A Double-Interactively Recurrent Fuzzy Cerebellar Model Articulation Controller Model Combined with an Improved Particle Swarm Optimization Method for Fall Detection

In many Eastern and Western countries,falling birth rates have led to the gradual aging of society.Older adults are often left alone at home or live in a long-term care center,which results in them being susceptible to unsafe events(such as falls)that can have disastrous consequences.However,automatically detecting falls fromvideo data is challenging,and automatic fall detection methods usually require large volumes of training data,which can be difficult to acquire.To address this problem,video kinematic data can be used as training data,thereby avoiding the requirement of creating a large fall data set.This study integrated an improved particle swarm optimization method into a double interactively recurrent fuzzy cerebellar model articulation controller model to develop a costeffective and accurate fall detection system.First,it obtained an optical flow(OF)trajectory diagram from image sequences by using the OF method,and it solved problems related to focal length and object offset by employing the discrete Fourier transform(DFT)algorithm.Second,this study developed the D-IRFCMAC model,which combines spatial and temporal(recurrent)information.Third,it designed an IPSO(Improved Particle Swarm Optimization)algorithm that effectively strengthens the exploratory capabilities of the proposed D-IRFCMAC(Double-Interactively Recurrent Fuzzy Cerebellar Model Articulation Controller)model in the global search space.The proposed approach outperforms existing state-of-the-art methods in terms of action recognition accuracy on the UR-Fall,UP-Fall,and PRECIS HAR data sets.The UCF11 dataset had an average accuracy of 93.13%,whereas the UCF101 dataset had an average accuracy of 92.19%.The UR-Fall dataset had an accuracy of 100%,the UP-Fall dataset had an accuracy of 99.25%,and the PRECIS HAR dataset had an accuracy of 99.07%.

Direct Pointwise Comparison of FE Predictions to StereoDIC Measurements:Developments and Validation Using Double Edge-Notched Tensile Specimen

To compare finite element analysis(FEA)predictions and stereovision digital image correlation(StereoDIC)strain measurements at the same spatial positions throughout a region of interest,a field comparison procedure is developed.The procedure includes(a)conversion of the finite element data into a triangular mesh,(b)selection of a common coordinate system,(c)determination of the rigid body transformation to place both measurements and FEA data in the same system and(d)interpolation of the FEA nodal information to the same spatial locations as the StereoDIC measurements using barycentric coordinates.For an aluminum Al-6061 double edge notched tensile specimen,FEA results are obtained using both the von Mises isotropic yield criterion and Hill’s quadratic anisotropic yield criterion,with the unknown Hill model parameters determined using full-field specimen strain measurements for the nominally plane stress specimen.Using Hill’s quadratic anisotropic yield criterion,the point-by-point comparison of experimentally based full-field strains and stresses to finite element predictions are shown to be in excellent agreement,confirming the effectiveness of the field comparison process.

Magnetic resonance imaging-based deep learning model to predict multiple firings in double-stapled colorectal anastomosis

BACKGROUND Multiple linear stapler firings during double stapling technique(DST)after laparoscopic low anterior resection(LAR)are associated with an increased risk of anastomotic leakage(AL).However,it is difficult to predict preoperatively the need for multiple linear stapler cartridges during DST anastomosis.AIM To develop a deep learning model to predict multiple firings during DST anastomosis based on pelvic magnetic resonance imaging(MRI).METHODS We collected 9476 MR images from 328 mid-low rectal cancer patients undergoing LAR with DST anastomosis,which were randomly divided into a training set(n=260)and testing set(n=68).Binary logistic regression was adopted to create a clinical model using six factors.The sequence of fast spin-echo T2-weighted MRI of the entire pelvis was segmented and analyzed.Pure-image and clinical-image integrated deep learning models were constructed using the mask region-based convolutional neural network segmentation tool and three-dimensional convolutional networks.Sensitivity,specificity,accuracy,positive predictive value(PPV),and area under the receiver operating characteristic curve(AUC)was calculated for each model.RESULTS The prevalence of≥3 linear stapler cartridges was 17.7%(58/328).The prevalence of AL was statistically significantly higher in patients with≥3 cartridges compared to those with≤2 cartridges(25.0%vs 11.8%,P=0.018).Preoperative carcinoembryonic antigen level>5 ng/mL(OR=2.11,95%CI 1.08-4.12,P=0.028)and tumor size≥5 cm(OR=3.57,95%CI 1.61-7.89,P=0.002)were recognized as independent risk factors for use of≥3 linear stapler cartridges.Diagnostic performance was better with the integrated model(accuracy=94.1%,PPV=87.5%,and AUC=0.88)compared with the clinical model(accuracy=86.7%,PPV=38.9%,and AUC=0.72)and the image model(accuracy=91.2%,PPV=83.3%,and AUC=0.81).CONCLUSION MRI-based deep learning model can predict the use of≥3 linear stapler cartridges during DST anastomosis in laparoscopic LAR surgery.This model might help determine the best anastomosis strategy by avoiding DST when there is a high probability of the need for≥3 linear stapler cartridges.

Steering the energy sharing of electrons in nonsequential double ionization with orthogonally polarized two-color field

Using the semiclassical ensemble model,the dependence of relative amplitude for the recollision dynamics in nonsequential double ionization(NSDI)of neon atom driven by the orthogonally polarized two-color field(OTC)laser field is theoretically studied.And the dynamics in two typical collision pathways,recollision-impact-ionization(RII)and recollisionexcitation with subsequent ionization(RESI),is systematically explored.Our results reveal that the V-shaped structure in the correlated momentum distribution is mainly caused by the RII mechanism when the relative amplitude of the OTC laser field is zero,and the first ionized electrons will quickly skim through the nucleus and share few energy with the second electron.As the relative amplitude increases,the V-shaped structure gradually disappears and electrons are concentrated on the diagonal in the electron correlation spectrum,indicating that the energy sharing after electrons collision is symmetric for OTC laser fields with large relative amplitudes.Our studies show that changing the relative amplitude of the OTC laser field can efficiently control the electron–electron collisions and energy exchange efficiency in the NSDI process.

Refinement of Adaptive Dynamical Simulation of Quantum Mechanical Double Slit Interference Phenomenon

We applied adaptive dynamics to double slit interference phenomenon using particle model and obtained partial successful results in our previous report. The patterns qualitatively corresponded well with experiments. Several properties such as concave single slit pattern and large influence of slight displacement of the emission position were different from the experimental results. In this study we tried other slit conditions and obtained consistent patterns with experiments. We do not claim that the adaptive dynamics is the principle of quantum mechanics, but the present results support the probability of adaptive dynamics as the candidate of the basis of quantum mechanics. We discuss the advantages of the adaptive dynamical view for foundations of quantum mechanics.

Model-constrained and data-driven double-supervision acoustic impedance inversion

Seismic impedance inversion is an important technique for structure identification and reservoir prediction.Model-based and data-driven impedance inversion are the commonly used inversion methods.In practice,the geophysical inversion problem is essentially an ill-posedness problem,which means that there are many solutions corresponding to the same seismic data.Therefore,regularization schemes,which can provide stable and unique inversion results to some extent,have been introduced into the objective function as constrain terms.Among them,given a low-frequency initial impedance model is the most commonly used regularization method,which can provide a smooth and stable solution.However,this model-based inversion method relies heavily on the initial model and the inversion result is band limited to the effective frequency bandwidth of seismic data,which cannot effectively improve the seismic vertical resolution and is difficult to be applied to complex structural regions.Therefore,we propose a data-driven approach for high-resolution impedance inversion based on the bidirectional long short-term memory recurrent neural network,which regards seismic data as time-series rather than image-like patches.Compared with the model-based inversion method,the data-driven approach provides higher resolution inversion results,which demonstrates the effectiveness of the data-driven method for recovering the high-frequency components.However,judging from the inversion results for characterization the spatial distribution of thin-layer sands,the accuracy of high-frequency components is difficult to guarantee.Therefore,we add the model constraint to the objective function to overcome the shortages of relying only on the data-driven schemes.First,constructing the supervisor1 based on the bidirectional long short-term memory recurrent neural network,which provides the predicted impedance with higher resolution.Then,convolution constraint as supervisor2 is introduced into the objective function to guarantee the reliability and accuracy of the inversion results,which makes the synthetic seismic data obtained from the inversion result consistent with the input data.Finally,we test the proposed scheme based on the synthetic and field seismic data.Compared to model-based and purely data-driven impedance inversion methods,the proposed approach provides more accurate and reliable inversion results while with higher vertical resolution and better spatial continuity.The inversion results accurately characterize the spatial distribution relationship of thin sands.The model tests demonstrate that the model-constrained and data-driven impedance inversion scheme can effectively improve the thin-layer structure characterization based on the seismic data.Moreover,tests on the oil field data indicate the practicality and adaptability of the proposed method.

Exploring the Potential of Cowpea-Wheat Double Cropping in the Semi-Arid Region of the Southern United States Using the DSSAT Crop Model

Information is limited on the potential of double-cropping cowpea (Vigna unguiculata L.) and wheat (Triticum aestivum L.) in the semiarid region of the southern United States. Using the Decision Support System for Agrotechnology Transfer (DSSAT) crop model and weather data of 80 years, we assessed the possibility of cowpea-wheat double-cropping in this region for grain purpose as affected by planting date and N application rate. Results showed that the possibility of double-cropping varied from 0% to 65%, depending on the cropping system. The possibility was less with systems comprising earlier planting dates of wheat and later planting dates of cowpea. Results indicated that cowpea-wheat double-cropping could be beneficial only when no N was applied, with wheat planted on October 15 or later. At zero N, the double-crops of cowpea planted on July 15 and wheat planted on November 30 were the most beneficial of all the 72 double-cropping systems studied. With a delay in planting cowpea, the percentage of beneficial double-cropping systems decreased. At N rates other than zero, fallow-wheat monocropping systems were more beneficial than cowpea-wheat double-cropping systems, and the benefit was greater at a higher N rate. At 100 kg N ha-1, the monocrop of wheat planted on October 15 was the most beneficial of all the 94 systems studied. Results further showed that fallow-wheat yields increased almost linearly with an increase in N rate from 0 to 100 kg∙ha-1. Fallow-wheat grain yields were quadratically associated with planting dates. With an increase in N rate, wheat yields reached the peak with an earlier planting date. Wheat yields produced under monocropping systems were greater than those produced under double-cropping systems for any cowpea planting date. Cowpea yields produced under monocropping systems were greater than those produced under any double-cropping system. The relationship between cowpea grain yields and planting dates was quadratic, with July 1 planting date associated with the maximum yields.

Application of the double absorbing boundary condition in seismic modeling

We apply the newly proposed double absorbing boundary condition（DABC）（Hagstrom et al., 2014） to solve the boundary reflection problem in seismic finite-difference（FD） modeling. In the DABC scheme, the local high-order absorbing boundary condition is used on two parallel artificial boundaries, and thus double absorption is achieved. Using the general 2D acoustic wave propagation equations as an example, we use the DABC in seismic FD modeling, and discuss the derivation and implementation steps in detail. Compared with the perfectly matched layer（PML）, the complexity decreases, and the stability and fl exibility improve. A homogeneous model and the SEG salt model are selected for numerical experiments. The results show that absorption using the DABC is considerably improved relative to the Clayton–Engquist boundary condition and nearly the same as that in the PML.

PRICING EUROPEAN OPTION IN A DOUBLE EXPONENTIAL JUMP-DIFFUSION MODEL WITH TWO MARKET STRUCTURE RISKS AND ITS COMPARISONS

Using Fourier inversion transform, P.D.E. and Feynman-Kac formula, the closedform solution for price on European call option is given in a double exponential jump-diffusion model with two different market structure risks that there exist CIR stochastic volatility of stock return and Vasicek or CIR stochastic interest rate in the market. In the end, the result of the model in the paper is compared with those in other models, including BS model with numerical experiment. These results show that the double exponential jump-diffusion model with CIR-market structure risks is suitable for modelling the real-market changes and very useful.

Predicting dynamics of soil organic carbon mineralization with a double exponential model in different forest belts of China

The dynamics of soil organic carbon （SOC） was analyzed by using laboratory incubation and double exponential model that mineralizable SOC was separated into active carbon pools and slow carbon pools in forest soils derived from Changbai and Qilian Mountain areas. By analyzing and fitting the CO2 evolved rates with SOC mineralization, the results showed that active carbon pools accounted tor 1.0% to 8.5% of SOC with an average of mean resistant times （MRTs） for 24 days, and slow carbon pools accounted for 91% to 99% of SOC with an average of MRTs for 179 years. The sizes and MRTs of slow carbon pools showed that SOC in Qilian Mountain sites was more difficult to decompose than that in Changbai Mountain sites. By analyzing the effects of temperature, soil clay content and elevation on SOC mineralization, results indicated that mineralization of SOC was directly related to temperature and that content of accumulated SOC and size of slow carbon pools from Changbai Mountain and Qilian Mountain sites increased linearly with increasing clay content, respectively, which showed temperature and clay content could make greater effect on mineralization of SOC.

Primary Reasoning behind the Double ITCZ Phenomenon in a Coupled Ocean-Atmosphere General Circulation Model

This paper investigates the processes behind the double ITCZ phenomenon, a common problem in Coupled ocean-atmosphere General Circulation Models (CGCMs), using a CGCM—FGCM-0 (Flexible General Circulation Model, version 0). The double ITCZ mode develops rapidly during the ?rst two years of the integration and becomes a perennial phenomenon afterwards in the model. By way of Singular Value Decomposition (SVD) for SST, sea surface pressure, and sea surface wind, some air-sea interactions are analyzed. These interactions prompt the anomalous signals that appear at the beginning of the coupling to develop rapidly. There are two possible reasons, proved by sensitivity experiments: (1) the overestimated east-west gradient of SST in the equatorial Paci?c in the ocean spin-up process, and (2) the underestimated amount of low-level stratus over the Peruvian coast in CCM3 (the Community Climate Model, Version Three). The overestimated east-west gradient of SST brings the anomalous equatorial easterly. The anomalous easterly, a?ected by the Coriolis force in the Southern Hemisphere, turns into an anomalous westerly in a broad area south of the equator and is enhanced by atmospheric anomalous circulation due to the underestimated amount of low-level stratus over the Peruvian coast simulated by CCM3. The anomalous westerly leads to anomalous warm advection that makes the SST warm in the southeast Paci?c. The double ITCZ phenomenon in the CGCM is a result of a series of nonlocal and nonlinear adjustment processes in the coupled system, which can be traced to the uncoupled models, oceanic component, and atmospheric component. The zonal gradient of the equatorial SST is too large in the ocean component and the amount of low-level stratus over the Peruvian coast is too low in the atmosphere component.

Simulation of double cold cores of the 35°N section in the YellowSea with a wave-tide-circulation coupled model

Based on the MASNUM wave-tide-circulation coupled numerical model, the temperature structure along 35°N in the Yellow Sea was simulated and compared with the observations. One of the notable features of the temperature structure along 35°N section is the double cold cores phenomena during spring and summer. The double cold cores refer to the two cold water centers located near 122°E and 125°E from the depth of 30m to bottom. The formation, maintenance and disappearance of the double cold cores are discussed. At least two reasons make the temperature in the center (near 123°E) of the section higher than that near the west and east shores in winter. One reason is that the water there is deeper than the west and east sides so its heat content is higher. The other is invasion of the warm water brought by the Yellow Sea Warm Current (YSWC) during winter.This temperature pattern of the lower layer (from 30m to bottom) is maintained through spring and summer when the upper layer (0 to 30m) is heated and strong thermocline is formed. Large zonal span of the 35°N section (about 600 km) makes the cold cores have more opportunity to survive. The double cold cores phenomena disappears in early autumn when the west cold core vanishes first with the dropping of the thermocline position.

Mathematical Model and Geometrical Model of Double Pitch ZN-type Worm Gear Set Based on Generation Mechanism

The current researches on the tooth surface mathematical equations and the theory of gearing mainly pay attention to the ordinary type worm gear set（e.g., ZN, ZA, or ZK）. The research of forming mechanism and three-dimensional modeling method for the double pitch worm gear set is not enough. So there are some difficulties in mathematical model deducing and geometry modeling of double pitch ZN-type worm gear set based on generation mechanism. In order to establish the mathematical model and the precise geometric model of double pitch ZN-type worm gear set, the structural characteristics and generation mechanism of the double pitch ZN-type worm gear set are investigated. Mathematical model of the ZN-type worm gear set is derived based on its generation mechanism and the theory of gearing. According to the mathematical model of the worm gear set which has been developed, a geometry modeling method of the double pitch ZN-type worm and worm gear is presented. Furthermore, a geometrical precision calculate method is proposed to evaluate the geometrical quality of the double pitch worm gear set. As a result, the maximum error is less than 6′10–4 mm in magnitude, thus the model of the double pitch ZN-type worm gear set is available to meet the requirements of finite element analysis and engineering application. The derived mathematical model and the proposed geometrical modeling method are helpful to guiding the design, manufacture and contact analysis of the worm gear set.

Effects of Doubled Carbon Dioxide on Rainfall Responses to Large-Scale Forcing:A Two-Dimensional Cloud-Resolving Modeling Study

ABSTRACT Rainfall responses to doubled atmospheric carbon dioxide concentration were investigated through the analysis of two pairs of two-dimensional cloud-resolving model sensitivity experiments. One pair of experiments simulated pre-summer heavy rainfall over southern China around the summer solstice, whereas the other pair of experiments simulated tropical rainfall around the winter solstice. The analysis of the time and model domain mean heat budget revealed that the enhanced local atmospheric warming was associated with doubled carbon dioxide through the weakened infrared radiative cooling during the summer solstice. The weakened mean pre-summer rainfall corresponded to the weakened mean infrared radiative cooling. Doubled carbon dioxide increased the mean tropical atmospheric warming via the enhanced mean latent heat in correspondence with the strengthened mean infrared radiative cooling during the winter solstice. The enhanced mean tropical rainfall was associated with the increased mean latent heat.

Valuing Credit Default Swap under a double exponential jump diffusion model

This paper discusses the valuation of the Credit Default Swap based on a jump market, in which the asset price of a firm follows a double exponential jump diffusion process, the value of the debt is driven by a geometric Brownian motion, and the default barrier follows a continuous stochastic process. Using the Gaver-Stehfest algorithm and the non-arbitrage asset pricing theory, we give the default probability of the first passage time, and more, derive the price of the Credit Default Swap.

Asymptotic Inference for the Weak Stationary Double AR(1) Model

An AR(1) model with ARCH(1) error structure is known as the first-order double autoregressive (DAR(1)) model. In this paper, a conditional likelihood based method is proposed to obtain inference for the two scalar parameters of interest of the DAR(1) model. Theoretically, the proposed method has rate of convergence O(n-3/2). Applying the proposed method to a real-life data set shows that the results obtained by the proposed method can be quite different from the results obtained by the existing methods. Results from Monte Carlo simulation studies illustrate the supreme accuracy of the proposed method even when the sample size is small.

Nucleon-nucleon interactions in the double folding model for fusion reactions

Nucleus-nucleus potentials are determined in the framework of double folding model for M3Y-Reid and M3Y- Paris effective nucleon-nucleon （NN） interactions. Both zero-range and finite-range exchange parts of NN interactions are considered in the folding procedure. In this paper the spherical projectile-spherical target system 16O＋^2008Pb is selected for calculating the barrier energies, fusion cross sections and barrier distributions with the density-independent and density-dependent NN interactions on the basis of M3Y-Reid and M3Y Paris NN interactions. The barrier energies become lower for Paris NN interactions in comparison with Reid NN interactions, and also for finite-range exchange part in comparison with zero-range exchange part. The density-dependent NN interactions give similar fusion cross sections and barrier distributions, and the density-independent NN interaction causes the barrier distribution moving to a higher position. However, the density-independent Reid NN interaction with zero-range exchange part gives the lowest fusion cross sections. We find that the calculated fusion cross sections and the barrier distributions are in agreement with the experimental data after renormalization of the nuclear potential due to coupled-channel effect.

Comparative Analysis between Single Diode and Double Diode Model of PV Cell: Concentrate Different Parameters Effect on Its Efficiency

This research appraises comparative analysis between single diode and double diode model of photovoltaic (PV) solar cells to enhance the conversion efficiency of power engendering PV solar systems. Single diode model is simple and easy to implement, whereas double diode model has better accuracy which acquiesces for more precise forecast of PV systems performance. Exploration is done on the basis of simulation results and MATLAB tool is used to serve this purpose. Simulations are performed by varying distinct model parameters such as solar irradiance, temperature, value of parasitic resistances, ideality factor of diode and number of series and parallel connected solar cells used to assemble PV array. Conspicuous demonstration is executed to analyze effects of these specifications on the efficiency curve and power vs. voltage output characteristics of PV cell for specified models.

Physical modeling based on hydrodynamic simulation for the design of InGaAs/InP double heterojunction bipolar transistors

A physical model for scaling and optimizing InGaAs/InP double heterojunction bipolar transistors（DHBTs） based on hydrodynamic simulation is developed.The model is based on the hydrodynamic equation,which can accurately describe non-equilibrium conditions such as quasi-ballistic transport in the thin base and the velocity overshoot effect in the depleted collector.In addition,the model accounts for several physical effects such as bandgap narrowing,variable effective mass,and doping-dependent mobility at high fields.Good agreement between the measured and simulated values of cutoff frequency,f t,and maximum oscillation frequency,f max,are achieved for lateral and vertical device scalings.It is shown that the model in this paper is appropriate for downscaling and designing InGaAs/InP DHBTs.

Evidences supporting the vascular etiology of post-double balloon enteroscopy pancreatitis: Study in porcine model

Double balloon enteroscopy(DBE) is an endoscopic technique broadly used to diagnose and treat small bowel diseases. Among the associated complications of the oral DBE, post-procedure pancreatitis has taken the most attention due to its gravity and the thought that it might be associated to the technique itself and anatomical features of the pancreas. However, as the etiology has not been clarified yet, this paper aims to review the published literature and adds new results from a porcine animal model. Biochemical markers, histological sections and the vascular perfusion of the pancreas were monitored in the pig during DBE practice. A reduced perfusion of the pancreas and bowel, the presence of defined hypoxic areas and disseminated necrotic zones were found in the pancreatic tissue of pigs. All these evidences contribute to support a vascular distress as the most likely etiology of the post-DBE pancreatitis.