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Background:Human brucellosis shows high morbidity, severe economic losses and public health problems globally. Because of traditional cultural method shortcomings, a novel tool for assisting clinical decision to identify high-risk infectious patients is urgently required. Methods: The data of total 2283 clinically confirmed brucellosis patients (including acute phase 816/chronic phase 989) and 13093 patients with characterized healthy outcomes was collected. Models with 3 different case groups, different sizes of variables, 7 different machine learning algorithms were tested and compared for model optimization. Metrological means combined with Shapley additive explanation (SHAP) was used for model explanation. Results: The gradient boosting machine with acute phrase patients as case group achieved the highest accuracy (AUC=0.997, 95%CI 0.994-0.999), specificity/sensitivity of 89.6%/99.8% and positive predictive value/negative predictive value of 99.4%/96.7%. Finally, 16 variables based on Pearson's correlation coefficient scores and recursive feature reduction using random forest algorithm was selected for this model. The measurement uncertainty (MU) of percent basophil, direct count eosinophil, percent eosinophil in complete blood count accounted for a large proportion in all variables. Thus, the influence of each input feature for the accuracy and the generalization of our model was quantitative and visualized by MU together with SHAP. Conclusions The proposed metrology-driven artificial intelligence-basedmodel, exclusive using regular laboratory results offers a promising tool to preliminarily identify high-risk brucellosis infection patients and risk stratify patients in different population, thereby promoting the health of the patients while protecting the health of the public and overcoming financial or supply constraints, especially in rural areas.

Objectives Patient-based real-time quality control (PBRTQC) has gained attention as an alternative/integrative tool for internal quality control (iQC). However, it is still doubted for its performance and its application in real clinical settings. We aim to generate a newly and easy-to-access patient-based real-time QC by machine learning (ML) traceable to standard reference data with assigned values by National Institute of Metrology of China (NIM), and to compare it with PBRTQC for clinical validity evaluation. Methods For five representative biochemistry analytes, 1,195 000 patient testing results each were collected. After data processing, independent training and test sets were divided. Machine learning internal quality control (MLiQC) was set up by Random Forest in ML and was validated by way of both metrology algorithm traceability and 4 PBRTQC methods recommended by IFCC analytical working group. Results MLiQC were established. As an example of albumin (ALB) at the critical bias, the uncertainty of MLiQC was 0.14%, which was evaluated by standard reference data produced by NIM. Compared with four optimal PBRTQC methods at critical bias, the average of the number of patient samples from a bias introduced until detected (ANPed) of MLiQC averagely decreased from 600 to 20. The median and 95 quantiles of NPeds (MNPed and 95NPed) of MLiQC were superior to all optimal PBRTQCs above 90% for all test items. Conclusions MLiQC is highly superior to PBRTQC and well-suited in real settings. The validation of the model from two aspects of algorithm traceability and clinical effectiveness confirms its satisfactory performance.

This paper discusses some problems the benchmark researches should pay attention to from the perspective of Metrology. Metrology is about the science of measurement, and it is considered as the foundation of industry development, for you have to measure it before you know what level it reaches. Metrology has a series of mechanisms to ensure the attributes of the measurement results, including Accuracy, Traceability, consistency and legality. Benchmark is widely used to evaluate the information technology products and helps the users to choose the products they need, and if absorbing the ideas of Metrology research during the designing, developing and application procedures of the benchmark, the quality of the measurement result of the benchmark will be improved greatly and become more authoritative.

The gate control system has some features such as multiple input parameters, nonlinearity, hysteresis, time change etc., therefore it can’t achieve good results by using traditional PID. In consideration of these characteristics, based on self-adaptive fuzzy PID control, we improved it and created a new time-independent, deterministic fuzzy PID. Then by auto-fusion of multiple input parameters, we have established a multi-input parameters fusion, time-independent and self-adaptive fuzzy PID controller and used it to control the reservoir gate and water level automatically under heavy rainfall. Simulations and experiments have shown that this method can offer faster response, smaller overshoot and better static and dynamic performance.

In order to promote the modernization of our urban, and to improve the management level of city and public affairs, an architecture of the digital urban management model based on WebGIS is put forward. Furthermore, the core open source technologies involving in the model are discussed in detail. Finally, a set of software named Rizhao Digital Urban MIS is designed and realized to show the feasibility and reliability of the digital urban management model. The system platform can provide a set of efficient and rich functionalities which can meet the demands of a small and medium-sized city perfectly.

In order to promote the construction of water conservancy modernization, an architecture of municipal water resources application system based on GIS, along with the calculation model and functional structure of surface water resources management subsystem and groundwater resources management subsystem, that are the core components within the application system, were discussed throughout this paper. The application system has been used in several small-medium size cities in Shandong Province, and has achieved good economic and social benefits.

An architecture of municipal water resources MIS (Management Information System) based on GIS is designed and implemented in this paper. The major innovation of our research is as follows: An algorithm for auto-generating of water isoline based on TIN was designed and developed, An algorithm for the same color weighted minimum distance was proposed, GML was used to represent and store the spatial information and map data. The MIS has been used in Shandong province and achieved good economic and social benefits.

GML schemas are metadata files, which define the structure, content and restriction of GML instances. GML parsing establishes a good basis for future GML data studies and applications such as storage, compression, query, index and share etc. The engine for GML grammar validation is an important component of GML parser, which includes validity verification and consistency verification. The objective of validity verification is to ensure GML data to be well-formed. In this paper, the functional structure of the GML schema-based parser is discussed, and an algorithm for GML data validity verification is developed and implemented. Experimental results show that the algorithm is effective and efficient.

A comprehensive and accurate user service request description is vital to the success of service discovery. This paper proposes a personalized description model for user's service request, which can update user's current needs based on current context. The service recommendation method based on this model is also introduced in detail, and the experiments illustrate the effectiveness of the model for the service discovery.

According to that there are large amount of data, complexity of data type and format in the water resources management, we built the water resources calculation model and established the water resources management information system based on the advanced ArcGIS and Visual Studio.NET development platform. The system can integrate the spatial data and attribute data organically, and manage them uniformly. It can analyze spatial data, inquire by map and data bidirectionally, provide various charts and report forms automatically, link multimedia information, manage database etc. . So it can provide spatial and static synthetical information services for study, management and decision of water resources, regional geology and eco-environment etc..

This paper proposes a kind of multi-agent based internetware system architecture, and introduces a diagnoser that can perform on-line diagnosis by observing the behaviors of it. This diagnoser brings semantic description to the procedure of states conversation of the system to be diagnosed by using dynamic description logic, which makes it possible to make use of more knowledge to analyze the failure further.

Based on the model of mixed-atmosphere, studies are conducted on the characteristics of electron temperature and the nonlinear attenuation of stong wave at different bands of frequency longitudinal propagation in the mixed-atmosphere. Simulations show that the nonlinear attenuation of stong wave at the frequency range of L,S and X band increases with the improvement of the field intensity of incident wave at the same incident frequency. When the attenuation reaches the maximum, a reverse trend will appear. But for the ultra-wide spectrum microwave the nonlinear attenuation decreases with the increase of the field intensity of incident wave and increases with the increase of the incident electronmagnetic waves. And the nonlinear attenuation is greater than the linear attenuation when the field intensity of incident wave at a lower order of magnitude. When the field intensity of incident wave reaches some value, nonlinear attenuation will be less than linear attenuation and the phenomenon wil be more obvious when the frequency of incident wave is lower.