Verification Of Feasibility Research Articles

An open-source platform for interactive collision prevention in photon and particle beam therapy treatment planning

We present an open-source platform to aid medical dosimetrists in preventing collisions between gantry head and patient or couch during photon or particle beam therapy treatment planning. This generic framework uses the native scripting interface of the particular planning software to import STL files of the treatment machine elements. These are visualized in 3D together with the contoured or scanned patient surface. A graphical dialog with sliders allows the interactive rotation of the gantry and couch, with real-time feedback. To prevent a future replanning, treatment planners can assess in advance and exclude beam angles resulting in a potential risk of collision. The software platform is publicly available on GitHub and has been validated for RayStation with actual patient plans. Furthermore, the incorporation of the complete patient geometry was tested with a 3D surface scan of a full-body phantom performed with a handheld smartphone. With this study, we aim at minimizing the risk of replanning due to collisions and thus of treatment delays and unscheduled consumption of manpower. The clinical workflow can be streamlined at no cost already at the treatment planning stage. By ensuring a real-time verification of the plan feasibility, the script might boost the use of optimal couch angles that a planner might shy away from otherwise.

Principal Component Analysis in Projection and Image Domains—Another Form of Spectral Imaging in Photon-Counting CT

We explore the feasibility of principal component analysis (PCA) as a form of spectral imaging in photon-counting CT. Using the data acquired by a prototype system and simulated by computer, we investigate the feasibility of spectral imaging in photon-counting CT via PCA for feature extraction and study the impacts made by data standardization and de-noising on its performance. The PCA in the projection domain maintains the data consistence that is essential for tomographic image reconstruction and performs virtually the same as that in the image domain. The first three primary components account for more than 99.99% covariance of the data. Within anticipation, the contrast-to-noise ratio (CNR) between the target and background in the first principal component image can be larger than that in the image generated from the data acquired in each energy bin. More importantly, the CNR in the first principal component image may be larger than that in the image formed by the summed data acquired in all energy bins (i.e., the conventional polychromatic CT image). In addition, de-noising can not only reduce the noise in images but also improve the effectiveness/efficiency of PCA in feature extraction. The PCA in either projection or image domain provides another form of spectral imaging in photon-counting CT that fits the essential requirements on spectral imaging in true color. The verification of PCA's feasibility in CT as a form spectral imaging and observation of its potential superiority in CNR over conventional polychromatic CT are meaningful in theory and practice.

Development and Psychometric Testing of a Tool Measuring Nurses’ Competence for Disaster Response

IntroductionThere is a growing awareness among governments, communities, and health care agencies of the need to evaluate roles and competencies in disaster nursing. A validated instrument was developed to evaluate nurses’ competencies for disaster response. MethodsA psychometric evaluation study was developed in 2 stages: 1) content and face validity, and 2) verification of feasibility and reliability with test-retest. Competencies were extracted from the Framework of Disaster Nursing Competencies published by the International Council of Nurses. The participants included 8 experts in emergencies and disasters who were nurses with a PhD and had more than 2 years of experience with education or clinical practice in emergencies or disasters, and 326 nurses from a mobile emergency care service in southern Brazil. The data analysis used a content validity index and intraclass correlation coefficients. The psychometric properties of the instrument included reliability assessed with Cronbach alpha, feasibility and test-retest reliability assessed with t tests and intraclass correlation coefficients, and factor analysis. ResultsThe overall evaluation of the instrument yielded an intraclass correlation coefficient of 0.92 (SD = 0.04), and the mean content validity index was acceptable at 0.88 (SD = 0.12). Out of 51 items, 41 were validated and organized in 3 domains according to factor analysis: 1) care of the community; 2) care of the individual and family; and 3) psychological support and care of vulnerable populations. The instrument demonstrated good internal consistency (Cronbach α = 0.96) and adequate test-retest reliability (intraclass correlation coefficient >0.7). DiscussionThe Nurses’ Disaster Response Competencies Assessment Questionnaire showed good internal consistency, adequate reproducibility, and appropriate feasibility for use to evaluate nurses’ competencies for disaster response.

Feasible working-state spaces of heat pipes: Integrated analyses of their isothermality and heat transfer limits

Heat pipes (HPs) are promising in advanced energy and power systems, featured by capability to transfer large heat flow over long distances with small temperature drops. However, the feasibility verification of such isothermality is usually ignored while only heat transfer limits (HTLs) are checked when HPs are to be designed and applied. In this work, criteria on feasible working-state spaces of HPs have been established, integrating the classical HTL and the pseudo-wick-thermal-conductivity-based isothermality theories. Calculations and comparisons have been done in wide ranges of working medium species, lengths, temperature and cooling condition. Isothermality is found to improve with increasing temperature and decreasing length as well as cooling coefficient, thus could always be achieved as long as temperature is sufficiently high. With regard to HTLs, differences exist between water HPs and alkali metal HPs. The isothermality and the HTL criteria compete to found the lower bounds of temperature but no upper bound exists for alkali metal HPs, while both upper bounds (determined by the HTL criterion) and lower bounds (determined by the isothermality criterion) exist for water HPs. The ranges of feasible working-state spaces of HPs with different working mediums are primarily determined by the HTL criterion. Once HPs are designed to operate not exceeding HTLs, isothermality can generally be guaranteed.

Effects of environmental feature selection on end‐to‐end vehicle steering controller

The method of deep learning has been widely used for end-to-end vehicle controllers' training because of its approximately non-linear functions. However, the convolutional neural network (CNN) training process requires a large amount of labelled data sets and takes a lot of time. Aiming at this problem, three experimental frameworks are designed to study the influence of single features on end-to-end controller in the simple and complex environments. The performance of controllers trained with different features is analysed, and the criteria of feature selection are given to reduce calculation cost. Firstly, two types of images with different environmental complexities are collected and pre-processed into three types of missing feature sets (data sets for sky, roadside, and road features are discarded, respectively). Then, based on the NVIDIA network model, the feasibility and road verification of the three frameworks designed are carried out. The experimental results show that: (i) Road features are indispensable to the training controller in simple or complex environments; (ii) roadside features help to improve the generalisation of the controller; (iii) sky features play a limited role in training vehicle steering controllers.

Synergistic decarbonization and desulfurization of blast furnace gas via a novel magnesium-molybdenum looping process

In this work, a novel system for synergistic decarbonization and desulfurization of blast furnace gas (BFG) was proposed via a magnesium-molybdenum looping process (MMLP): MgO ↔ MgCO3 and MoO3 ↔ MoS2. The system is comprised of a desulfurization/decarbonization reactor (DDR) and a carbon–sulfur carrier regeneration reactor (CRR). The simulation was conducted for feasibility verification and parameter optimization with applied ASPEN Plus software. Four carbon–sulfur carriers, MgO-MoO3, MgO-Fe2O3, MgO-MnO2, and MgO-SnO2, were preliminary investigated for screening. Results indicate that MgO-MoO3 performs superior capability of synergistic decarbonization and desulfurization. Both water–gas shift and COS/CS2 hydrolysis can be promoted in the presence of MgO via the CO2 absorption and the sorption-enhanced organic sulfur hydrolysis. The effects of MgO/C and 2MoO3/S mole ratios, temperature, pressure, O2 flow rate, and H2O flow rate were intensively discussed. Excessive temperature (>240 °C) in DDR leads to a decrease in carbon removal efficiency. A suitable amount of H2O is beneficial for CO2 capture, organic sulfur hydrolysis, and water gas shift reaction while excessive H2O decreases the organic sulfur hydrolysis efficiency and increases the system energy consumption. Carbon removal efficiency (CRE) of 99.70%, sulfur removal efficiency (SRE) of 100.00%, and H2 yield at 0.276 kmol/h (BFG flow rate = 1 kmol/h) can be obtained under the typical conditions of MgO/C = 2MoO3/S = 1.1, temperature = 240 °C, pressure = 1 atm and H2O/(CO + COS + CS2) = 1.2, providing theoretical guidance for the synergistic removal of sulfides and COx of BFG.

Efficient Provision of Service Function Chains in Overlay Networks Using Reinforcement Learning

Software-Defined Networking (SDN) and Network Functions Virtualization (NFV) technologies facilitate deploying Service Function Chains (SFCs) at clouds in efficiency and flexibility. However, it is still challenging to efficiently chain Virtualized Network Functions (VNFs) in overlay networks without knowledge of underlying network configurations. Although there are many deterministic approaches for VNF placement and chaining, they have high complexity and depend on state information of substrate networks. Fortunately, Reinforcement Learning (RL) brings opportunities to alleviate this challenge as it can learn to make suitable decisions without prior knowledge. Therefore, in this article, we propose an RL approach for efficient SFC provision in overlay networks, where the same VNFs provided by multiple vendors are with different performance. Specifically, we first formulate the problem into an Integer Linear Programming (ILP) model for benchmarking. Then, we present the online SFC path selection into a Markov Decision Process (MDP) and propose a corresponding policy-gradient-based solution. Finally, we evaluate our proposed approach with extensive simulations with randomly generated SFC requests and a real-world video streaming dataset, and implement an emulation system for feasibility verification. Related results demonstrate that performance of our approach is close to the ILP-based method and better than deep Q-learning, random, and load-least-greedy methods.

Verification of the technical feasibility of composting: case study

The aim of this work is to verify the technical feasibility of composting in the case of Marrakech prefecture. On the basis of waste composition and in accordance with the choice of the installation of Marrakech controlled landfill, composting has been considered as the most suitable waste treatment.To ensure the feasibility of composting, physicochemical analyses have been carried out on the fermentable part of waste; analyses on the content of metal elements have also been performed on the fine fraction, since the most important part is located in the same fraction. All parameters determined in the laboratory, have shown that optimal conditions to have good quality compost have been respected. The only restriction identified is the copper content, which should be less than 20 ppm. Generally the low levels of metal element content indicate that the storage and collection conditions of waste have not influenced their quality. On the other hand, the process must be properly controlled and managed, to produce high-quality compost.

Feasibility verification of direct spectrum division transmission over multiple satellite transponder

Feasibility verification of direct spectrum division transmission over multiple satellite transponder

Augmentation of Vortex Cavitator Performance by the Use of Co-Directional Swirl of the Flux after Vortex Chamber

Abstract Background: Acoustic cavitation is the creation and collapse of cavitation caverns in liquid in an acoustic field with a frequency of f = 1–3 kHz. The acoustic-cavitation processes manifest themselves during the collapse phase, with high pressure gradient continuum deformation, with a multiple transformation of energy forms. Liquid whistles are widely used to create an acoustic field of high power, but their efficiency only reaches 6–12%. We propose a liquid whistle in the form of a vortex cavitator (analogue of the Ranque vortex tube) with a rotating body in which a reduction in the input power is predicted. Objective: Verification of feasibility of using a rotating body in a vortex cavitator with a rotation co-directional to the operational pump impeller. Method: The method for identifying the feasibility of using a rotating body is to exclude body from the prototype and directly connect vortex chamber outlet with the pump inlet, which ensures the most complete preservation of co-directional vortex component of the flux entering the pump impeller. Results: The results of experimental studies confirmed the validity of the hypothesis to a greater extent, since we achieved an increase in pressure at the outlet of the pump and a decrease in power at the drive relative to the original design. Conclusions: The feasibility of designing the vortex cavitator body with rotation capability has been established, which will provide a reduction in input power of at least 30% by a rotation of the body, co-directional with the impeller.

A class of exact penalty functions and penalty algorithms for nonsmooth constrained optimization problems

In this paper, a class of smoothing penalty functions is proposed for optimization problems with equality, inequality and bound constraints. It is proved exact, under the condition of weakly generalized Mangasarian–Fromovitz constraint qualification, in the sense that each local optimizer of the penalty function corresponds to a local optimizer of the original problem. Furthermore, necessary and sufficient conditions are discussed for the inverse proposition of exact penalization. Based on the theoretical results in this paper, a class of smoothing penalty algorithms with feasibility verification is presented. Theories on the penalty exactness, feasibility verification and global convergence of the proposed algorithm are presented. Numerical results show that this algorithm is effective for nonsmooth nonconvex constrained optimization problems.

Feasibility verification for anomaly detection of track structures based on vibration data form vehicle body

Strengthening the detection and monitoring of abnormal track structure is of great significance to ensure the good operation of high-speed trains. The feasibility of detecting abnormal track structure of lower structure based on vehicle body vibration acceleration is verified numerically in this paper. A passenger car model is firstly established by rigid body dynamics software SIMPACK, and the vibration response of the car body is obtained by adding the abnormal irregularity waveform of typical track on the track spectrum as the wheel-rail excitation. And then, by comparing the acceleration vibration response of different positions and directions on the car body, the optimal measuring point of vibration sensor on the car body is determined. The results show that the vertical vibration acceleration of the front and rear position of the car can effectively reflect the abnormality of the lower track structure. Using the vibration data of the car body as the medium can provide a new way for the rapid abnormal detection of the lower track structure.

Fault Data Detection of Traffic Detector Based on Wavelet Packet in the Residual Subspace Associated with PCA

To improve the accuracy and efficiency of fault data identification of traffic detectors is crucial in order to decrease the probability of unexpected failures of the intelligent transportation system (ITS). Since convolutional fault data recognition based on traffic flow three-parameter law has a poor capability for multiscale of fault data, PCA (principal component analysis) is adopted for traffic fault data identification. This paper proposes the fault data detection models based on the PCA model, MSPCA (multiscale principal component analysis) model and improved MSPCA model, respectively. In order to improve the recognition rate of traffic detectors’ fault data, the improved MSPCA model combines the wavelet packet energy analysis and PCA to achieve traffic detector data fault identification. On the basis of traditional MSPCA, wavelet packet multi-scale decomposition is used to get detailed information, and principal component analysis models are established on different scale matrices, and fault data are separated by wavelet packet energy difference. Through case analysis, the feasibility verification of traffic flow data identification method is carried out. The results show that the improved method proposed in this paper is effective for identifying traffic fault data.

Experimental Investigations of Novel Compound Bearing of Superconducting Magnetic Field and Hydrodynamic Fluid Field

Long-life and high-reliability bearing is a key technology for developing the next generation of reusable liquid rocket turbopumps. We proposed a concept of superconducting compound bearing to combine the advantages of the superconducting magnetic field and the hydrodynamic fluid field. At the start-up, stop, and low-speed stages, the turbopump rotor system will be suspended by superconducting magnetic field to avoid mechanical friction and wear. The participation of hydrodynamic fluid field will ensure the stability during high-speed operational stage. An axial-type superconducting compound bearing with six tilting pads was erected, and an experimental verification of compound feasibility was conducted on an established testing device. The maximum rotational speed for experiments was 10 000 rpm, and the minimum bearing clearance was 100 μm. Due to the temperature rise on the superconducting pads during rotating, the superconducting magnetic force of the bearing decreases obviously versus the rotational speed. When the bearing clearance was decreased to 100 μm, this decay tendency was slowed down after 6000 rpm, even with an increase of 0.8 K in the cooling temperature of the liquid nitrogen container. It was attributed to the generation of hydrodynamic fluid-film force, and the value is 19.2 N at least. The monitored vibration results also reflected the different characteristics of the two physical fields. The verified superconducting compound bearing is a promising alternative for the rolling element bearings in the existing rocket turbopumps.

Bookings in the European gas market: characterisation of feasibility and computational complexity results

As a consequence of the liberalisation of the European gas market in the last decades, gas trading and transport have been decoupled. At the core of this decoupling are so-called bookings and nominations. Bookings are special long-term capacity right contracts that guarantee that a specified amount of gas can be supplied or withdrawn at certain entry or exit nodes of the network. These supplies and withdrawals are nominated at the day-ahead. The special property of bookings then is that they need to be feasible, i.e., every nomination that complies with the given bookings can be transported. While checking the feasibility of a nomination can typically be done by solving a mixed-integer nonlinear feasibility problem, the verification of feasibility of a set of bookings is much harder. The reason is the robust nature of feasibility of bookings-namely that for a set of bookings to be feasible, all compliant nominations, i.e., infinitely many, need to be checked for feasibility. In this paper, we consider the question of how to verify the feasibility of given bookings for a number of special cases. For our physics model we impose a steady-state potential-based flow model and disregard controllable network elements. For this case we derive a characterisation of feasible bookings, which is then used to show that the problem is in coNP for the general case but can be solved in polynomial time for linear potential-based flow models. Moreover, we present a dynamic programming approach for deciding the feasibility of a booking in tree-shaped networks even for nonlinear flow models. It turns out that the hardness of the problem mainly depends on the combination of the chosen physics model as well as the specific network structure under consideration. Thus, we give an overview over all settings for which the hardness of the problem is known and finally present a list of open problems.

Feasibility study of a new method to measure fast neutron flux by neutron-induced X-ray fluorescence method

A new method is proposed to detect fast neutron flux: the neutron-induced X-ray fluorescence method. In this method, the neutrons are firstly converted to charged particles, and then the charged particles interact with the target to generate the characteristic X-ray fluorescence. Finally, the Kα X-ray emission from the target is detected for measurement of the neutron flux. On the basis of this method, the structure of the detection device is designed: it is composed mainly of a layer of a fast neutron converter and a layer of the target. The Geant4 Monte Carlo simulation toolkit is used to optimize the detection device. According to the simulation results, the detection device is manufactured so as to perform the feasibility verification experiments. In the experiments, a D-T neutron generator is used as the neutron source, and the number of neutrons is changed in two ways: by change of the working voltage of the neutron generator or by change of the measurement time. The experimental results show that there is a good linear relationship between the number of neutrons and the Kα X-ray counts when the measurement time is changed. When the working voltage of the neutron generator is changed, a 3He proportional counter is used as a reference detector. The results show that the trend of the Kα X-ray counts is in good agreement with the trend for the 3He proportional counter. It is proved that this method is feasible for fast neutron flux measurement.

Removing the Feasibility Conditions Imposed on Tracking Control Designs for State-Constrained Strict-Feedback Systems

For strict-feedback nonlinear systems under full-state constraints, current barrier Lyapunov function (BLF) and integral BLF based control solutions rely on feasibility conditions for virtual controllers. In this work, we present a new solution that completely removes such restrictive conditions. First, we construct a nonlinear state-dependent function that purely depends on constrained states to cope with full state and asymmetric constraints directly; second, we introduce a new coordinate transformation and integrate it into each step of dynamic surface control based backstepping design, completely circumventing the demanding feasibility conditions on virtual controllers. Consequently, there is no need for the tedious offline computations for feasibility verification, allowing the designer more freedom to select design parameters, enabling the system with a larger range of initial conditions to be handled, and rendering the solution more user-friendly in design and implementation. Simulation verification also confirms the benefits and effectiveness of the proposed control method.

Design and Performance Evaluation of a Simple Semi-Physical Human-Vehicle Collaborative Driving Simulation System

Human-vehicle collaborative driving (HVCD) has a novel concept of an intermediate stage from the development of a normal smart vehicle to self-driving vehicle, requires the vehicle’s decision-making authority equivalent to the human driver’s operation. As the self-driving vehicle cannot achieve full-condition driving without human driver yet and still have a long time to go, the collaborative driving can exploit both machine and human specialties, which requires human and vehicle intelligence to control the vehicle simultaneously and work together. However, there were a few studies focusing on the HVCD that experimental environment and evaluation methods are rarely discussed, even under the simulation conditions, which limits the development of collaborative driving. To bridge the significant gaps, this paper designed simple semi-physical simulation system architecture for the HVCD. First, the simple designed system can achieve basic functions, including human control input as the normal driver, vehicle intelligence with local and global sensor data process and decision fusion. The presented system can use and process this multi-source information to achieve the HVCD in the simulated environment. Second, the evaluation method based on vehicle driving safety, stability, and rapidity is proposed and discussed, which matters most for system performance test and feasibility verification. In addition, experiments with different decision fusion conditions were presented and the experimental results show that the proposed simple semi-physical HVCD simulation system can work smoothly and reflect the practical scenario. Furthermore, the performance of different fusion weights experiments shows the advantages of both human driver and vehicle intelligence, which provides a reference for the HVCD related research improvement.

Robust bounded feasibility verification of piecewise affine systems via reachability computations

We address robust bounded feasibility verification for a discrete-time PieceWise Affine (PWA) system whose evolution can be influenced by some input. The aim is to determine an input sequence that makes the system satisfy a certain property within a finite time horizon, while maximizing the amount of perturbation that can be applied to the input without violating the given property. This is important to assess the robustness of the solution to numerical errors. We focus on the case of a property expressed in terms of the output of the system taking values in a certain spec set, and propose a verification method resting on reachability computations. The idea is to determine the set of states that the system can reach through all its possible evolutions, with the input taking values in its whole range, and check if the computed reach sets intersect with the one corresponding to the output spec set. If this is the case, then, an input sequence driving the output to the spec set exists and can be determined together with its robustness level by solving a linear optimization program.

Design, experiment and verification of a refined resonance method for property measurement of piezoelectric stack

A refined resonance method, which is based on the theoretical model of a piezoelectric stack under constraint boundary condition is developed and proposed to measure the properties of piezoelectric stack which are relevant to the prestress. The method can transcend the limitation of the conventional resonance method in which the piezoelectric stack under measurement must be free to vibrate. An experimental setup has been designed and built according to the theoretical model, and the properties of a piezoelectric stack are characterized for a wide range of prestress to demonstrate the validity of this method. The experimental results show that properties including relative dielectric constant, piezoelectric constant, electromechanical coupling coefficient and elastic compliance exhibit strong pressure dependence. Among them, the piezoelectric constant measured by this method is compared with measurement by traditional static method, and the deviation between the refined and conventional method is less than 3.25% for a pressure range from 0 to 6 MPa, which indicates that the experimental results of the two test methods are consistent and the presented theoretical model for piezoelectric stack under preload manifests accuracy by means of the correctness and feasibility verification of the proposed method though cross validation and relevant discussions. Consequently, the refined resonance method could be extended to analyze the variation of piezoelectric stack properties that occurs under operational conditions with varied pressure.