Initial Condition Sensitivity Research Articles

Data-driven computation of adjoint sensitivities without adjoint solvers: An application to thermoacoustics

Adjoint methods have been the pillar of gradient-based optimization for decades. They enable the accurate computation of a gradient (sensitivity) of a quantity of interest with respect to all system parameters in one calculation. When the gradient is embedded in an optimization routine, the quantity of interest can be optimized for the system to have the desired behavior. Adjoint methods, however, require the system's governing equations and their Jacobian. In this paper, we propose a computational strategy to infer the adjoint sensitivities from data when the governing equations might be unknown (or partly unknown), and noise might be present. The key component of this strategy is an echo state network, which learns the dynamics of nonlinear regimes with varying parameters, and it evolves dynamically via a hidden state. Although the framework does not make assumptions on the dynamical system, we focus on thermoacoustics, which are governed by nonlinear and time-delayed systems. First, we show that a parameter-aware echo state network (ESN) infers the parametrized dynamics. Second, we derive the adjoint of the ESN to compute two types of sensitivity: (i) parameter sensitivity, which is the gradient of a time-averaged cost functional with respect to physical or design parameters of the system, and (ii) initial condition sensitivity, which is the gradient of a cost functional of the final state with respect to the initial condition. Third, we propose the thermoacoustic echo state network (T-ESN), which embeds the physical knowledge in the network architecture for improved generalization. Fourth, we apply the framework to a variety of nonlinear thermoacoustic regimes of a prototypical system. We show that the T-ESN accurately infers the correct adjoint sensitivities of the acoustic energy with respect to the flame parameters and initial conditions. The results are robust to noisy data, from periodic, through quasiperiodic, to chaotic regimes. The inferred adjoint sensitivities are employed to suppress an instability via steepest descent. We show that a single network predicts the nonlinear bifurcations on unseen scenarios, which allows it to converge to the minimum of the acoustic energy. This work opens new possibilities for gradient-based data-driven design optimization. Published by the American Physical Society 2024

An Applied Image Cryptosystem on Moore’s Automaton Operating on δ ( q k )/𝔽 2

The volume of multimedia-based image data or video frames in Web 3.0 is constantly increasing, owing to the advancement of real-time data transmission. However, security vulnerabilities frequently impair the performance of real-time applications. Many researchers have recently proposed image encryption schemes based on a high-dimensional chaotic system due to properties such as ergodicity and initial state sensitivity. Nonetheless, most schemes have suffered from excessive computational complexity, low security, and the generation of cryptographically secure random numbers. To overcome these challenges, an efficient and highly secure cryptosystem is necessary for safe multimedia transmission in Web 3.0. This article proposes a novel work on the image cryptosystem based on the Escalation function with a one-time key-oriented Moore’s Automaton over a finite field 𝔽 2 . The Escalation function is a nonlinear scrambling technique for plaintext images that goes through the confusion phase and plays an essential role in row-column permutation. To make the algorithm more secure and robust in the diffusion phase, the proposed Moore’s Automaton produced ciphertext images through a highly random key stream generated by the combination of a logistic map and cyclic group. Specifically, the proposed Moore’s Automaton operates on δ ( q k )/𝔽 2 to render random binary bits into unpredictable sequences to construct ciphertext images. Our new finding quickens the speed and provides adequate key space, and pixel distributions are more uniform, have high entropy value, and are secure against differential and statistical attacks.

A new 3D hidden conservative chaotic system with multistability and its circuit implementation

A novel three-dimensional conservative system without an equilibrium point is constructed by replacing the square term x 2 + y 2 in the Vaidyanathan - Sundarapandian oscillator with a simple absolute value term |x|. The system is analyzed in detail by using time-domain waveform plots, bifurcation plots, Lyapunov exponent spectra, spectral entropy (SE), and C0 complexity. It is found that the system has rich dynamic behaviors: multiple phase trajectories can be tuned by only one parameter and multistability due to initial value sensitivity. The system shows that it can yield eight heterogeneous trajectories coexistent at different initial conditions, including periodic, quasi-periodic, and chaotic states. Additionally, the transient behavior was also observed. Finally, the experimental circuit was implemented, verifying both the physical realizability and the rich dynamic behaviors of the proposed system. With high complexity and sensitivity of parameter and initial condition, the proposed system is useful in image encryption and secure communication.

Chaotic map technique for enhancement security for android mobile system based on image encryption

Network <span>security continues to be the priority of many organizations. To ensure the protection of their data, they pay great attention to Encryption systems. Moreover, because of the enormous developments in networks of connection particularly the internet which has used by several people to share a variety of data kinds. The security of data has been a significant issue. As a result, there is a significant focus in using methods of decryption and encryption. Numerous encryption techniques have become advanced to preserve data protection, chaotic encryption systems are one of these methods widely used in recent years, where several techniques were proposed to use a chaotic map for encrypt images for the reason that of their characteristics e.g., random action unpredictability and initial conditions sensitivity. In this paper, proof authentication of sent information is used chaotic encryption algorithm to provide cipher text and hidden in image then send to another user. This approach is applied in cellular operating system environment (android). Thus, the sending and receiving of text will be safe and secure. The proposed approach is tested on different types of mobile. The proposed system gives good results.</span>

The Sensitivity of Initial Condition and Horizontal Resolution on Simulation of Tropical Cyclone Amphan over the Bay of Bengal using WRF-ARW Model

Simulation of Super Cyclonic Storm (SuCS) Amphan (2020) has been carried out as a case study to analyze the sensitivity of Initial Condition (IC) and Horizontal Resolution (HR) on the intensity, track, and landfall predictions of the Tropical Cyclones (TCs). The results suggest that the IC and HR have a significant impact on TC simulations. Diminishing the HR in simulation results in a comparatively higher severity of the system. The simulation with a reduced lead time and a comparatively smaller HR has forecasted the Minimum Central Pressure (MCP) distribution reasonably well. In comparison to the observations, the reduced lead time model run with higher resolution has forecasted the Maximum Sustained Wind Speed (MSWS) distribution precisely. According to the statistical analysis, the continual reduction of lead time in simulation with the HR of 27 km has simulated better track and landfall positions than other resolutions. Thus, the combination of reduced lead time and higher resolution in simulation may be considered for the proper track and landfall forecasting. Dhaka Univ. J. Sci. 69(3): 202-211, 2022 (June)

Free Response of a Rotational Nonlinear Energy Sink Coupled to a Linear Oscillator: Fractality, Riddling, and Initial-Condition Sensitivity at Large Initial Displacements

AbstractFor large initial rectilinear displacements, we investigate free response of a linear oscillator inertially coupled to a rotational nonlinear energy sink (NES). Absent direct rectilinear damping, two ranges of orbitally stable solutions are accessible, in contrast to one range at lower, intermediate energies (2021, J. Appl. Mech. 88, 121009). As at lower initial energies, fractal and riddled basins of attraction are identified for both previously considered numerical combinations of the two dimensionless parameters (characterizing rotational damping, and coupling of rotational to rectilinear motion). In this case, however, the final amplitude, in addition to the final angular orientation, displays initial-condition sensitivity. For one parameter combination, most motionless initial conditions (MICs, with the masses of the linear oscillator and NES both initially at rest) lead to a discrete set of “special” orbitally stable solutions with one of two amplitudes, and no MICs lead to complete dissipation of initial energy. For the other combination, the results are similar to those at intermediate initial energies, with no MICs leading to special solutions, and many leading to complete dissipation. Results for both parameter combinations strongly suggest that no qualitatively new behavior occurs for initial energies beyond those considered here, with nonrotating asymptotic special-amplitude solutions having larger rectilinear amplitude either not existing or existing in only very small parts of the MIC space. With direct damping of rectilinear motion, transient chaos leads to initial-condition sensitivity of settling time, with the case of no direct rectilinear damping providing good guidance to damped-case behavior.

Improved Sine-Tangent chaotic map with application in medical images encryption

The attractive properties of ergodicity, unpredictability, and initial state sensitivity have made chaotic maps the go-to tools in many applications, including cryptography and cyber–physical systems. Despite this, two challenges arise when using chaos systems in cryptography: (i) some one-dimensional (1D) chaotic maps do not satisfy the unpredictability property, and (ii) although they exhibit a complex and chaotic behavior, high-dimensional (HD) chaotic maps incur higher computational complexity. To address these issues, this paper proposes a new 1D chaotic map dubbed the improved Sine-Tangent map (IST map) that is derived from of the Sine map, a tangent function, and a Chebyshev polynomial of the first kind. Relative to chaotic maps, the proposed IST map provides better unpredictability and ergodicity, a vast chaotic range, enhanced complex behavior, and competitive computational complexity. Based on the IST map, we also introduced an encryption scheme for securing medical images in telemedicine. It consists of two diffusion phases, i.e., a bitwise XOR operation and a bitwise expanded XOR (eXOR) operation, with an intermediated confusion one, i.e., random circular-shift. An overriding step is foremost first completed before performing these cryptography phases, i.e., key generation. The secret key of the IST map is updated using the sine and cosine values of the sum of pixels of the input image. This leads to a unique secret key for each image. That is, one-time chaotic sequences are produced for each input image. The cyclic pattern of the sine and cosine values of the sum of pixels provides a prominent sensibility to small changes in the input image. Thus, the proposed algorithm is capable of resisting any chosen/known plaintext attacks. A performance analysis shows that the proposed algorithm outperforms a set of state-of-the-art comparison algorithms and its variants based on Sine, SE, and ST maps since it allows the best performance/complexity trade-off.

Influence of initial soil moisture in a regional climate model study over West Africa – Part 1: Impact on the climate mean

Abstract. The impact of soil moisture initial conditions on the mean climate over West Africa was examined using the latest version of the regional climate model of the International Centre for Theoretical Physics (RegCM4) at a 25 km horizontal resolution. The soil moisture reanalysis of the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis of the 20th century (ERA-20C) was used to initialize the control experiment, while its minimum and maximum values over the entire domain were used to establish the respective initial dry and wet soil moisture conditions (hereafter referred to as dry and wet experiments, respectively). For the respective control, wet and dry experiments, an ensemble of five runs from June to September was performed. In each experiment, we analyzed the two idealized simulations most sensitive to the dry and wet soil moisture initial conditions. The impact of soil moisture initial conditions on precipitation in West Africa is linear over the Central and West Sahel regions, where dry (wet) experiments lead to a rainfall decrease (increase). The strongest precipitation increase is found over the West Sahel for wet experiments, with a maximum change value of approximately 40 %, whereas the strongest precipitation decrease is found for dry experiments over the Central Sahel, with a peak change of approximately −4 %. The sensitivity of soil moisture initial conditions can persist for 3–4 months (90–120 d) depending on the region. However, the influence on precipitation is no longer than 1 month (between 15 and 30 d). The strongest temperature decrease is located over the Central and West Sahel, with a maximum change of approximately −1.5 ∘C in wet experiments, whereas the strongest temperature increase is found over the Guinea coast and Central Sahel for the dry experiments, with a maximum change of around 0.6 ∘C. A significant impact of soil moisture initial conditions on the surface energy fluxes is noted: in the wet (dry) experiments, a cooling (warming) of the surface temperature is associated with a decrease (increase) in sensible heat flux, an increase (decrease) in latent heat flux and a decrease (increase) in the boundary layer depth. Part 2 of this study (Koné et al., 2022) investigates the influence of soil moisture initial conditions on climate extremes.

Sensitivity‐Based Soil Moisture Assimilation for Improved Streamflow Forecast Using a Novel Forward Sensitivity Method (FSM) Approach

AbstractThe need for and the use of different data assimilation techniques to improve the quality of streamflow forecast is now well established. In this paper, the goal is to demonstrate the power of a new class of methods known as the forward sensitivity method (FSM) which is based on the temporal evolution of model sensitivities with respect to the control variables consisting of initial conditions and parameters. FSM operates in two phases: the first phase provides a simple algorithm for placing observations at or near where the square of forward sensitivities attains their maximum values. Using only this selected subset of observations in a weighted least squares method, the second phase then provides an estimate of the unknown elements of the control variables. In this paper, FSM based assimilation is applied to a simple class of two parameter model in a medium‐sized agriculture dominant watershed lying in the Krishna River Basin, India. Four assimilation scenarios were tested to determine the effect of assimilating only sensitive observations as well as the impact of temporally evolving initial condition sensitivity. Sensitivity results showed that observations during the monsoon time alone are enough for assimilation purposes, which has helped in reducing the computational time greatly. Assimilation and forecast results also indicated that the scenarios which assimilated only sensitive observations are better in estimating daily streamflow. From the obtained results, it is concluded that FSM based assimilation has significant potential to improve the streamflow simulations, especially in places where data availability remains a major challenge.

Hypertension and Stroke Cardiovascular Control Evaluation by Analyzing Blood Pressure, Cerebral Blood Flow, Blood Vessel Resistance and Baroreflex.

Cardiovascular diseases have been the leading causes of mortality in Taiwan and the world at large for decades. The composition of cardiovascular and cerebrovascular systems is quite complicated. Therefore, it is difficult to detect or trace the related signs of cardiovascular and cerebrovascular diseases. The characteristics and changes in cardiopulmonary system disease can be used to track cardiovascular and cerebrovascular disease prevention and diagnosis. This can effectively reduce the occurrence of cardiovascular and cerebrovascular diseases. This study analyzes the variability in blood pressure, cerebral blood flow velocity and the interaction characteristics using linear and nonlinear approaches in stroke, hypertension and healthy groups to identify the differences in cardiovascular control in these groups. The results showed that the blood pressure and cerebral blood flow of stroke patients and hypertensive patients were significantly higher than those of healthy people (statistical differences (p < 0.05). The cerebrovascular resistance (CVR) shows that the CVR of hypertensive patients is higher than that of healthy people and stroke patients (p < 0.1), indicating that the cerebral vascular resistance of hypertensive patients is slightly higher. From the patient’s blood flow and vascular characteristics, it can be observed that the cardiovascular system is different from those in healthy people. Baroreflex sensitivity (BRS) decreased in stroke patients (p < 0.05). Chaotic analysis revealed that the blood pressure disturbance in hypertensive patients has a higher chaotic behavior change and the difference in initial state sensitivity. Cross-correlation (CCF) analysis shows that as the course of healthy→hypertension→stroke progresses, the maximum CCF value decreases significantly (p < 0.05). That means that blood pressure and cerebral blood flow are gradually not well controlled by the self-regulation mechanism. In conclusion, cardiovascular control performance in hypertensive and stroke patients displays greater variation. This can be observed by the bio-signal analysis. This analysis could identify a measure for detecting and preventing the risk for hypertension and stroke in clinical practice. This is a pilot study to analyze cardiovascular control variation in healthy, hypertensive and stroke groups.

A color image encryption scheme based on 1D cubic map

In this paper, we introduce a new one-dimensional modular chaotic system based on the composition of the cubic map and the exponential function (1-DCE). The evaluation results demonstrate that chaos performances of the 1-DCE chaotic map can be enhanced significantly, such as a better Lyapunov exponent, a high initial state sensitivity, and infinite chaotic ranges when compared with the classical cubic map and other existing chaotic maps. Furthermore, we investigate its applications in color image encryption, where a new efficient image encryption scheme is proposed using the confusion-diffusion pattern. We notice that an efficient diffusion method is performed based on a constructed mask and a ribbon before applying bitxor operator, where we change the pixel values completely and randomly. This technique gives a unique encryption results for each encryption time and makes it unpredictable and sensitive to any infinitesimal changes. Moreover, the computer results and security analysis prove the encryption method efficiency when compared with existing works in terms of the required high security level against statistical and differential attacks, and also its significant encryption rapidity.

Free Response of a Rotational Nonlinear Energy Sink Coupled to a Linear Oscillator: Fractality, Riddling, and Initial-Condition Sensitivity at Intermediate Initial Displacements

AbstractFree response of a rotational nonlinear energy sink (NES) inertially coupled to a linear oscillator is investigated for dimensionless initial rectilinear displacements ranging from just above the smallest amplitude at which nonrotating, harmonically rectilinear motion is unstable absent direct rectilinear damping, up to the next-largest amplitude at which such motion is orbitally stable. With motionless initial conditions (MICs), i.e., initial velocity of the primary mass and initial angular velocity of the NES mass both zero, predicted behavior for two previously investigated combinations of the dimensionless parameters (characterizing rotational damping, and coupling of rectilinear and rotational motions) differs strongly from that found at smaller initial displacements (Ding and Pearlstein, 2021, “Free Response of a Rotational Nonlinear Energy Sink: Complete Dissipation of Initial Energy for Small Initial Rectilinear Displacements,” J. Appl. Mech., 88(1), p. 011005). For both combinations, a wide range of MICs leads to solutions displaying transient chaos and depending sensitively on initial conditions, giving rise to fractality and riddling in the relationship between initial conditions and asymptotic solutions. Absent direct rectilinear damping of the linear oscillator, for one combination of parameters there exists a wide range of MICs with trajectories leading to time-harmonic, orbitally stable “special” solutions with a single amplitude, but no MICs are found for which all initial energy is dissipated. For the other combination, no such special solutions are found, but there exist MICs for which all initial energy is dissipated. With direct rectilinear damping, sensitivity extends to a measure of settling time, which can be extremely sensitive to initial conditions. A statistical approach to this sensitivity is discussed, along with implications for design and implementation.

Steganography-based voice hiding in medical images of COVID-19 patients.

A novel image steganography technique in order to hide the ciphered voice data has been suggested in this work. The doctor’s voice comments belonging to a coronavirus disease 2019 (COVID-19) patient are hidden in a medical image in order to protect the patient information. The introduced steganography technique is based on chaos theory. Firstly, the voice comments of the doctor are converted to an image and secondly, they are ciphered utilizing the suggested encryption algorithm based on a chaotic system. Then, they are embedded into the cover medical image. A lung angiography dual-energy computed tomography (CT) scan of a COVID-19 patient is used as a cover object. Numerical and security analyses of steganography method have been performed in MATLAB environment. The similarity metrics are calculated for R, G, B components of cover image and stego image as visual quality analysis metrics to examine the performance of the introduced steganography procedure. For a 512 × 512 pixel cover image, SSIM values are obtained as 0.8337, 0.7926, and 0.9273 for R, G, B components, respectively. Moreover, security analyses which are differential attack, histogram, information entropy, correlation of neighboring pixels and the initial condition sensitivity are carried out. The information entropy is calculated as 7.9993 bits utilizing the suggested steganography scheme. The mean value of the ten UACI and NPCR values are obtained as 33.5688% and 99.8069%, respectively. The results of security analysis have revealed that the presented steganography procedure is able to resist statistical attacks and the chaotic system-based steganography scheme shows the characteristics of the sensitive dependence on the initial condition and the secret key. The proposed steganography method which is based on a chaotic system has superior performance in terms of being robust against differential attack and hiding encrypted voice comments of the doctor. Moreover, the introduced algorithm is also resistant against exhaustive, known plaintext, and chosen plaintext attacks.

Novel pseudo random key &amp; cosine transformed chaotic maps based satellite image encryption

Image encryption converts the images into unrecognizable forms that seems like a white noise. Digital Chaos has also emerged as one of the important technique to design secure and efficient image encryption schemes. The chaos theory possesses various desirable properties required for the encrypting images like initial state sensitivity, unpredictability and behavioural complexity. However, image encryption schemes suffer from vulnerabilities like differential attack, statistical, known/chosen plaintext attack, and brute force attack. This paper proposes a novel approach to generate a pseudorandom key. This pseudo random key is combined with Logistic map (LM), cosine transformed Logistic map (CTLM) and cosine transformed Logistic-Sine Map (CTLSM), one by one, to implement three secure and efficient methods for satellite image encryption. The scheme uses the 384-bit of share key to perform encryption during the process. The proposed approaches are tested for parameters such as Entropy, Correlation Coefficient (CC), Number of Changing Pixel Rate (NPCR), Unified Averaged Changed Intensity (UACI), Avalanche effect, Bit Correct Ratio (BCR) and Peak Signal to Noise Ratio (PSNR). The work also analyses the various cryptanalytic attacks on the proposed chaos and novel Pseudo random key combinations. The results show that the proposed pseudo random key and CTLSM combination outperforms the other two combinations, and is more efficient in resisting all type of attacks as well.

A color image encryption scheme reducing the correlations between R, G, B components

In this paper, a new color image encryption method based on confusion and diffusion processes has been introduced. A chaotic system based sub-block image swapping has been proposed in order to permutate the positions of the pixels as a confusion method. Moreover, the pixels in sub-block have been spirally shifted to increase the confusion level. Modulo and XOR operations which are based on a chaotic system have been suggested in order to transform the values of the pixels as a diffusion method. To do that, each pixel value is XORed with the next pixel and then modulo operation has been performed for the current and next pixels throughout the image. Double Random Phase Encoding (DRPE) method is also utilized as an optical setup in this study. In addition, an algorithm is suggested in order to reduce the correlations between R, G, B components of the color image. The security analyses performing histogram analysis, correlation coefficient analysis of two adjacent pixels, information entropy analysis, chi-squared test and differential attack have been carried out in order to show that the proposed algorithm scheme is robust against differential, statistical and exhaustive attacks. Moreover, secret key sensitivity, initial condition sensitivity, cropping attack, noise test and plaintext attacks have been done to evaluate the performance of the introduced algorithm. All analysis results have been carried out in MATLAB environment.

Invasive dynamics for a predator–prey system with Allee effect in both populations and a special emphasis on predator mortality

We considered a non-linear predator–prey model with an Allee effect on both populations on a two spatial dimension reaction-diffusion setup. Special importance to predator mortality was given as it may be often controlled through human-made harvesting processes. The local dynamics of the model was studied through boundedness, equilibrium, and stability analysis. An extensive numerical stability analysis was performed and found that bi-stability is not possible for the non-spatial model. By analyzing the spatial model, we found the condition for successful invasion and the persistence region of the species based on the predator Allee effect and its mortality parameter. Four different dynamics in this region of the parameter space are mainly explored. First, the Allee effect on both populations leads to various new types of species spread. Second, for a high value of per-capita growth rate, two completely new spreads (e.g., sun surface, colonial) have been found depending on the Allee effect parameter. Third, the Allee coefficient on the predator population leads to spatiotemporal chaos via a patchy spread for both linear and quadratic mortality rates. Finally, a more rigorous analysis is performed to study the chaotic nature of the system within the whole persistence domain. We have studied the possibility of chaos through temporal variation in different invasion regions. Furthermore, the chaotic fluctuation is studied through the sensitivity of initial conditions and by investigating the dominant Lyapunov exponent value.

A New WoT Cryptography Algorithm Based on GOST and Novel 5d Chaotic System

The concept Web of Things (WoT) goes well beyond the emphasis on the Internet as a means of sharing data, instead of introducing all resources and connections involving computers, data, and people to the Web. It, therefore, focuses on a range of problems and opportunities, thus paving the way for several exciting industries applications. In cryptography a range of main characteristics of chaotic systems such as non-linearity, initial condition sensitivity, and mixing properties are available. These characteristics provide an essential connection between cryptography and chaos. GOST block cipher is based on secret key secrecy. However, when the encryption process with the same key is used for plaintext, the same cipher text is created. Message replication can be easily detected by an adversary who is a bad link in every communication. In this paper, propose to use a 5d chaotic system combined with GOST block cipher to create a new secure Web of Things (WoT) cryptography system. The 5D chaotic system was used to generate chaotic random keys used in GOST algorithm to provide proper security with as high hardness randomly enhances the NIST fifteen statistical tests and modifies key schedule as security operations.

2D-SCMCI Hyperchaotic Map for Image Encryption Algorithm

Chaos has unpredictability and initial condition sensitivity, which known as a best candidate for cryptography application. However, there are many defects for the existing chaotic cryptography systems due to the use of chaotic maps that without complexity dynamic properties. To overcome these weaknesses, this work designed a 2D-SCMCI hyperchaotic map based on Cascade Modulation Couple (CMC) and two 1D-chaotic map. The dynamic characteristics of the 2D-SCMCI hyperchaotic map are analyzed through attractor trajectory, 0–1 test, bifurcation diagram, Lyapunov exponents and spectrum entropy (SE) complexity. The results of analysis indicate that 2D-SCMCI hyperchaotic map has rich dynamic performance and randomness, which illustrates that it is more suitable for image encryption algorithm. Therefore, an image encryption algorithm is proposed by 2D-SCMCI hyperchaotic map. In encryption algorithm, the image is scrambled by row and column, forward and backward diffusion are used to diffuse image pixel values. The security performances analysis results indicate that the introduced algorithm has better security characteristics.

A sensitive dynamic mutual encryption system based on a new 1D chaotic map

In this research paper, we propose a novel one-dimensional chaotic system based on the fraction of cosine over sine (1-DFCS). Evaluation of 1-DFCS indicates the existence of a complex chaotic behavior, an infinite chaotic range, and a high initial state sensitivity. We further propose a new sensitive dynamic mutual image encryption scheme (SDME) using 1-DFCS. SDME is designed with a dynamic diffusion and confusion, which gives a unique encryption process for each image. To ensure the dynamicity, SDME is enriched with a new proposed plain image sensitivity function (PISF). PISF uses the 1-DFCS, plain image, and secret key, which makes it unpredictable and sensitive to a tiny change. PISF is recommended to many image encryption schemes to raise their ability toward the differential attacks. Besides, we propose a mutual part encryption technique. This technique refers to two parties encrypting each other, where a small change in one part reflects the other part. These three characteristics make our scheme able to achieve a high-security level in a single round, which provides a combination of security and time efficiency. The experiment results prove that SDME provides better performance when compared with several state-of-the-art image encryption systems.

The role of atmospheric forcings and WRF physical set-up on convective initiation over Córdoba, Argentina

The accurate determination of the location and timing of convective initiation (CI) is a crucial aspect of forecasting and high impact weather warning systems associated with deep convection. Central Argentina, particularly the Sierras de Córdoba (SDC), is characterized by the regular occurrence of deep convective cells that reach supercell characteristics producing large hail and occasionally tornadoes.In order to analyze the sensitivity of the CI over SDC, an ensemble of 12 simulations with the WRF model at convection-permitting resolution (3 km.) was carried out to study a marginal supercell initiated on October 17, 2017 at the SDC foothills. The ensemble was built using 3 different microphysics (MP) parameterizations (WSM6, Thompson and Morrison) and 2 planetary boundary layer (PBL) parameterizations (Yonsei University and Mellor Yamada Janjic). Also, the sensitivity of initial and boundary conditions is considered by forcing the model with 2 different global analyses: the European Centre for Medium-Range Weather Forecast (ECMWF) model, and the Global Data Assimilation System (GDAS).The two different forcing data show low-level moisture differences, which later modulate the life-cycle of the simulated cells. A tracking algorithm was used to capture their life-cycle, and CI was detected at both the hills and the plains. Simulations forced with ECMWF analyses tend to show better results with characteristics closer to the ones observed including: initiation over the eastward slope of SDC, stronger cells and slow propagation. Among all simulations analyzed, the best performance was obtained with the combination of Thompson MP and Yonsei University PBL schemes.