Sine Wave Model Research Articles

Efficient Bayesian inference and model selection for continuous gravitational waves in pulsar timing array data

Abstract Finding and characterizing gravitational waves from individual supermassive black hole binaries is a central goal of pulsar timing array experiments, which will require analysis methods that can be efficient on our rapidly growing datasets. Here we present a novel approach built on three key elements: (i) precalculating and interpolating expensive matrix operations; (ii) semi-analytically marginalizing over the gravitational-wave phase at the pulsars; (iii) numerically marginalizing over the pulsar distance uncertainties. With these improvements the recent NANOGrav 15 yr dataset can be analyzed in minutes after an O ( 1 h ) setup phase, instead of an analysis taking days–weeks with previous methods. The same setup can be used to efficiently analyze the dataset under any sinusoidal deterministic model. In particular, this will aid testing the binary hypothesis by allowing for efficient analysis of competing models (e.g. incoherent, monopolar, or dipolar sine wave model) and scrambled datasets for false alarm studies. The same setup can be updated in minutes for new realizations of the data, which enables large simulation studies.

Investigation of non-line-of-sight underwater optical wireless communications with wavy surface.

Underwater optical wireless communication (UOWC) systems have been widely researched to achieve high-speed and secure wireless communications. The non-line-of-sight (NLOS) UOWC system that uses the water surface to reflect signal light is widely studied to overcome the line-of-sight (LOS) channel limitation, particularly the channel blockage issue by marine biology or complex underwater topography. However, most previous NLOS UOWC studies have assumed a flat water surface or a general sine or cosine surface wave model for simplicity, leading to inaccurate performance estimations. In this paper, we build a theoretical NLOS UOWC framework with the Pierson wave model which considers both spatial correlation and time relativity information of wave incorporating wind speed, and investigate the signal-noise-ratio (SNR) and bit-error-rate (BER) performance. Results show that compared with the previous flat surface, the wavy surface can reduce the probability of achieving a satisfying signal level by up to 70%, affecting the performance of NLOS UOWC systems. Furthermore, we investigate the multiple-input-multiple-output (MIMO)-based NLOS UOWC under wavy surfaces. Results show that the MIMO principle can reduce the impact of the wavy surface, where the probability of achieving a satisfying signal level can be increased by up to 50% using the 2 × 4 MIMO configuration. However, results also show that further increasing the number of receivers may not further improve the system performance. The proposed model enables more accurate design and analysis of NLOS UOWC systems by accounting for the overlooked impact of wavy surfaces.

A NEW ROUGH FRACTURE PERMEABILITY MODEL OF COAL WITH INJECTED WATER BASED ON DAMAGED TREE-LIKE BRANCHING NETWORK

The fracture network structure of coal is very complex, and it has always been a hot issue to characterize the fracture network structure of coal by using a tree-like branching network. In this paper, a new rough fracture permeability model of water injection coal based on a damaged tree-like branching network is proposed. In this model, fractal theory and sine wave model are used to characterize the rough characteristics of fracture structure. In addition, the applicability of the model is verified by the self-developed experimental system, and the sensitivity analysis and weight analysis of the influencing factors in the model are carried out. The results show that the factors affecting the permeability of the established permeability mathematical model are mainly the amplitude factors of sinusoidal fluctuation, length ratio, maximum branch series, number of damaged fractures, opening ratio, opening fractal dimension and initial fracture length. Among them, the sinusoidal fluctuation amplitude factor has the greatest influence on the permeability and the other two are inversely proportional. Therefore, with pulsating water injection, the frequency of changes in the water pressure was altered to improve the water injection efficiency in coal fractures with sinusoidal distribution to increase permeability. The research results provide a theoretical basis for further improving the theoretical models for seepage in porous media and fluid flow analysis of damaged tree-like branching networks.

Temperature and the maturation of fish: a simple sine-wave model for predicting accelerated spring spawning

Temperature and the maturation of fish: a simple sine-wave model for predicting accelerated spring spawning

Impact of Indian summer monsoon in westerly dominated water resources of western Himalayas

ABSTRACT We used stable water isotopes of oxygen and hydrogen to identify and estimate the seasonal contribution of precipitation to the regional hydrology of Sindh and Rambiara catchments of western Himalayas. The different source waters exhibit significant spatio-temporal variations that correspond to the change in seasonal meteorology, precipitation form and moisture sources. The two-component hydrograph separation based on d-excess suggests that the western disturbances (WD) contribute dominantly (76 ± 4 %) to the regional hydrology, compared to Indian summer monsoon (ISM) rainfall (24 ± 4 %). A comparison of d-excess values of WD and ISM indicates the groundwater consists of 90 ± 3 % WD sources and 10 ± 2 % ISM sources, signifying distinct seasonal variations in groundwater recharge sources. The sine wave model results showed that the annual mean residence time (MRT) of groundwater for the Sindh catchment (5.8 ± 0.6 months) is greater than the Rambiara groundwater (3.6 ± 0.5 months). The lower isotope values observed in the river water than in the precipitation suggest its origin from the snowmelt. This study provides valuable insights into the hydrological processes operating in the high altitude Himalayan catchments to facilitate the improved understanding of runoff generation mechanisms and water resource management in future climate change scenarios.

A Multivariate Polynomial Regression to Reconstruct Ground Contact and Flight Times Based on a Sine Wave Model for Vertical Ground Reaction Force and Measured Effective Timings.

Effective contact () and flight () times, instead of ground contact () and flight () times, are usually collected outside the laboratory using inertial sensors. Unfortunately, and cannot be related to and because the exact shape of vertical ground reaction force is unknown. However, using a sine wave approximation for vertical force, and as well as and could be related. Indeed, under this approximation, a transcendental equation was obtained and solved numerically over a grid. Then, a multivariate polynomial regression was applied to the numerical outcome. In order to reach a root-mean-square error of 0.5 ms, the final model was given by an eighth-order polynomial. As a direct application, this model was applied to experimentally measured values. Then, reconstructed (using the model) was compared to corresponding experimental ground truth. A systematic bias of 35 ms was depicted, demonstrating that ground truth values were larger than reconstructed ones. Nonetheless, error in the reconstruction of from was coming from the sine wave approximation, while the polynomial regression did not introduce further error. The presented model could be added to algorithms within sports watches to provide robust estimations of and in real time, which would allow coaches and practitioners to better evaluate running performance and to prevent running-related injuries.

GRACEfully Closing the Water Balance: A Data‐Driven Probabilistic Approach Applied to River Basins in Iran

AbstractTo fully benefit from remotely sensed observations of the terrestrial water cycle, bias and random errors in these data sets need to be quantified. This paper presents a Bayesian hierarchical model that fuses monthly water balance data and estimates the corresponding data errors and error‐corrected water balance components (precipitation, evaporation, river discharge, and water storage). The model combines monthly basin‐scale water balance constraints with probabilistic data error models for each water balance variable. Each data error model includes parameters that are in turn treated as unknown random variables to reflect uncertainty in the errors. Errors in precipitation and evaporation data are parameterized as a function of multiple data sources, while errors in GRACE storage observations are described by a noisy sine wave model with parameters controlling the phase, amplitude, and randomness of the sine wave. Error parameters and water balance variables are estimated using a combination of Markov Chain Monte Carlo sampling and iterative smoothing. Application to semiarid river basins in Iran yields (a) significant reductions in evaporation uncertainty during water‐stressed summers, (b) basin‐specific timing and amplitude corrections of the GRACE water storage dynamics, and (c) posterior water balance estimates with average standard errors of 4–12 mm/month for water storage, 3.5–7 mm/month for precipitation, 2–6 mm/month for evaporation, and 0–2 mm/month for river discharge. The approach is readily extended to other data sets and other (gauged) basins around the world, possibly using customized data error models. The resulting error‐filtered and bias‐corrected water balance estimates can be used to evaluate hydrological models.

Seasonal variation of lung function in cystic fibrosis: Longitudinal modeling to compare a Midwest US cohort to international populations

Characterizing seasonal trend in lung function in individuals with chronic lung disease may lead to timelier treatment of acute respiratory symptoms and more precise distinction between seasonal exposures and variability. Limited research has been conducted to assess localized seasonal fluctuation in lung function decline in individuals with cystic fibrosis (CF) in context with routinely collected demographic and clinical data. We conducted a longitudinal cohort study of 253 individuals aged 6–22 years with CF receiving care at a pediatric Midwestern US CF center with median (range) of follow-up time of 4.7 (0–9.95) years, implementing two distinct models to estimate seasonality effects. The outcome, lung function, was measured as percent-predicted of forced expiratory volume in 1 s (FEV1). Both models showed that older age, being male, using Medicaid insurance and having Pseudomonas aeruginosa infection corresponded to accelerated FEV1 decline. A sine wave model for seasonality had better fit to the data, compared to a linear model with categories for seasonality. Compared to international cohorts, seasonal fluctuations occurred earlier and with greater volatility, even after adjustment for ambient temperature. Average lung function peaked in February and dipped in August, and FEV1 fluctuation was 0.81% predicted (95% CI: 0.52 to 1.1). Adjusting for temperature shifted the peak and dip to March and September, respectively, and decreased FEV1 fluctuation to 0.45% predicted (95% CI: 0.08 to 0.82). Understanding localized seasonal variation and its impact on lung function may allow researchers to perform precision public health for lung diseases and disorders at the point-of-care level.

A Specific Duration and High-energy Sine Wave Model to Reflect the Awaking and Falling Asleep Moments of Human

The process of falling asleep is complicated. Is there a mutation between sleep state and waking state? This paper applied a new specific duration and high-energy sine wave (SDHE) model based on single-channel brainwave to study this problem. The falling asleep moment and awaking moment could be identified through the SDHE. The closest research is AASM criterion. 30 seconds multi-channel brainwave as a frame was used to score the human sleep stage in the criterion. In the Dreams database used in this paper, an expert did the sleep classification of the 20 test subjects according to the AASM criterion. The switching step between waking stage and other sleep stages provided a basis for this paper. Within one minute of the time difference, the Cohen’s Kappa consistency of the discriminant result of the model and the expert was 0.58. In view of the strong and clear law of the SDHE, this paper would have more promising applications and significance in the signal processing of brainwave.

Influence of the Amplitude of Inlet Axial Pulsating Flow on Turbine Working Characteristics

The flow field at the outlet of the rotating detonation combustor has strong pulsation characteristics, and this strong impact will bring fatal damage to the downstream turbine. In this paper, the simplified sine wave model was used to simulate the rotating detonation wave to study the characteristics of the turbine working in a pulsating flow field. The results show that the greater the amplitude of the incoming flow pulsation, the stronger the non-uniformity of the aerodynamic parameters and heat transfer parameters of the flow field inside the turbine. The increase in the amplitude of the incoming flow pulsation will aggravate the separation of the end wall secondary flow and the cascade flow, resulting in greater flow loss and reducing the working efficiency of the turbine.

Study on Influence of Micro-tool Tip Arc Waviness on Cutting Micro Aspheric Surface

In this paper, the influence of the waviness of tip arc profile on the surface quality of micro transition arc workpiece is studied. Firstly, the contour curve of the surface of the micro tool was measured by using the radius amplitude measuring instrument, and the characteristic parameters of the waviness in the contour curve were found. A simulation study of the effect of feed rate on the quality of the machined surface of a sine wave model with different characteristics was performed by Matlab. It can be known from the simulation results that when a sine wave of 0.05sin(10t) exists in the contour of the tool tip arc, when the feed rate is small, the impact on the surface accuracy of the workpiece is greater, and a sin wave of 0.02sin(30t) locally affects the regional surface roughness is greater. With the increase of feed rate, a sin wave of 0.02sin(30t) has no effect on the surface roughness of the partial area, while a sin wave of 0.05sin(10t) still has a greater effect on the surface roughness of the partial area.

Flexible Adaptive Control of Snake-Like Robot Based on LSTM and Gait

This paper presents a flexible control method for snake-like robots to adapt to the environment autonomously. This method enables the snake-like robot to sense the environment and adjust autonomously according to the changes of the environment. For example, snake-like robots climb pipes with varying diameters. In order to achieve efficient and flexible motion, we adopt closed-loop gait control. This control method uses a parameterized sine wave (gait function) and long short-term memory network (LSTM) model. Because of the structure of LSTM is suitable for prediction of time series data, we use LSTM to predict the changes of joint angles that can best represent the shape change of snake-like robot, and integrate the predicted joint angle values with the gait values to realize the control of robot. Because this control method will eventually allow the snake-like robot to move autonomously in the changing environment, we can achieve the flexible adaptive behavior of the robot.

Dynamic Interpenetrating Polymer Network (IPN) Strategy for Multiresponsive Hierarchical Pattern of Reversible Wrinkle.

Dynamic micro-/nanowrinkle patterns with response to multienvironmental stimuli can offer a facile method for on-demand regulation of surface properties, thus allowing for generation of a smart surface. Here a practical yet robust strategy is described to fabricate redox, light and thermal responsive wrinkle by building dynamic double interpenetrating polymer network (IPN) as the top layer for a typical bilayer system. IPNs were constructed through the photochemical reaction of a mixture comprised of light-sensitive anthracene-containing polymer (PAN) and redox-sensitive disulfide-containing diacrylate monomer (DSDA). Thanks to the dynamic covalent reversible C-C bond in PAN and S-S bond in DSDA, the morphology of wrinkled surface not only can be reversibly and precisely (micrometer scale) tailored to all kinds of complicated hierarchical pattern permanently, but also can be controlled temporarily by irradiation of near-infrared light (NIR). A sine wave model is proposed to investigate the dynamics of real-time reversible wrinkle evolution. This general approach based on IPN allows independent multistimuli control over wettability and optical properties on the wrinkled surface,thus, presents a considerable alternative to implement a smart surface.

Characterization of noise emitted by a power tiller through geostatistics

ABSTRACT Noise is one of the harmful and stressful physical agents present in the workplace. Research performed with geostatistics to adjust the semivariogram of tractor noise were performed using the Gaussian and spherical model. In this way, the aim was to map the spatial variability of the noise emitted by a power tiller through the sine wave model, besides testing other fitting methods, in order to identify health zones for the workers. The experiment was performed with an agricultural power tiller (10.3 kW) placed in a working regime (1500 rpm), coupled to a brushcutter, and a digital sound level meter to collect noises in points distributed along a regular grid sampling of 2.0 × 2.0 m around the tractor. The spatial dependence of noise was analyzed through semivariogram fitting by different methods and by the wave model to obtain the spatial distribution map interpolated by kriging. It was possible to characterize the structure and the magnitude of the spatial dependence of the noise levels emitted by the tractor, as well as to map the spatial distribution. A maximum noise level of 96.5 dB was observed close to the tractor engine, a value above the limit of 85.0 dB for 8 h of daily exposure (NR-15). Thus, the use of ear protectors is recommended for both the tractor driver and the professionals who support agricultural operation within a radius of 6 m from the emitting source under the conditions studied.

МОДЕЛЬ ИНСОЛЯЦИИ ПОВЕРХНОСТИ ЗЕМЛИ В ПУНКТЕ "КАРАДАГ" ПО ДАННЫМ SSE

Anomalous enhancement of solar insolation of the earth's surface in the presence of foci of excitation in its depths can cause a response at local sites. Such foci include, first of all, recent and past (retro) volcanoes, such as the ancient volcano on the territory of Kara-Dag in the Crimea. The authors of this article have found increased, in comparison with other localities of the Crimea, general insolation according to SSE. According to the 22-year linear trend, the rate of insolation growth falling on the earth's surface at Kara-Dag has been calculated, which is 2,69 kWh/m2 per century, being more than 2 times higher than insolation growth in other areas of the Crimea. This phenomenon has been the subject of discussion, and additional research is needed, both on the geological structure of Kara-Dag and on the impact of external and internal forces. At the stage of studying the structure of data on insolation of the earth's surface at Kara-Dag, we have built a 6-order sine-wave model. The most powerful (amplitudes more than an order of magnitude higher than the noise level) regular oscillations on the 22-year interval have periods of 365,3 and 365,7 days. Statistical estimates of the degree of approximation by a sinusoidal model (R2 = 0,9, RMSE = 0,7) indicate that, in addition to regular periodic oscillations, there are irregular fluctuations in the data at time intervals determined by a continuous time-frequency wavelet analysis. The wavelet transformation graph highlights the interval of insolation energy growth at Kara-Dag locality after 1995. In order to analyze the statistical relationship of changes in local insolation of the Earth's surface with the Earth's rotation around the axis and its orbital movement, solar activity and global temperature, autoregression models of the power spectral density were calculated using which coherent oscillations were found between variations in Kara-Dag paragraph and variations in the data: on the length of the day (LOD) with a period of 11,8 years and a square modulus of coherence of 0,85; about solar activity with periods of 10,5, 3,6 years and a squared coherence modulus of 0,8 and 0,85; about global temperature indices with periods of 2,3, 3,5 years and squares of coherence modulus 0,7 and 0,9, respectively. The increased growth of insolation and the temperature of the earth at Kara-Dag locality that we found requires additional research and observations.

Estimation and validation of daily global solar radiation by day of the year-based models for different climates in China

Day of the year-based (DYB) models can achieve great accuracy in daily global solar radiation estimation without specific meteorological elements. Many empirical models (EMs) and machine learning (ML) methods have been proposed for DYB models. However, the number of their comparative studies based on diverse climates is limited. In this study, a grand total of 14 DYB models are established to estimate daily global solar radiation based on measured data from 1994 to 2015 at 35 meteorological stations in six climate zones of China. Detailed tasks are as follows: (1) Seven EMs and seven ML models are trained for solar radiation estimation. (2) A new EM and two novel ML models are proposed, i.e. hybrid 3rd order polynomial and sine wave model, adaptive neuro-fuzzy inference system (ANFIS) optimized by chaotic firefly algorithm (CFA) and ANFIS optimized by whale optimization algorithm with simulated annealing and roulette wheel selection (WOASAR). (3) Four statistical indicators are utilized to compare those models, and the best model for each station is decided. (4) We discuss the model parameters and climate variances of six specific stations in different climate zones. The comparison results demonstrate superb estimation precision and climate adaptability of the newly proposed models.

Remote analysis of myocardial fiber information in vivo assisted by cloud computing

A cloud-based analysis system of cardiac images is constructed to realize the remote sharing of cardiac images and related computing services. In its core service, a novel image post-processing approach is presented to obtain information on individual in vivo myocardial fibers. This approach is based on the anisotropic decomposition of the local deformation using tagged magnetic resonance (tMR) images of the heart. The local sine wave model (SinMod) is used in our approach to trace the motion in image sequences. Within this motion framework, a pair of anisotropic deformation components for each pixel is then extracted by Poisson orthogonal composition, which can represent exactly the local Poisson Effect. Based on these pair components, the direction structure (by the major deformation vector field) and the elastic property (by Poisson ratio) of myocardial fiber can be estimated. The experimental results demonstrate that our proposed approach is useful in analyzing information of in vivo myocardial fibers. It will have potential to provide the valuable cloud computing service for remote cardiac diagnosis and treatment.

Estimating mean residence time of karst groundwater in mountainous catchments of Western Himalaya, India

ABSTRACTThe mean residence time (MRT) of karst groundwater in three mountainous catchments of the Western Himalaya was estimated using multiple approaches: the tritium method, the sine wave model and tracer tests. Water samples were collected from precipitation, glacier melt, streams and karst springs for δ2H and tritium analysis during 2012 and 2013. High tritium values were observed in winter precipitation and low values in summer precipitation. The variation of tritium in karst springs was similar to that of the streams, whereas glacier melt showed lower tritium values. The MRT of cold karst springs was shorter than that of warm karst springs. The tracer breakthrough curves (TBC) retrieved for different springs suggested a short travel time for groundwater and possibly conduit flow. Deterioration of water quality and variation in flux magnitude are the two main practical consequences of the short travel time of karst groundwater in the region.EDITOR D. KoutsoyiannisASSOCIATE EDITOR K. Heal

Oscillatory patterns in heart rate variability and complexity: A meta-analysis

Abstract The study of instantaneous heart rate changes is a non invasive form to obtain indirect information about heart rate control. This beat-to-beat variation is denominated heart rate variability (HRV) and when estimated through frequency domain methods provides information about the sympathetic (SNS) or parasympathetic (PNS) nervous system. Beat-to-beat variation can also be estimated by nonlinear methods, then termed heart rate complexity (HRC). Even though HRC does not possess a straightforward relationship with the SNS or PNS, these estimators are also utilized to infer changes in the autonomic nervous system (ANS). In many situations, a low value of both indexes (HRV/HRC) is associated with several cardiovascular diseases. On the other hand, there are scenarios (such as, exercise and temperature challenges) in which those indexes appear to be less informative, mainly because the association between HRV/HRC and the ANS ceases to hold tight. Therefore, it is interesting to extract additional information from HRV/HRC analyses that could lead to a broader understanding of cardiac control. Previous experiments in our laboratory suggested the existence of an oscillatory component in HRV/HRC results along the time of experiment. The present study tested the existence of this pattern in HRV/HRC of 13 subjects running at constant speed. For this purpose, sine wave, linear and quadratic models were fitted to the results of these estimators. The sine wave model significantly, and more adequately than the other models, fitted the results obtained. Furthermore, the correlation obtained was significantly higher for the HRC data. This meta -analysis is a novel technique not found in the literature survey, moreover, it reveals a new way to approach cardiac control.

Performance assessment of different day-of-the-year-based models for estimating global solar radiation - Case study: Egypt

Different models are introduced to predict the daily global solar radiation in different locations but there is no specific model based on the day of the year is proposed for many locations around the world. In this study, more than 20 years of measured data for daily global solar radiation on a horizontal surface are used to develop and validate seven models to estimate the daily global solar radiation by day of the year for ten cities around Egypt as a case study. Moreover, the generalization capability for the best models is examined all over the country. The regression analysis is employed to calculate the coefficients of different suggested models. The statistical indicators namely, RMSE, MABE, MAPE, r and R2 are calculated to evaluate the performance of the developed models. Based on the validation with the available data, the results show that the hybrid sine and cosine wave model and 4th order polynomial model have the best performance among other suggested models. Consequently, these two models coupled with suitable coefficients can be used for estimating the daily global solar radiation on a horizontal surface for each city, and also for all the locations around the studied region. It is believed that the established models in this work are applicable and significant for quick estimation for the average daily global solar radiation on a horizontal surface with higher accuracy. The values of global solar radiation generated by this approach can be utilized in the design and estimation of the performance of different solar applications.