SemDQ: A Semantic Framework for Data Quality Assessment

Objective: Access to, and reliance upon, high quality data is an enabling cornerstone of modern health delivery systems. Sadly, health systems are often awash with poor quality data which contributes both to adverse outcomes and can compromise the search for new knowledge. Traditional approaches to purging poor data from health information systems often require manual, laborious and time-consuming procedures at the collection, sanitizing and processing stages of the information life cycle with results that often remain sub-optimal. A promising solution may lie with semantic technologies - a family of computational standards and algorithms capable of expressing and deriving the meaning of data elements. Semantic approaches purport to offer the ability to represent clinical knowledge in ways that can support complex searching and reasoning tasks. It is argued that this ability offers exciting promise as a novel approach to assessing and improving data quality. This study examines the effectiveness of semantic web technologies as a mechanism by which high quality data can be collected and assessed in health settings. To make this assessment, key study objectives include determining the ability to construct of valid semantic data model that sufficiently expresses the complexity present in the data as well as the development of a comprehensive set of validation rules that can be applied semantically to test the effectiveness of the proposed semantic framework. Methods: The Semantic Framework for Data Quality Assessment (SemDQ) was designed. A core component of the framework is an ontology representing data elements and their relationships in a given domain. In this study, the ontology was developed using openEHR standards with extensions to capture data elements used in for patient care and research purposes in a large organ transplant program. Data quality dimensions were defined and corresponding criteria for assessing data quality were developed for each dimension. These criteria were then applied using semantic technology to an anonymized research dataset containing medical data on transplant patients. Results were validated by clinical researchers. Another test was performed on a simulated dataset with the same attributes as the research dataset to confirm the computational accuracy and effectiveness of the framework. Results: A prototype of SemDQ was successfully implemented, consisting of an ontological model integrating the openEHR reference model, a vocabulary of transplant variables and a set of data quality dimensions. Thirteen criteria in three data quality dimensions were transformed into computational constructs using semantic web standards. Reasoning and logic inconsistency checking were first performed on the simulated dataset, which contains carefully constructed test cases to ensure the correctness and completeness of logical computation. The same quality checking algorithms were applied to an established research database. Data quality defects were successfully identified in the dataset which was manually cleansed and validated periodically. Among the 103,505 data entries, application of two criteria did not return any error, while eleven of the criteria detected erroneous or missing data, with the error rates ranging from 0.05% to 79.9%. Multiple review sessions were held with clinical researchers to verify the results. The SemDQ framework was refined to reflect the intricate clinical knowledge. Data corrections were implemented in the source dataset as well as in the clinical system used in the transplant program resulting in improved quality of data for both clinical and research purposes. Implications: This study demonstrates the feasibility and benefits of using semantic technologies in data quality assessment processes. SemDQ is based on semantic web standards which allows easy reuse of rules and leverages generic reasoning engines for computation purposes. This mechanism avoids the shortcomings that come with proprietary rule engines which often make ruleset and knowledge developed for one dataset difficult to reuse in different datasets, even in a similar clinical domain. SemDQ can implement rules that have shown to have a greater capacity of detect complex cross-reference logic inconsistencies. In addition, the framework allows easy extension of knowledge base to cooperate more data types and validation criteria. It has the potential to be incorporated into current workflow in clinical care setting to reduce data errors during the process of data capture

HDRfeat: A Feature-Rich Network for High Dynamic Range Image Reconstruction

A major challenge for high dynamic range (HDR) image reconstruction from multi-exposed low dynamic range (LDR) images, especially with dynamic scenes, is the extraction and merging of relevant contextual features in order to suppress any ghosting and blurring artifacts from moving objects. To tackle this, in this work we propose a novel network for HDR reconstruction with deep and rich feature extraction layers, including residual attention blocks with sequential channel and spatial attention. For the compression of the rich-features to the HDR domain, a residual feature distillation block (RFDB) based architecture is adopted. In contrast to earlier deep-learning methods for HDR, the above contributions shift focus from merging/compression to feature extraction, the added value of which we demonstrate with ablation experiments. We present qualitative and quantitative comparisons on a public benchmark dataset, showing that our proposed method outperforms the state-of-the-art.Comment: 4 pages, 5 figure

Performance Diagnosis and Analysis of a Thermal Power Turbine Unit in a Power Plant

In order to further improve the operation level of the provincial grid direct thermal power units, optimize the data quality of the provincial thermal power unit system, diagnose and analyze the operation data of the thermal power unit system, and comprehensively analyze and evaluate the unit regulation ability from the aspects of heating capacity, the minimum startup mode of the whole plant, and the load capacity of the heating state, so as to provide support for the accurate scheduling of the unit

Stability and sensitivity characteristic analysis for the hydropower unit considering the sloping roof tailrace tunnel and coupling effect of the power grid

This paper focuses on the stability and dynamic characteristics of the coupled system of nonlinear hydraulic turbine regulating system (HTRS) and power grid (PG). By establishing a nonlinear mathematical model considering the downstream surge chamber and sloping roof tailrace tunnel, the coupling effect and influence mechanism between the hydropower station and power grid are revealed. First, with regard to the coupled system, HTRS considering downstream surge chamber and sloping roof tailrace tunnel and PG model is established. Then, dynamic performance of the coupled system is investigated based on the nonlinear mathematical model as well as Hopf bifurcation theory and validated by numerical simulation. Meanwhile, the impact mechanism of HTRS and PG is revealed by investigating dynamic characteristics. In addition, stability is studied by using eigenvalue method according to the Jacobian matrix of the coupled system. Finally, parameter sensitivity is investigated to quantify parameter effects on system performance. The experimental results indicate that bifurcation line divides the whole proportional–integral adjustment coefficient plane into two parts and the region at the bottom of bifurcation line is stability region. HTRS and PG possess a coupling effect on stable domain and dynamic properties of the coupled system. The variation of HTRS parameters is most significant for the coupled system, especially for the inertia time constant of the hydraulic turbine unit and penstock flow inertia time constant

Analysis of Heating Transformation of Nuclear Power Units

Under the current national conditions and policy support, nuclear heating has flourished. Domestic nuclear power units mainly generate electricity, and nuclear heating as a clean energy source is one of the main ways to solve winter heating in the north. This paper first compares and analyzes the two different ways of nuclear heating, then takes the nuclear heating of Haiyang Nuclear Power Station as an example, based on the mature experience of steam extraction heating transformation of thermal power units, makes an economic analysis on the steam extraction transformation of PWR nuclear power units from the characteristics of the thermal system combined with the Spot market, and finally makes an economic evaluation on the Cogeneration nuclear power units

Live video productions interaction with augmented reality : dance for all!

Augmented Reality (AR) is a powerful and emerging technology that is able to alter one’s experience in real-life with virtual elements and interfaces. By putting together technology and the arts, the experience will be both interactive and immersive. Dance For All! is an AR dance tutorial book that combines both AR and design to provide a platform for individuals to learn how to dance. It involves the teaching of simple hip-hop moves by displaying virtual tutorial videos over the pages of a dance book with the use of a mobile device’s camera feed. I will be conducting the dance tutorial videos myself and I will design a whole branding to the final product. By allowing users to create this experience themselves, it will be socially interactive and impactful. This platform aims to create an immersive experience for people to learn and eventually promote dance in the community.Bachelor of Engineering (Electrical and Electronic Engineering

Application Research on Zero Output of Double Low Pressure Cylinder of 600MW Unit

Under the dual carbon target, the rapid development of new energy promotes the increasing peak shaving capacity of thermal power units as basic power sources. Taking 600MW unit as an example, this paper studies the feasibility of zero output of low pressure cylinder for heat supply transformation of 600MW unit, and analyzes the peak shaving capacity of the unit by cutting off double low pressure cylinder and single low pressure cylinder

Power consumption characteristics of cement industry and parameter analysis of self provided power plant

Cement production is an industry that consumes a lot of electric energy. During the period of power shortage in China, the government encouraged multi-channel financing to run electricity to alleviate the power shortage problem of large industrial users. Therefore, many cement enterprises have established their own power plants. This paper analyses the basic electrical characteristics of the cement industry, classifies the loads of enterprises, and studies the regulation characteristics of various types of equipment

Optimal Dispatch of Multi-Type CHP Units Integrated with Flexibility Renovations for Renewable Energy Accommodation

Driven by the goals of carbon neutral and carbon peak, coal power units need increased flexibility in peak shaving to accommodate intermittent renewables, especially for a region with a large proportion of combined heat and power (CHP) units in China. In this study, the data-mining-based method is proposed for revealing and utilizing the heat–power coupling mechanism of CHP units, which can be used to solve the mentioned issues. Specifically, extraction-condensing (EC) units, high-back-pressure (HBP) units and low-pressure turbine zero power output (LZPO) units are introduced into the proposed dispatch model for maximizing renewable energy accommodation. The operation schemes and the feasible minimum output power of the CHP system under one certain heat load are obtained via the genetic algorithm. Results show that the CHP system is capable of reducing its output power by 18.7% to 41.7% in the heating season, compared with the actual operation data. Furthermore, the influence of multi-type units’ combination on peak-shaving flexibility is discussed. This study can be utilized for the optimal load dispatch scheme of multiple CHP units and guide the power dispatching department in making reasonable generation plans