Relative Distortion Research Articles

Multi Images Steganography using Neural Network

Abstract: Currently, the most successful approach to steganography in empirical objects, such as digital media, is to embed the payload while minimizing a suitably defined distortion function. The design of the distortion is essentially the only task left to the stegnographer since efficient practical codes exist that embed near the payload-distortion bound. The ractitioner goal is to design the distortion to obtain a scheme with a high empirical statistical detectability. In this paper, we propose a universal distortion design called universal wavelet relative distortion (UNIWARD) that can be applied for embedding in an arbitrary domain. The embedding distortion is computed as a sum of relative changes of coefficients in a directional filter bank decomposition of the cover image. The directionality forces the embedding changes to such parts of the cover object that are difficult to model in multiple directions, such as textures or noisy regions, while avoiding smooth regions or clean edges. We demonstrate experimentally using rich models as well as targeted attacks that steganographic methods built using UNIWARD match or outperform the current state of the art in the spatial domain, JPEG domain, and sideinformed JPEG domain.

Employee income, premium pricing, and high deductible health plan enrollment

ABSTRACT Employer health plan premiums are often subsidized at different levels according to enrollee income. When enrollees cross an income threshold, they lose some of the income-based subsidy resulting in higher premium prices for their plan choices. We use these discontinuous subsidy reductions, which induce relative price changes across plans, to assess the relationship between premium price and plan choice for workers in a large, national firm. We segmented individuals by income into $100 bins surrounding a $40,000 subsidy threshold and $200 bins surrounding a $110,000 subsidy threshold. We plotted these bins to visualize potential discontinuities and then estimated regression models that fit linear trends to the binned data at each subsidy threshold. Higher income workers were more likely to enrol in high deductible health plans (HDHPs) when those plans became relatively cheaper compared to traditional plans (estimate = −0.057, standard error = 0.027; p-value = 0.02). In contrast, lower income workers were less likely to enrol in a HDHP when the relative price fell (estimate = 0.065, standard error = 0.029, p-value = 0.03). Our findings indicate that responses to relative price distortions between insurance plan options differ by income and that benefit design should account for such heterogeneity.

Renewable energy targets and unintended storage cycling: Implications for energy modeling

SummaryTo decarbonize the economy, many governments have set targets for the use of renewable energy sources. These are often formulated as relative shares of electricity demand or supply. Implementing respective constraints in energy models is a surprisingly delicate issue. They may cause a modeling artifact of excessive electricity storage use. We introduce this phenomenon as “unintended storage cycling”, which can be detected in case of simultaneous storage charging and discharging. In this paper, we provide an analytical representation of different approaches for implementing minimum renewable share constraints in energy models, and show how these may lead to unintended storage cycling. Using a parsimonious optimization model, we quantify related distortions of optimal dispatch and investment decisions as well as market prices, and identify important drivers of the phenomenon. Finally, we provide recommendations on how to avoid the distorting effects of unintended storage cycling in energy modeling.

Validation of a Swedish translation of the gamblers’ beliefs questionnaire

The 20-item Gamblers’ Beliefs Questionnaire (GBQ) is used to identify cognitive distortions commonly had by gamblers. There is a great need for psychometrically validated instruments for both treatment and research purposes in the field of gambling addiction in Sweden. The purpose of this study was to validate a Swedish translation of the GBQ by assessing internal consistency, convergent validity, known-groups validity, the two-factor structure of the GBQ, and scaling success. The GBQ was translated into Swedish (GBQ-SE) and validated in a sample of 402 Swedish speaking women (47.9%) and men (52.1%) between 18–86 years, representing undergraduates, a working population, and people with current or historical gambling problems. The GBQ-SE showed excellent internal consistency and moderate relationships with instruments of problem gambling severity. We also showed that problem gamblers tend to endorse more gambling related distortions than non-problem gamblers by finding a significantly higher level of cognitive distortions in the problem gambler group. We were not able to confirm the two-factor structure in our sample. When assessing scaling success an overlap for eight of twenty of the items between the subscales was found. We conclude that the GBQ-SE is valid as a general instrument of gambling related cognitive distortions. It can be used to aid in treatment planning with gambling addicted clients, to evaluate treatment outcome, and for research purposes.

Analysis of the use of the Hanning Window for the measurement of interharmonic distortion caused by close tones in IEC standard framework.

The widespread use of devices based on power electronics and other nonlinear loads has led to an increase in harmonic distortion that affects the quality of power systems. Therefore, the correct measurement of harmonic and interharmonic content is necessary. The International Electrotechnical Commission (IEC) standards define the concepts of spectral and time grouping required for such measurements. This paper demonstrates that the procedures defined in the IEC standards are not sufficiently accurate when several close interharmonic tones interact due to the lack of stability of the values that the Discrete Fourier Transform obtains in each sampling window, and to the inaccuracy in the measurement of interharmonic groups and rates when using the Hanning window. This paper proposes novel solutions based on time aggregation and the use of other groupings and alternative windows. The results obtained are compared with the results produced by applying the rectangular window indicated in the standards, using sensitivity analysis varying one of the tones and using experimental results measuring the output signals of frequency inverters driving induction motors. The proposed method achieves greater accuracy and stability in the measurement of spectral groupings and their related distortion rates in signals with abundant and dispersed interharmonic content.

Liability for white-collar crimes in Ukraine: Theoretical and enforcement issues

This paper raises current theoretical and practical issues related to the implementation of a comprehensive mechanism of liability for economic criminal offences in Ukraine. The purpose of this study is to identify the main problem areas in the criminal law security of economic relations and to develop conceptual advice on their elimination. The paper uses a wide range of methodological tools (including comparative, historical, systemic, Aristotelian (dogmatic), modelling), which enabled a comprehensive and critical analysis of the current state and prospects for improving the criminal regulation of economic relations in the country. The results of the study are designed to promote the development of a unified conceptual model of protection of the national economy through criminal law. It is established that the prolonged economic crisis and distortions of market relations continue to adversely affect the state and dynamics of economic crime. The author’s opinion is also argued that since criminal law measures cannot objectively have a positive effect on economic processes, they can be relied on only to eliminate certain adverse consequences of economic activity. The study substantiated that the term “criminal offences against the market economy” in the context denoting the crimes for which responsibility is prescribed by Section VII of the Special Part of the Criminal Code of Ukraine, successfully passes conditional verification for compliance with the name of this structural part of the Criminal Code. Over the past five years, Ukraine’s criminal law policy on combating crimes in the sphere of economic activity has not undergone radical changes. Finally, there are hopes for the active development of legal research to become a reliable foundation for quality law-making to optimise the statutory framework in terms of criminal law response to economic and financial torts.

The distortions of party relations in Russia

The distortions of party relations in Russia

Fast and Robust Differential Relative Pose Estimation With Radial Distortion

In this letter, we address the differential two-view geometry problem of estimating the relative pose between two consecutive frames in the presence of radial distortion. This problem is of both theoretical and practical interests and has not been solved. We derive its parameterization and present an effective and robust generalized eigenvalue solver based on the hidden variable technique. Furthermore, we propose a nonlinear refinement scheme within the maximum likelihood criterion to produce more accurate estimates of the relative pose and radial distortion. Compared with the standard differential solutions without modeling the radial distortion, our approach can recover more geometrically correct point correspondences for a pair of radially distorted images. Moreover, our differential solution runs an order of magnitude faster than the discrete solution in terms of recovering the full camera motion. Experiment results on both synthetic and real data demonstrate the effectiveness of our model and method in dealing with the radial distortion.

Distortion of the Host Water Cages of Structure I Gas Hydrates: Structural Analysis of C2H4 Hydrate by Powder X-ray Diffraction

This study investigated the crystal structure and composition of C2H4 hydrate, prepared from finely powdered ice and C2H4 gas, using powder X-ray diffraction (PXRD). A crystallographic structural model of C2H4 hydrate, derived using the Rietveld and direct-space methods, shows that the occupancy of the 512 cages is 38%, assuming that the 51262 cages are fully occupied. Furthermore, similar to C2H6 hydrate, the centers of guest molecules (C2H4) lie out of the centers of the equatorial planes of the 51262 cages and near the centers of the 512 cages (carbon atoms are spherically arranged around these cores). However, the 512 and 51262 cages of C2H4 hydrate are larger and smaller, respectively, than the corresponding cages of C2H6 hydrate, despite the fact that C2H4 molecules are slightly smaller than C2H6 molecules. This difference is attributed to the high occupancy of the 512 cages of C2H4 hydrate, which leads to the expansion and concomitant contraction of the 512 and 51262 cages, respectively. Evidently, the relative distortion of the 51262 and 512 cages of the three-dimensional sI hydrate is a crucial factor determining its stability. In addition, the kinetic stability of C2H4 hydrate under low-temperature conditions was investigated by temperature-dependent PXRD.

An Adaptive Algorithm for Battery Charge Monitoring based on Frequency Domain Analysis

With technological advancement, the automobile industry is undergoing a design evolution. There has been an increase in the use of electrically actuated systems; electronics-based control systems, along with an increase in average power consumption. But such increased incorporation has been one of the main causes of roadside breakdowns. However, through the help of modelling and simulation manufacturers can evaluate vehicle operation; reduce their cost while achieving a competitive advantage in the automotive market. Here an automotive electrical system has been discussed. Its architecture consists of a battery, alternator, starter solenoid, and starter motor. Detailed modelling and simulation based on Simulink have been developed. Here charge level of automobile battery and its effect on the operational characteristics of an automobile has been considered and simulated in a MATLAB Simulink environment. First, a time-domain analysis has been made of the current response recorded from its maximum, minimum value, and slope characteristics. The response characteristics hence obtained are also analysed in the frequency domain through FFT analysis to obtain data characteristics in the frequency domain. A detailed analysis has been done at different levels of battery charge degradation to obtain a continuous data set for different states. The result shows significant changes both in time and frequency domain displaying discrimination in terms of DC and frequency components along with relative harmonics distortions enabling battery charge monitoring from starting transients. This method of response characteristics analysis helps in easier computation and in designing a system that can help with vehicle diagnosis and quality control.

Histopathological Evaluation of Ficus Capensis Aqueous Extract on Liver, Kidney, Intestine and its Potentials in Treatment of Anaemia

Ficus capensi is a nature of Nigerian multi ethnic group and it is been identified and called differently dy ethnic groups for example, igbo call it akporo, hausa -uwaryara,etc. The aim of the this research titlled; Histopathologica evaluation of ficus capensis ethanol extract on liver, kidney, intestine and it potentials in the treatment of anaemia is to evaluate the effect of leaf and stem back extract of ficus capensis in the treatment potential of anaemia and it’s histopathological effect on liver, kidney, and large intestine of wister rat. The animals were grouped into 5(A, B, C, D & E) and anaemia induced with cirfuroxime in all the groups except group E which is the negative control whereas other groups were treated with vitamins and leaf & stem bark of Ficuscapensis ethanol extract; group C wasn’t treated and it’s regarded as positive control. The blood sample were collected suing cardiac puncture and liver,kidney and large intestine were all harvested following dissection upon 14 days treatment and experimental termination. All the samples collected were analysed using standard methods. There was significant difference in body weight, same was observed in multiple comparism test on packed cell volume and haemoglobin after treatment with Vitamins, leaf and stem bark of Ficus capensis ethanol extract. It was also observed that there was relative distortion of large intestinal lumen, kidney and hepatocytes. Ficusis capensis leaf and bark has shown antianaemic potentials, however; its toxic effect on the selected organs (liver, Kidney and large intestine) called for caution among users.

Analysis of Laser beam welding of SS316L butt joints using Design of Experiments

Process control plays a significant role in increasing customer demand for quality, performance, cost; safety and reliability are essential for continuous growth, securing a process that allows least distortion after the laser welding process by applying with Experimentation Design. In the current experiments, the parameters of Laser power, welding speed, and Argon shielding are being used with L4 orthogonal array. These variables were checked to find the best control level combination of output and its related least distortion and maximum tensile strength. The X-ray radiography has tested the welds’ consistency and found that they are free from the surface and internal defects. The results show that welding speed, weld processes are critical parameter, and a shielding gas are not critical.

Orbital tumors

Orbit can be home for a spectrum of tumors with almost every orbital structure having the potential to harbor a neoplastic process. Surgical exposure and resection of orbital tumors can often be tricky due to the intricate anatomy of the region, with an additional complexity caused by a tumor related distortion. The clinical presentation depends on the primary structure involved and the location of the tumor within the orbit, and so does the scheme of management. Modern diagnostic imaging modalities offer a crucial pre-operative understanding of the precise location of the tumor within the orbit; it also helps in defining the nature of the tumor. Both these aspects are required for planning the appropriate surgical approach. Often, orbital tumors extend beyond the confines of the orbit requiring the tailoring of the surgical procedure, which may necessitate the involvement of a multidisciplinary team. The contemporary neurosurgical practice is also witnessing a progressive inclination towards minimally invasive endoscopic approaches, which have shown equally good if not better results in properly selected cases. Furthermore, early promising results with attempts at performing multisession stereotactic radiosurgery on orbital tumors has rekindled interest in this modality, in line with the management of intra-cranial tumors having a similar pathology. This article aims to recapitulate relevant surgical anatomy and to elucidate the current practice in the management of common orbital tumors encountered by neurosurgeons.

From laboratory-scaled experiments to numerical predictions of sonic boom level variability due to atmospheric turbulence

Supersonic flights of aircraft through the atmosphere create shock waves called “sonic booms.” Atmospheric turbulence affects the perceived loudness of sound at the ground level, mainly by changing its amplitude and rise time, which are significant factors in determining the acceptability of supersonic flight. Some authors compared theoretical predictions of sonic boom distortion to sonic boom recordings, but such analyses are limited because the parameters of turbulence cannot be measured accurately enough to allow detailed quantitative comparisons. In the 1990s David Blackstock showed that laboratory scaled experiments using N-waves produced by electrical sparks and a downscaled atmosphere offer an attractive alternative to field measurements since both the acoustic source and the turbulence can be controlled (Lipkens and Blackstock, JASA 1998, Lipkens and Blanc-Benon, CRAcadSci Paris 1995). Following this research, we developed at Ecole Centrale de Lyon two experimental setups to study separately the influence of temperature or random velocity fluctuations on the waveform distortion in relation to the occurrence of random caustics at large distances of propagation (Blanc-Benon, Lipkens, Dallois, Hamilton, and Blackstock, JASA 2002). The aim of this paper is to present recent experimental results obtained using optical interferometry and numerical predictions based on the nonlinear KZK propagation equation.

Quantitative effects of off-resonance related distortion on brain mechanical property estimation with magnetic resonance elastography.

Off-resonance related geometric distortion can impact quantitative MRI techniques, such as magnetic resonance elastography (MRE), and result in errors to these otherwise sensitive metrics of brain health. MRE is a phase contrast technique to determine the mechanical properties of tissue by imaging shear wave displacements and estimating tissue stiffness through inverse solution of Navier's equation. In this study, we systematically examined the quantitative effects of distortion and corresponding correction approaches on MRE measurements through a series of simulations, phantom models, and in vivo brain experiments. We studied two different k-space trajectories, echo-planar imaging and spiral, and we determined that readout time, off-resonance gradient strength, and the combination of readout direction and off-resonance gradient direction, impact the estimated mechanical properties. Images were also processed through traditional distortion correction pipelines, and we found that each of the correction mechanisms works well for reducing stiffness errors, but are limited in cases of very large distortion. The ability of MRE to detect subtle changes to neural tissue health relies on accurate, artifact-free imaging, and thus off-resonance related geometric distortion must be considered when designing sequences and protocols by limiting readout time and applying correction where appropriate.

Image synthesis via adversarial geometric consistency pursuit

Realistic image synthesis is a class of vision problems where the goal is to synthesize new images by fusing a source image and a target image. It is a challenging problem due to the visual gap between the two images, including geometry and appearance. To synthetically address the geometric distortion and appearance realism, we propose a novel method, the adversarial geometric consistency pursuit model (AGCP), which explicitly allows seamless image synthesis. The proposed method takes geometric correction and appearance harmonization into account, handling the relative scaling, spatial layout, color, viewpoint, and distortion transformation to generate a realistic composite image. Moreover, we also propose a joint geometric consistency pursuit loss that handles the geometric consistency and enhances the network to generalize better for different scales of source images. Our comparative evaluation demonstrates the effectiveness of the proposed method in the aforementioned challenging cases.

Near Real-Time Automatic Sub-Pixel Registration of Panchromatic and Multispectral Images for Pan-Sharpening

This paper presents a near real-time automatic sub-pixel registration method of high-resolution panchromatic (PAN) and multispectral (MS) images using a graphics processing unit (GPU). In the first step, the method uses differential geo-registration to enable accurate geographic registration of PAN and MS images. Differential geo-registration normalizes PAN and MS images to the same direction and scale. There are also some residual misalignments due to the geometrical configuration of the acquisition instruments. These residual misalignments mean the PAN and MS images still have deviations after differential geo-registration. The second step is to use differential rectification with tiny facet primitive to eliminate possible residual misalignments. Differential rectification corrects the relative internal geometric distortion between PAN and MS images. The computational burden of these two steps is large, and traditional central processing unit (CPU) processing takes a long time. Due to the natural parallelism of the differential methods, these two steps are very suitable for mapping to a GPU for processing, to achieve near real-time processing while ensuring processing accuracy. This paper used GaoFen-6, GaoFen-7, ZiYuan3-02 and SuperView-1 satellite data to conduct an experiment. The experiment showed that our method’s processing accuracy is within 0.5 pixels. The automatic processing time of this method is about 2.5 s for 1 GB output data in the NVIDIA GeForce RTX 2080Ti, which can meet the near real-time processing requirements for most satellites. The method in this paper can quickly achieve high-precision registration of PAN and MS images. It is suitable for different scenes and different sensors. It is extremely robust to registration errors between PAN and MS.

Neural network compensation method for improving detection accuracy of rotor position from magnetic encoder

With the advantages of low cost, small size and high resolution, the magnetic encoder is suitable for permanent magnet synchronous motor. However, due to the installation accuracy and the motor vibration, the rotor position error from magnetic encoder can seriously impact the performance of the motor. Therefore, it is necessary to reduce the detection error of the rotor position from the encoder. In this letter, a new rotor position detection method is proposed based on neural network. The characteristic of the position error from magnetic encoder is analysed, and the backpropagation neural network is presented to obtain the error compensation function. On the basis of the compensation function, the rotor position error can be corrected and thus the precise rotor position can be detected. The experimental results show that not only the rotor position error but also the related total harmonic distortion of the phase current and the torque ripple can be reduced effectively.

CNN‐based off‐angle iris segmentation and recognition

Accurate segmentation and parameterisation of the iris in eye images still remain a significant challenge for achieving robust iris recognition, especially in off-angle images captured in less constrained environments. While deep learning techniques (i.e. segmentation-based convolutional neural networks (CNNs)) are increasingly being used to address this problem, there is a significant lack of information about the mechanism of the related distortions affecting the performance of these networks and no comprehensive recognition framework is dedicated, in particular, to off-angle iris recognition using such modules. In this work, the general effect of different gaze angles on ocular biometrics is discussed, and the findings are then related to the CNN-based off-angle iris segmentation results and the subsequent recognition performance. An improvement scheme is also introduced to compensate for some segmentation degradations caused by the off-angle distortions, and a new gaze-angle estimation and parameterisation module is further proposed to estimate and re-project (correct) the off-angle iris images back to frontal view. Taking benefit of these, several approaches (pipelines) are formulated to configure an end-to-end framework for the CNN-based off-angle iris segmentation and recognition. Within the framework of these approaches, a series of experiments is carried out to determine whether (i) improving the segmentation outputs and/or correcting the output iris images before or after the segmentation can compensate for some off-angle distortions, (ii) a CNN trained on frontal eye images is capable of detecting and extracting the learnt features on the corrected images, or (iii) the generalisation capability of the network can be improved by training it on iris images of different gaze angles. Finally, the recognition performance of the selected approach is compared against some state-of-the-art off-angle iris recognition algorithms.

Impact of Energy Market Distortions on the Productivity of Energy Enterprises in China

China aims to enhance its total factor productivity (TFP) to achieve sustainable development. However, the looming energy market reform and its accompanying energy distortions prevent the realization of this ambitious goal. This study first establishes a theoretical model to reveal the inhibitory effects of energy market distortions on the TFP of energy enterprises, and we examine this issue using the micro-data of Chinese energy enterprises. The empirical results indicate that relative distortions among energy enterprises and overall distortions in different regions significantly inhibit the promotion of energy enterprises TFP, but the marginal inhibitory effects are diminishing. Energy market distortions also inhibit enterprises’ entry and accelerate enterprises’ exit from the energy market. Thus, eliminating inappropriate interventions in micro-energy enterprises, establishing a unified national energy market, and improving the competitive environment of energy companies are of great theoretical and policy importance.