type, then concentration’ was adopted to realize rapid online detection of fertilizer type and concentration. Experimental results indicated that the maximum relative error of the sensor stability test was 0.72%, and the maximum error of concentration detection was 7.26%. Thus, the intelligent water and fertilizer machine can give feedback on the information of a fertilizer solution in real-time during the process of precise variable fertilization, thus improving the intelligence of water and fertilizer machines