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  Subjects -> SCIENCES: COMPREHENSIVE WORKS (Total: 374 journals)
Showing 201 - 265 of 265 Journals sorted by number of followers
Revista Científica de la Universidad Nacional del Este     Open Access   (Followers: 9)
Patterns     Open Access   (Followers: 5)
History of Science and Technology     Open Access   (Followers: 5)
Journal of the Indian Institute of Science     Hybrid Journal   (Followers: 4)
Research Policy : X     Open Access   (Followers: 4)
Data     Open Access   (Followers: 4)
Advanced Theory and Simulations     Hybrid Journal   (Followers: 4)
Frontiers in Climate     Open Access   (Followers: 4)
Research     Open Access   (Followers: 4)
MUST : Journal of Mathematics Education, Science and Technology     Open Access   (Followers: 4)
People and Nature     Open Access   (Followers: 4)
Journal of Composites Science     Open Access   (Followers: 3)
Orbis Cógnita : Revista Científica     Open Access   (Followers: 3)
Science & Technology Studies     Open Access   (Followers: 3)
Journal of Big History     Open Access   (Followers: 3)
Discover Sustainability     Open Access   (Followers: 3)
Citizen Science : Theory and Practice     Open Access   (Followers: 2)
International Journal of Culture and Modernity     Open Access   (Followers: 2)
Indonesian Journal of Science and Mathematics Education     Open Access   (Followers: 2)
Journal of Science and Technology     Open Access   (Followers: 1)
International Journal of Research in Science     Open Access   (Followers: 1)
Scientonomy : Journal for the Science of Science     Open Access   (Followers: 1)
Global Journal of Science Frontier Research     Open Access   (Followers: 1)
Uluslararası Bilimsel Araştırmalar Dergisi (IBAD)     Open Access   (Followers: 1)
Journal of Science and Engineering     Open Access   (Followers: 1)
Bilge International Journal of Science and Technology Research     Open Access   (Followers: 1)
Applied Mathematics and Nonlinear Sciences     Open Access   (Followers: 1)
AAS Open Research     Open Access   (Followers: 1)
Acta Scientifica Malaysia     Open Access   (Followers: 1)
ARPHA Conference Abstracts     Open Access   (Followers: 1)
Impact     Open Access   (Followers: 1)
International Journal of Innovative Research and Scientific Studies     Open Access   (Followers: 1)
Revista Saber Digital     Open Access   (Followers: 1)
Futures & Foresight Science     Hybrid Journal   (Followers: 1)
Experimental Results     Open Access   (Followers: 1)
Revista Vivências em Ensino de Ciências     Open Access   (Followers: 1)
Jaunujų mokslininkų darbai     Open Access   (Followers: 1)
iScience     Open Access   (Followers: 1)
Fundamental Research     Open Access  
BJHS Themes     Open Access  
South American Sciences     Open Access  
Middle European Scientific Bulletin     Open Access  
Journal of Alasmarya University     Open Access  
Research Integrity and Peer Review     Open Access  
Natural Sciences Education     Hybrid Journal  
Proceedings of the Indian National Science Academy     Full-text available via subscription  
Indian Journal of History of Science     Hybrid Journal  
RAC: Revista Angolana de Ciências     Open Access  
The Innovation     Open Access  
Journal of Responsible Technology     Open Access  
Natural Sciences     Open Access  
Revista de la Sociedad Científica del Paraguay     Open Access  
Rekayasa     Open Access  
Rihan Journal for Scientific Publishing     Open Access  
Türk Bilim ve Mühendislik Dergisi     Open Access  
ArtefaCToS : Revista de estudios sobre la ciencia y la tecnología     Open Access  
Ethiopian Journal of Sciences and Sustainable Development     Open Access  
Vilnius University Proceedings     Open Access  
Sciential     Open Access  
ARPHA Proceedings     Open Access  
Gaudium Sciendi     Open Access  
Crea Ciencia Revista Científica     Open Access  
Rafidain Journal of Science     Open Access  
Journal of Al-Qadisiyah for Pure Science     Open Access  
Revista Tecnológica     Open Access  
Himalayan Journal of Science and Technology     Open Access  
International Journal of Academic Research in Business, Arts & Science     Open Access  
Universidad, Ciencia y Tecnología     Open Access  
Fides et Ratio : Revista de Difusión Cultural y Científica     Open Access  
Acta Nova     Open Access  
Revista de la Academia Colombiana de Ciencias Exactas, Físicas y Naturales     Open Access  
Entre Ciencia e Ingeniería     Open Access  
Revista Politécnica     Open Access  
Reportes Científicos de la FaCEN     Open Access  
Jurnal Ilmiah Ilmu Terapan Universitas Jambi : JIITUJ     Open Access  
Revista Eletrônica Ludus Scientiae     Open Access  
Emergent Scientist     Open Access  
Journal of Scientific Research and Reports     Open Access  
Asian Journal of Advanced Research and Reports     Open Access  
Archives of Current Research International     Open Access  
Advances in Research     Open Access  
International Journal of Applied Science     Open Access  
Iranian Journal of Science and Technology, Transactions A : Science     Hybrid Journal  
J : Multidisciplinary Scientific Journal     Open Access  
Revista Binacional Brasil - Argentina: Diálogo entre as ciências     Open Access  
Revista Ciencia y Tecnología     Open Access  
Journal of Institute of Science and Technology     Open Access  
Journal of Science (JSc)     Open Access  
WikiJournal of Science     Open Access  
Acta Materialia Transilvanica     Open Access  
Integrated Research Advances     Open Access  
PENDIPA : Journal of Science Education     Open Access  
Open Conference Proceedings Journal     Open Access  
Naturen     Full-text available via subscription  
Ekaia : EHUko Zientzia eta Teknologia aldizkaria     Open Access  
Sci     Open Access  
Maskana     Open Access  
Hoosier Science Teacher     Open Access  
Reports in Advances of Physical Sciences     Open Access  
Facets     Open Access  
Adıyaman University Journal of Science     Open Access  
Revista Brasileira de Iniciação Científica     Open Access  
Communications Faculty of Sciences University of Ankara Series A2-A3 Physical Sciences and Engineering     Open Access  
Scientific African     Open Access  
Scientific Journal of Mehmet Akif Ersoy University     Open Access  
Black Sea Journal of Engineering and Science     Open Access  
Fırat University Turkish Journal of Science & Technology     Open Access  
Gazi University Journal of Science     Open Access  
Middle East Journal of Science     Open Access  
International Journal of Computational and Experimental Science and Engineering (IJCESEN)     Open Access  
International Journal of Engineering, Technology and Natural Sciences     Open Access  
Bulletin of the National Research Centre     Open Access  
Uni-pluriversidad     Open Access  
ConCiencia     Open Access  
Ciencia y Tecnología     Open Access  
Revista Bases de la Ciencia     Open Access  
Elkawnie : Journal of Islamic Science and Technology     Open Access  
Ciência ET Praxis     Open Access  
Arab Journal of Basic and Applied Sciences     Open Access  
International Annals of Science     Open Access  
Science Heritage Journal     Open Access  
Avrasya Terim Dergisi     Open Access  
International Scientific and Vocational Studies Journal     Open Access  
TÜBAV Bilim Dergisi     Open Access  
LOGIKA Jurnal Ilmiah Lemlit Unswagati Cirebon     Open Access  
Dalat University Journal of Science     Open Access  
Investiga : TEC     Open Access  
Investigación Joven     Open Access  
Respuestas     Open Access  
Science Diliman     Open Access  
Instruments     Open Access  
Revista Científica y Tecnológica UPSE     Open Access  
HardwareX     Open Access  
Sultan Qaboos University Journal for Science     Open Access  
Borneo Journal of Resource Science and Technology     Open Access  
Sainstek : Jurnal Sains dan Teknologi     Open Access  
Revista de Información Científica     Open Access  
Indonesian Journal of Fundamental Sciences     Open Access  
Sainteknol : Jurnal Sains dan Teknologi     Open Access  
Jurnal Natural     Open Access  
Frontiers for Young Minds     Open Access  
Revista Ciência, Tecnologia & Ambiente     Open Access  
Journal of Indian Council of Philosophical Research     Hybrid Journal  
Journal of Negative and No Positive Results     Open Access  
Revista Conhecimento Online     Open Access  
Nova     Open Access  
CienciaUAT     Open Access  
Enseñanza de las Ciencias : Revista de Investigación y Experiencias Didácticas     Open Access  
Makara Journal of Science     Open Access  
Jurnal Sains Dasar     Open Access  
Indonesian Journal of Science and Technology     Open Access  
Ethiopian Journal of Science and Technology     Open Access  
Jurnal Matematika, Sains, Dan Teknologi     Open Access  
Heidelberger Jahrbücher Online     Open Access  
ARO. The Scientific Journal of Koya University     Open Access  
International Journal of Recent Contributions from Engineering, Science & IT     Open Access  
Estação Científica (UNIFAP)     Open Access  
The Winnower     Open Access  

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Journal of Shanghai Jiaotong University (Science)
Journal Prestige (SJR): 0.143
Number of Followers: 0  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 1995-8188 - ISSN (Online) 1007-1172
Published by Springer-Verlag Homepage  [2467 journals]
  • Air Combat Assignment Problem Based on Bayesian Optimization Algorithm

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      Abstract: In order to adapt to the changing battlefield situation and improve the combat effectiveness of air combat, the problem of air battle allocation based on Bayesian optimization algorithm (BOA) is studied. First, we discuss the number of fighters on both sides, and apply cluster analysis to divide our fighter into the same number of groups as the enemy. On this basis, we sort each of our fighters’ different advantages to the enemy fighters, and obtain a series of target allocation schemes for enemy attacks by first in first serviced criteria. Finally, the maximum advantage function is used as the target, and the BOA is used to optimize the model. The simulation results show that the established model has certain decision-making ability, and the BOA can converge to the global optimal solution at a faster speed, which can effectively solve the air combat task assignment problem.
      PubDate: 2022-12-01
       
  • Multi-UAV Route Re-Generation Method Based on Trajectory Data

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      Abstract: A large number of unmanned aerial vehicle (UAV) trajectory data related to air traffic information has important value in engineering fields. However, the cost of data and trajectory processing limits the applications, and as the number of UAVs increases rapidly, future UAVs’ path data will be very large. Therefore, this paper designs a multi-UAV route re-generation method based on trajectory data, which can realize the UAVs’ path data compression, de-aggregation, and regeneration tasks. Based on the trajectory data, the three-dimensional Douglas-Peucker algorithm is used to compress the trajectory data to reduce the storage space. The improved B-spline path smoothing algorithm based on the reversing control point is used to depolymerize and smooth the path. Simulation experiments show that the above multi-UAV route re-generation algorithm can obtain a more optimized path while maintaining the important characteristics of the original path.
      PubDate: 2022-12-01
       
  • Data Driven Model-Free Adaptive Control Method for Quadrotor Trajectory
           Tracking Based on Improved Sliding Mode Algorithm

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      Abstract: In order to solve the problems of dynamic modeling and complicated parameters identification of trajectory tracking control of the quadrotor, a data driven model-free adaptive control method based on the improved sliding mode control (ISMC) algorithm is designed, which does not depend on the precise dynamic model of the quadrotor. The design of the general sliding mode control (SMC) algorithm depends on the mathematical model of the quadrotor and has chattering problems. In this paper, according to the dynamic characteristics of the quadrotor, an adaptive update law is introduced and a saturation function is used to improve the SMC. The proposed control strategy has an inner and an outer loop control structures. The outer loop position control provides the required reference attitude angle for the inner loop. The inner loop attitude control ensures rapid convergence of the attitude angle. The effectiveness and feasibility of the algorithm are verified by mathematical simulation. The mathematical simulation results show that the designed model-free adaptive control method of the quadrotor is effective, and it can effectively realize the trajectory tracking control of the quadrotor. The design of the controller does not depend on the kinematic and dynamic models of the unmanned aerial vehicle (UAV), and has high control accuracy, stability, and robustness.
      PubDate: 2022-12-01
       
  • Airframe Damage Region Division Method Based on Structure Tensor Dynamic
           Operator

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      Abstract: In order to improve the accuracy of damage region division and eliminate the interference of damage adjacent region, the airframe damage region division method based on the structure tensor dynamic operator is proposed in this paper. The structure tensor feature space is established to represent the local features of damage images. It makes different damage images have the same feature distribution, and transform varied damage region division into consistent process of feature space division. On this basis, the structure tensor dynamic operator generation method is designed. It integrates with bacteria foraging optimization algorithm improved by defining double fitness function and chemotaxis rules, in order to calculate the parameters of dynamic operator generation method and realizing the structure tensor feature space division. And then the airframe damage region division is realized. The experimental results on different airframe structure damage images show that compared with traditional threshold division method, the proposed method can improve the division quality. The interference of damage adjacent region is eliminated. The information loss caused by over-segmentation is avoided. And it is efficient in operation, and consistent in process. It also has the applicability to different types of structural damage.
      PubDate: 2022-12-01
       
  • Non-Line-of-Sight Multipath Detection Method for BDS/GPS Fusion System
           Based on Deep Learning

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      Abstract: Non-line-of-sight (NLOS) multipath effect is the main factor that restricts the application of global navigation satellite system (GNSS) in complex environments, especially in urban canyon. The effective avoidance of NLOS signals can significantly improve the positioning performance of GNSS receiver. In this paper, an NLOS/LOS classification model based on recurrent neural network is proposed to classify satellite signals received in urban canyon environments. The accuracy of classification is 91%, and the recognition rate of NLOS is 89%; the classification performance is better than traditional machine learning classification models such as support vector machine. For BeiDou navigation satellite system/global positioning system (BDS/GPS) fusion system, the least square algorithm and extended Kalman filter are used to estimate the position. The experimental results show that the three-dimensional positioning accuracy after NLOS recognition is improved about 60% on average compared with the traditional methods, and the positioning stability is also improved significantly.
      PubDate: 2022-12-01
       
  • Reliability Evaluation of Two-Phase Degradation Process with a Fuzzy
           Change-Point

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      Abstract: For some products, degradation mechanisms change during testing, and therefore, their degradation patterns vary at different points in time; these points are called change-points. Owing to the limitation of measurement costs, time intervals for degradation measurements are usually very long, and thus, the value of change-points cannot be determined. Conventionally, a certain degradation measurement is selected as the change-point in a two-phase degradation process. According to the tendency of the two-phase degradation process, the change-point is probably located in the interval between two neighboring degradation measurements, and it is a fuzzy variable. The imprecision of the change-point may lead to the incorrect product’s reliability evaluation results. In this paper, based on the fuzzy theory, a two-phase degradation model with a fuzzy change-point and a statistical analysis method are proposed. First, a two-phase Wiener degradation model is developed according to the membership function of the change-point. Second, the reliability evaluation is carried out using maximum likelihood estimation and a fuzzy simulation approach. Finally, the proposed methodology is verified via a case study. The results of the study show that the proposed methodology can achieve more believable reliability evaluation results compared with those of the conventional approach.
      PubDate: 2022-12-01
       
  • System Life and Reliability Modeling of a Multiple Power Takeoffs
           Accessory Gearbox Transmission

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      Abstract: A mathematical model for system life and reliability of a multiple power takeoffs aeroengine accessory gearbox transmission is presented. The geometry model of gear train is distributed into several subsystems by different transmitted powers. The lives of each component are combined to determine the units, subsystems and entire system lives sequentially according to a strict series probability model. The unit and subsystem interface models are defined to dispose the loads of common components. The algorithm verification is presented and a numerical example is given to illustrate the use of this program. The initial design could not fulfill the life requirement. A design modification shows that the gear train has a more balanced life distribution by strengthening the weak parts, and the overall life of entire system is increased above the design requirement. This program can help the designer to approach an optimal accessory gearbox transmission design efficiently.
      PubDate: 2022-12-01
       
  • Impact Angle/Time Constraint Guidance Design Based on Fast Terminal Error
           Dynamics

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      Abstract: Considering the problem that the optimal error dynamics can only converge at the terminal time, an impact angle/time constraint missile guidance law with finite-time convergence is designed in this paper, which is based on the pure proportional navigation (PPN) guidance law and the fast terminal error dynamics (FTED) approach. The missile guidance model and FTED equation are given first, and the dynamic equation of impact angle/time error based on PPN is also derived. Then, the guidance law is designed based on FTED, and the guidance error can converge to 0 in a finite time. Furthermore, considering the field of view constraint, the guidance law is improved by using the saturation function mapping method. Finally, a numerical simulation example is given to verify the effectiveness of the guidance law, which shows that the guidance law proposed in this paper can make the missile quickly adjust to the desired states in advance, and effectively relieve the overload saturation pressure of the actuator.
      PubDate: 2022-12-01
       
  • Further Result on the Observer Design for One-Sided Lipschitz Systems

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      Abstract: This paper investigates the problem of observer design for a class of control systems. Different from current works, the nonlinear functions in the system only satisfy the property of the one-sided Lipschitz (OSL) condition but not quadratic inner-boundedness (QIB). Moreover, the case where the OSL constant is negative is specially investigated. Firstly, a full-order observer is constructed for the original system. Then, a reduced-order observer is also designed by using the decomposition method. The advantage and effectiveness of the proposed design scheme are shown in a numerical simulation.
      PubDate: 2022-12-01
       
  • Semantic Segmentation-Based Road Marking Detection Using Around View
           Monitoring System

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      Abstract: Road marking detection is an important branch in autonomous driving, understanding the road information. In recent years, deep-learning-based semantic segmentation methods for road marking detection have been arising since they can generalize detection result well under complicated environments and hold rich pixel-level semantic information. Nevertheless, the previous methods mostly study the training process of the segmentation network, while omitting the time cost of manually annotating pixel-level data. Besides, the pixel-level semantic segmentation results need to be fitted into more reliable and compact models so that geometrical information of road markings can be explicitly obtained. In order to tackle the above problems, this paper describes a semantic segmentation-based road marking detection method using around view monitoring system. A semiautomatic semantic annotation platform is developed, which exploits an auxiliary segmentation graph to speed up the annotation process while guaranteeing the annotation accuracy. A segmentation-based detection module is also described, which models the semantic segmentation results for the more robust and compact analysis. The proposed detection module is composed of three parts: vote-based segmentation fusion filtering, graph-based road marking clustering, and road-marking fitting. Experiments under various scenarios show that the semantic segmentation-based detection method can achieve accurate, robust, and real-time detection performance.
      PubDate: 2022-12-01
       
  • Sealing Performance of Pressure-Adaptive Seal

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      Abstract: A pressure-adaptive seal is developed to meet the demands of quick assembling and disassembling for an individual protection equipment in aerospace. The analysis model, which reflects the main characteristics of the seal structure, is built based on the finite element method and the Roth’s theory of rubber seal, and verified by the prototype test. The influences of precompression ratio, hardness of the sealing ring rubber and friction coefficient on the sealing performance are investigated by variable parameter method. Results show that the model can describe the essential characteristics of the pressure-adaptive seal structure, which has good follow-up to the cavity pressure to achieve the purpose of pressure self-adaptive. The leakage rate correlates negatively with the precompression ratio of the sealing ring and the hardness of the sealing ring material, while is positively related to the friction coefficient between the sealing ring and the sealing edge. The maximum contact stress on sealing surface has negative correlation with the precompression ratio of the sealing ring, and positive correlation with the hardness of the seal ring material. The damage risk of the sealing ring increases with the increase of the precompression ratio of sealing ring, the hardness of sealing ring material and the friction coefficient.
      PubDate: 2022-12-01
       
  • Meso-Scale Tearing Mechanism Analysis of Flexible Fabric Composite for
           Stratospheric Airship via Experiment and Numerical Simulation

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      Abstract: Stratospheric airships are controllable lighter-than-air aircraft and have great potential application in surveillance and communication. The envelopes, one of the main structures of a stratospheric airship, are generally made of flexible fabric composites to be lightweight, high strength, capable of containing lifting gas, and resistant to the harsh stratospheric environment. The composites, however, are prone to tearing. Hence, their tearing behavior has attracted great attention. This paper explores the meso-scale tearing mechanism of an envelope and the temperature influence on its tear strength via experiment and numerical simulation. Biaxial tear tests were conducted on cruciform specimens, which were contacted with liquids (cold alcohol or hot water) at different temperatures including −25, 20, 50, 80 °C. The specimens’ tear stresses were measured and the meso-scale tearing behavior was captured with a microscope. Besides, a novel finite element analysis model based on truss and spring elements was established to simulate the tearing behavior. It was found that the simulation result has a relative agreement with the tests. The simulation results show that the maximum tear stress of the envelope drops by 39.62% as the temperature rises from −60°Cto 80°C and the tensile properties of yarns and matrix account for stress concentration around a crack tip. This work deeply reveals the meso-scale tearing mechanism of the envelope and provides a valuable reference for exploring tearing properties of flexible fabric composites.
      PubDate: 2022-12-01
       
  • Effect of Moving Endwall on Hub Leakage Flow of Cantilevered Stator in a
           Linear Compressor Cascade

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      Abstract: The cantilevered stator has the advantages of reducing mass and axial length of highly loaded compressor. The details of the hub leakage flow resulting from the clearance between the high-speed moving hub and the cantilevered stator hub are unclear. In this paper, the effect of a moving endwall on the hub leakage flow of a cantilevered stator in a linear compressor cascade was studied. After the simulation method was verified with the experimental results, the time-averaged results of unsteady Reynolds averaged Navier-Stokes (URANS) were selected to study a case with a hub clearance of 2 mm. The results show that the effect of the moving endwall of the cantilevered cascade on the general characteristics with below 30% span increases the leakage mass flow rate and reduces the static pressure coefficient at three conditions of 0°, 6°, and −7° incidences, and the change is most significant at −7° incidence. The effect of the moving endwall on the total pressure loss coefficient varies with different operating conditions, which decreases by 15.94% at 0° incidence, and increases by 4.77% and 18.51% at 6° incidence and −7° incidence, respectively. The influence of the moving endwall is below 14% span at −7° incidence, below 23% span at 0° incidence, and below 30% span at 6° incidence. These effects correspond to the static pressure coefficient and the difference of static pressure coefficient representing the blade loading. When designing the cantilevered stator and matching between the stages of a multistage compressor, the quantitative research results of this paper have certain guiding significance.
      PubDate: 2022-12-01
       
  • Construction on Aerodynamic Surrogate Model of Stratospheric Airship

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      Abstract: Stratospheric airship can stay at an altitude of 20 km for a long time and carry various loads to achieve long-term stable applications. Conventional stratospheric airship configuration mainly includes a low-resistance streamline hull and inflatable “X”-layout fins that realize the self-stabilization. A fast aerodynamic predictive method is needed in the optimization design of airship configuration and the flight performance analysis. In this paper, a predictive surrogate model of aerodynamic parameters is constructed for the stratospheric airship with “X” fins based on the neural network. First, a geometric shape parameterized model, and a flow field parameterized model were established, and the aerodynamic coefficients of airships with different shapes used as the training and test samples were calculated based on computational fluid dynamics (SA turbulence model). The improved Bayesian regularized neural network was used as the surrogate model, and 20 types of airships with different shapes were used to test the effectiveness of network. It showed that the correlation coefficients of Cx, Cy, Cz, CMx, CMy, CMz were 0.928 7, 0.991 7, 0.991 9, 0.958 2, 0.986 1, 0.984 2, respectively. The aerodynamic coefficient distribution contour at different angles of attack and sideslip angles is used to verify the reliability of the method. The method can provide an effective way for a rapid estimation of aerodynamic coefficients in the airship design.
      PubDate: 2022-12-01
       
  • Active Magnetic Compensation Based on Parametric Resonance Magnetometer

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      Abstract: Based on the parametric resonance magnetometer (PRM) theory, this paper establishes an experimental system of PRM. The experimental results are consistent with the theoretical predictions. A PRM has been developed with sensitivity of 0.5 pT/Hz1/2, which can detect the magnitude of residual magnetic field; furthermore, a proportion-integration-differentiation (PID) closed-loop magnetic compensation system of the residual magnetic field also has been realized. Compared with open-loop compensation, the PID closed-loop compensation reduces the average value of the residual magnetic field in the z-axis direction from 0.024 4 nT to −0.002 3 nT, and the mean-square error from 0.208 3 nT to 0.069 1 nT. In the same way, the average value of the residual magnetic field in the y-axis direction is reduced from 0.081 6 nT to −0.004 2 nT, and the mean-square error from 0.131 6 nT to 0.046 1 nT. The magnitude of residual magnetic fields in both directions is decreased to the order of picotesla (pT). In addition, based on the signal waveforms of the magnetometer, a method of verifying the effect of magnetic compensation is proposed.
      PubDate: 2022-11-12
       
  • Numerical Study of Bifurcated Blood Flow in Three Different Blood
           Viscosity Models

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      Abstract: This study aimed to analyze the hemodynamic effects of bifurcated vessels using different blood viscosity models. Three-dimensional models of bifurcated vessels in the popliteal artery were constructed based on CT images, and hemodynamic parameters of the Newtonian, Casson, and two-phase models were calculated by the computational fluid dynamics method. Blood flowed through the popliteal artery. Blood flow velocity changed after the bifurcated vessel, with accelerated blood flow velocity in the anterior tibial artery. A low-velocity vortex region with a region of low wall shear stress (WSS) was generated outside the bifurcated vessel. Local non-Newtonian importance coefficients of great than 1 (i.e., IL > 1) occurred during the cardiac cycle, and IL > 1.75 occurred at the beginning and end of the cycle. Compared with the Casson and two-phase models, the Newtonian model has a larger vortex region and lower WSS. Low-velocity vortex regions and low WSS regions in the bifurcated vessels may contribute to the development of atherosclerosis. Blood exhibited non-Newtonian fluid properties inbifurcated vessels (IL > 1), and the effect of non-Newtonian properties was more pronounced at the beginning and end of heartbeats (IL > 1.75). The Newtonian model predicts a higher risk of atherosclerosis formation and the effect of non-Newtonian properties of blood should be considered in hemodynamic studies. It is necessary to consider the influence of non-Newtonian properties of blood in hemodynamic studies.
      PubDate: 2022-11-12
       
  • Reasoning about Software Trustworthiness with Derivation Trees

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      Abstract: In order to analyze the trustworthiness of complex software systems, we propose a model of evidence-based software trustworthiness called trustworthiness derivation tree (TDT). The basic idea of constructing a TDT is to refine main properties into key ingredients and continue the refinement until basic facts such as evidences are reached. The skeleton of a TDT can be specified by a set of rules, which are convenient for automated reasoning in Prolog. We develop a visualization tool that can construct the skeleton of a TDT by taking the rules as input, and allow a user to edit the TDT in a graphical user interface. In a software development life cycle, TDTs can serve as a communication means for different stakeholders to agree on the properties about a system in the requirement analysis phase, and they can be used for deductive reasoning so as to verify whether the system achieves trustworthiness in the product validation phase. We have piloted the approach of using TDTs in more than a dozen real scenarios of software development. Indeed, using TDTs helped us to discover and then resolve some subtle problems.
      PubDate: 2022-11-12
       
  • Distributed Photovoltaic Real-Time Output Estimation Based on Graph
           Convolutional Networks

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      Abstract: The rapid growth of distributed photovoltaic (PV) has remarkable influence for the safe and economic operation of power systems. In view of the wide geographical distribution and a large number of distributed PV power stations, the current situation is that it is difficult to access the current dispatch data network. According to the temporal and spatial characteristics of distributed PV, a graph convolution algorithm based on adaptive learning of adjacency matrix is proposed to estimate the real-time output of distributed PV in regional power grid. The actual case study shows that the adaptive graph convolution model gives different adjacency matrixes for different PV stations, which makes the corresponding output estimation algorithm have higher accuracy.
      PubDate: 2022-11-12
       
  • Early Detection Methods of Deep Tissue Pressure Injuries: A Systematic
           Review

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      Abstract: Deep tissue pressure injuries (DTPIs) have witnessed a growing prevalence in hospitals and other health care units especially among individuals with pathological conditions that give rise to restricted mobility, impaired sensation, and reduced tissue tolerance. The etiology of DTPIs has been a subject of controversy, to which several explanatory models have been proposed, including direct mechanical insult, ischemia-reperfusion, lymphatic occlusion, and inflammatory cytokines. In line with these pathophysiological scenarios, ultrasound, subepidermal moisture detection, and biomarker technologies have been proposed as potential early detection methods of DTPIs. This paper provides a systematic review involving these three methods. The conclusion is that combining and implementing these methods at different time periods during DTPIs development and progression respectively is likely to be the most universal, effective and promising way for DTPIs diagnosis.
      PubDate: 2022-11-12
       
  • Dlung: Unsupervised Few-Shot Diffeomorphic Respiratory Motion Modeling

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      Abstract: Lung image registration plays an important role in lung analysis applications, such as respiratory motion modeling. Unsupervised learning-based image registration methods that can compute the deformation without the requirement of supervision attract much attention. However, it is noteworthy that they have two drawbacks: they do not handle the problem of limited data and do not guarantee diffeomorphic (topology-preserving) properties, especially when large deformation exists in lung scans. In this paper, we present an unsupervised few-shot learning-based diffeomorphic lung image registration, namely Dlung. We employ fine-tuning techniques to solve the problem of limited data and apply the scaling and squaring method to accomplish the diffeomorphic registration. Furthermore, atlas-based registration on spatio-temporal (4D) images is performed and thoroughly compared with baseline methods. Dlung achieves the highest accuracy with diffeomorphic properties. It constructs accurate and fast respiratory motion models with limited data. This research extends our knowledge of respiratory motion modeling.
      PubDate: 2022-11-12
       
 
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