Single Energy Model Research Articles

Robustness of Single- and Dual-Energy Deep-Learning-Based Scatter Correction Models on Simulated and Real Chest X-rays

Chest X-rays (CXRs) represent the first tool globally employed to detect cardiopulmonary pathologies. These acquisitions are highly affected by scattered photons due to the large field of view required. Scatter in CXRs introduces background in the images, which reduces their contrast. We developed three deep-learning-based models to estimate and correct scatter contribution to CXRs. We used a Monte Carlo (MC) ray-tracing model to simulate CXRs from human models obtained from CT scans using different configurations (depending on the availability of dual-energy acquisitions). The simulated CXRs contained the separated contribution of direct and scattered X-rays in the detector. These simulated datasets were then used as the reference for the supervised training of several NNs. Three NN models (single and dual energy) were trained with the MultiResUNet architecture. The performance of the NN models was evaluated on CXRs obtained, with an MC code, from chest CT scans of patients affected by COVID-19. The results show that the NN models were able to estimate and correct the scatter contribution to CXRs with an error of <5%, being robust to variations in the simulation setup and improving contrast in soft tissue. The single-energy model was tested on real CXRs, providing robust estimations of the scatter-corrected CXRs.

Study on the Calculation Method of Green GDP to Measure the Economic Health

This paper discusses the replacement of conventional GDP with green GDP (GGDP) as the main measure of economic health. Based on data on annual average temperature, annual precipitation, annual sunshine hours and annual average relative humidity for country C over the past decade, a multiple regression model is used to demonstrate that the linear effect of GGDP is positive for green growth. Further considering the differences in economic power between developed, developing and lagging countries, an infinite iterative game model of green GDP and conventional GDP is constructed based on the mutual constraints of long-term and short-term interests. Finally, considering the resistance to replacing GDP with green GDP, and in order to fully reflect the tortuous and complex relationship between climate change and social costs, an integrated model that will be embedded in the economic system, the DICE-2013R model, is constructed in order to achieve a shift from a single energy model to an integrated climate model. Normalising the data based on the model calcglobal scale.

Optimal Scheduling Strategy of Cascade Hydropower Plants Under the Joint Market of Day-Ahead Energy and Frequency Regulation

In order to adapt to new situation of cascade hydropower enterprises (CHEs) participating in the joint market of day-ahead energy and frequency regulation (FR), a short-term optimal scheduling strategy for cascade hydropower plants (CPPs) is proposed. Firstly, the development situation of AGC in China is introduced and the CPPs’ AGC mode of participation in FR from the perspective of economy and solvability is analyzed. Secondly, for maximizing the revenue, the economic dispatching model of CPPs based on the two-part FR compensation mechanism is proposed, which combines the benefits of both the energy and FR. Finally, a two-stage optimization method that couples the load distribution among multi plants with the economic operation of a single plant is proposed for solving the model above. The experimental results show that the two-stage optimization method has good convergence and robustness in solving the proposed model, and compared with the single energy model, the total benefits of the proposed model increases by $ \$ $ 72935.6 (5.54%) through optimizing the distribution of electricity quantity and AGC capacity, which provides a new idea for cascade hydropower enterprises (CHEs) to explore market dividend and optimize market decision-making.

Transient simulation of gas-condensate two-phase flow in pipes

An algorithm for transient gas-condensate two-phase flow in pipes is developed in this paper. It adopts a two-fluid model for hydraulic simulation and a single energy model for thermal simulation. For ease of calculation, a temperature-based energy equation is derived from the law of conservation of energy. In order to consider the influence of the phase transition, a new mass transfer model is developed in terms of total mass flow rate. Based on these models, a SIMPLE(Semi-Implicit Methods for Pressure-Linked Equations)-like algorithm is proposed to simulate the transient gas-condensate two-phase flow. It consists of four steps: pressure and velocity correction, volume fraction solution, temperature calculation and property parameters update. Case study shows that the proposed algorithm could well simulate gas-condensate stratified flow with low liquid mass fraction and high liquid mass fraction. In addition, the algorithm could provide a more consistent result for transient gas-condensate two-phase flow.

Inertial sensor aided multi-image nonuniform motion blur removal based on motion decomposition

Many factors lead to spatially varying blur kernels in a blurred image, such as camera shake, moving objects, and scene depth variation. The traditional camera shake removal methods either ignore the influence of varying depth values or object motion in dynamic scenes, while the methods not limited to removing camera shake always make simple assumptions about camera motion trajectory. We consider these factors in a unified framework, with the aid of an alternate-exposure capture strategy and simultaneously recorded inertial sensor readings. The inertial measurements relate the long-exposed blurred image to preceding and succeeding short-exposed noisy images. The special exposure arrangement effectively addresses the problem inherent in reconstructing camera motion from inertial measurements. In addition, the noisy image pair bracketing the blurred image is used for motion detection and initial depth map estimation, making the proposed method free of user interaction and additional expensive devices. Contrary to previous methods that individually parametrize the motion blur of the moving foreground layer and the static background layer, we exploit the fact that camera shake has a global influence to decompose the motion of the foreground layer such that a more tight constraint between the motion of layers is established. Given the motion and image data, we propose a single-energy model and minimize it using alternating optimization to estimate the spatially varying motion blur and the latent sharp image. Comparative experimental results demonstrate that our method outperforms conventional camera motion deblurring and object deblurring methods on both synthetic and real scenes.

Dynamic Video Deblurring Using a Locally Adaptive Blur Model.

State-of-the-art video deblurring methods cannot handle blurry videos recorded in dynamic scenes since they are built under a strong assumption that the captured scenes are static. Contrary to the existing methods, we propose a new video deblurring algorithm that can deal with general blurs inherent in dynamic scenes. To handle general and locally varying blurs caused by various sources, such as moving objects, camera shake, depth variation, and defocus, we estimate pixel-wise varying non-uniform blur kernels. We infer bidirectional optical flows to handle motion blurs, and also estimate Gaussian blur maps to remove optical blur from defocus. Therefore, we propose a single energy model that jointly estimates optical flows, defocus blur maps and latent frames. We also provide a framework and efficient solvers to minimize the proposed energy model. By optimizing the energy model, we achieve significant improvements in removing general blurs, estimating optical flows, and extending depth-of-field in blurry frames. Moreover, in this work, to evaluate the performance of non-uniform deblurring methods objectively, we have constructed a new realistic dataset with ground truths. In addition, extensive experimental results on publicly available challenging videos demonstrate that the proposed method produces qualitatively superior performance than the state-of-the-art methods which often fail in either deblurring or optical flow estimation.

Modelling EU‐GCC energy systems and trade corridors

PurposeThis article is based on the REACCESS research project, sponsored by the European Commission, with the objectives of evaluating the technical, economic, and environmental aspects of present and future energy corridors between the European countries (EU27) and their main energy suppliers. GCC countries have an important role to play given their role in EU energy supply and in greenhouse gas emissions. The paper aims to discuss these issues.Design/methodology/approachA single energy model was built by hard‐linking the TIMES integrated assessment model (TIAM‐World), the Pan European TIMES model (PET), and the RECOR model (REaccess CORridors), including more than 1,000 possible energy corridors supplying the European countries. Another major methodology advance was to create a hybrid objective function, combining the usual cost objective and a metric representing the supply risk incurred by EU27. The risk component was constructed via a novel approach that aggregates the elemental risk parameters of each corridor using a Min‐Max function. Four contrasted scenarios were assessed, based on security and climate objectives.FindingsAmong the many results, it appears that a large reduction of the supply risk may be achieved at a very modest increase of the total energy system cost for EU27. Cross‐effects of climate mitigation and security objectives are also observed. Due to the diversification requirement, the contribution of GCC countries to EU energy imports increases under risk scenario. Sensitivity analyses show that the European energy system seems unable to reduce the market shares of fossil fuels import from MENA countries, including GCC countries, much below the reference case, proving the strong dependency of EU27 energy system from these countries. However, total fossil fuels imports, as well as total energy consumed, are decreased under the risk adverse scenarios.Originality/valueMethodological developments, as described above, result in an advanced tool to assess how to increase the “energy system security”, by reducing the concentration of supply countries, diversifying import sources but also reducing the energy dependence at the end‐use side.

Ice core stratigraphy using dual energy x-ray absorptiometry (DEXA)

We are presenting a technique using x-rays to detect strata caused by density variation in 94 mm diameter ice cores. Moreover, high resolution density is determined. A 54 m long ice core retrieved from the Tasman Glacier of the Southern Alps in New Zealand has been x-ray scanned and the images were analysed. As a dual energy capable x-ray (DEXA) scanner was used, DEXA analysis techniques were used where appropriate, such as for the enhancement of strata visibility in the images. Density calculations though were based on a single energy model, using the fundamental law of x-ray attenuation. As the model does not precisely reflect realistic conditions, calibrations were made for the material properties and pixel scaling. Results of detected strata were compared to traditional visual light methods, where up to a depth of ∼35 m better detail was achieved using x-rays. Density data was checked against the average volumetric density. Results compare well with the volumetric density, however a small bias exists, which at present requires further investigation.

Field-assisted thermally stimulated current of mobile ions in a dielectric layer of a metal–oxide–semiconductor structure

A field-assisted thermally stimulated ionic current method has been used to investigate the transient currents associated with mobile ions in dielectric layers of metal-oxide-semiconductor (MOS) structures. Assuming Poole–Frenkel effect, an interface trapping model has been used to analyze J–V curves. Using a ramp voltage, analytic expressions for normalized J–V curves are obtained. The single energy model and distributed energy model have been analyzed. The most probable trapping depth of mobile ions, attempt-to-escape frequency and trapping energy distribution of mobile ions may be determined from J–V curves. The experimental results are consistent with theoretical calculations.