Classification of Citrus Plant Diseases Using Deep Transfer Learning

In recent years,the field of deep learning has played an important role towards automatic detection and classification of diseases in vegetables and fruits.This in turn has helped in improving the quality and production of vegetables and fruits.Citrus fruits arewell known for their taste and nutritional values.They are one of the natural and well known sources of vitamin C and planted worldwide.There are several diseases which severely affect the quality and yield of citrus fruits.In this paper,a new deep learning based technique is proposed for citrus disease classification.Two different pre-trained deep learning models have been used in this work.To increase the size of the citrus dataset used in this paper,image augmentation techniques are used.Moreover,to improve the visual quality of images,hybrid contrast stretching has been adopted.In addition,transfer learning is used to retrain the pre-trainedmodels and the feature set is enriched by using feature fusion.The fused feature set is optimized using a meta-heuristic algorithm,the Whale Optimization Algorithm(WOA).The selected features are used for the classification of six different diseases of citrus plants.The proposed technique attains a classification accuracy of 95.7%with superior results when compared with recent techniques.

Quaternion Integers Based Higher Length Cyclic Codes and Their Decoding Algorithm

The decoding algorithm for the correction of errors of arbitrary Mannheim weight has discussed for Lattice constellations and codes from quadratic number fields.Following these lines,the decoding algorithms for the correction of errors of n=p−12 length cyclic codes(C)over quaternion integers of Quaternion Mannheim(QM)weight one up to two coordinates have considered.In continuation,the case of cyclic codes of lengths n=p−12 and 2n−1=p−2 has studied to improve the error correction efficiency.In this study,we present the decoding of cyclic codes of length n=ϕ(p)=p−1 and length 2n−1=2ϕ(p)−1=2p−3(where p is prime integer andϕis Euler phi function)over Hamilton Quaternion integers of Quaternion Mannheim weight for the correction of errors.Furthermore,the error correction capability and code rate tradeoff of these codes are also discussed.Thus,an increase in the length of the cyclic code is achieved along with its better code rate and an adequate error correction capability.

Novel Scheme for Robust Confusion Component Selection Based on Pythagorean Fuzzy Set

The substitution box,often known as an S-box,is a nonlinear component that is a part of several block ciphers.Its purpose is to protect cryptographic algorithms from a variety of cryptanalytic assaults.A Multi-Criteria Decision Making(MCDM)problem has a complex selection procedure because of having many options and criteria to choose from.Because of this,statistical methods are necessary to assess the performance score of each S-box and decide which option is the best one available based on this score.Using the Pythagorean Fuzzy-based Technique for Order of Preference by Similarity to Ideal Solution(TOPSIS)method,the major objective of this investigation is to select the optimal S-box to be implemented from a pool of twelve key choices.With the help of the Pythagorean fuzzy set(PFS),the purpose of this article is to evaluate whether this nonlinear component is suitable for use in a variety of encryption applications.In this article,we have considered various characteristics of S-boxes,including nonlinearity,algebraic degree,strict avalanche criterion(SAC),absolute indicator,bit independent criterion(BIC),sum of square indicator,algebraic immunity,transparency order,robustness to differential cryptanalysis,composite algebraic immunity,signal to noise ratio-differential power attack(SNR-DPA),and confusion coefficient variance on some standard S-boxes that are Advanced Encryption Following this,the findings of the investigation are changed into Pythagorean fuzzy numbers in the shape of a matrix.This matrix is then subjected to an analysis using the TOPSIS method,which is dependent on the Pythagorean fuzzy set,to rank the most suitable S-box for use in encryption applications.

An Efficient Three-Factor Authenticated Key Agreement Technique Using FCM Under HC-IoT Architectures

The Human-Centered Internet of Things(HC-IoT)is fast becoming a hotbed of security and privacy concerns.Two users can establish a common session key through a trusted server over an open communication channel using a three-party authenticated key agreement.Most of the early authenticated key agreement systems relied on pairing,hashing,or modular exponentiation processes that are computationally intensive and cost-prohibitive.In order to address this problem,this paper offers a new three-party authenticated key agreement technique based on fractional chaotic maps.The new scheme uses fractional chaotic maps and supports the dynamic sensing of HC-IoT devices in the network architecture without a password table.The projected security scheme utilized a hash function,which works well for the resource-limited HC-IoT architectures.Test results show that our new technique is resistant to password guessing attacks since it does not use a password.Furthermore,our approach provides users with comprehensive privacy protection,ensuring that a user forgery attack causes no harm.Finally,our new technique offers better security features than the techniques currently available in the literature.

Generalization of Advanced Encryption Standard Based on Field of Any Characteristic

Nowadays most communications are done by utilizing digital transmission mechanisms.The security of this digital information transmitted through different communication systems is quite important.The secrecy of digital data is one of the burning topics of the digitally developed world.There exist many traditional algorithms in the literature to provide methods for robust communication.The most important and recent modern block cipher named the advanced encryption standard(AES)is one of the extensively utilized encryption schemes with binary based.AES is a succession of four fundamental steps:round key,sub-byte,shift row,and mix column.In this work,we will provide an innovative methodology for extending the AES in a Galois fieldwith any characteristic p.All four steps in the fundamental process with binary characteristics will be adjusted because of the new enhancement.By applying double affine transformations,we have enhanced the number of options in our suggested substitution boxes.The reconstruction of the nonlinear confusion component and encryption structure provides robustness in the generalized AES.The increase in the keyspace due to the Galois field generalization implies that we have improved additional confusion abilities and broadened the current notions.The implementation of the proposed structure of AES for image,audio,and video encryption will provide high security for secure communication.

Atmospheric Convection Model Based Digital Confidentiality Scheme

Nonlinear dynamics is a fascinating area that is intensely affecting a wide range of different disciplines of science and technology globally.The combination of different innovative topics of information security and high-speed computing has added new visions into the behavior of complex nonlinear dynamical systems which uncovered amazing results even in the least difficult nonlinearmodels.The generation of complex actions froma very simple dynamical method has a strong relation with information security.The protection of digital content is one of the inescapable concerns of the digitally advanced world.Today,information plays an important role in everyday life and affects the surroundings rapidly.These digital contents consist of text,images,audio,and videos,respectively.Due to the vast usage of digital images in the number of social and web applications,its security is one of the biggest issues.In this work,we have offered an innovative image encryption technique based on present criteria of confusion and diffusion.The designed scheme comprises two major nonlinear dynamical systems.We have employed discrete fractional chaotic iterative maps to add confusion capability in our suggested algorithm and continuous chaotic Lorenz system.We have verified our offered scheme by using statistical analysis.The investigations under the statistical tests suggested that our proposed technique is quite reasonable for the security of digital data.

Classification of Nonlinear Confusion Component Using Hybrid Multi-Criteria Decision Making

In today’s digital world,the most inevitable challenge is the protection of digital information.Due to the weak confidentiality preserving techniques,the existing world is facing several digital information breaches.To make our digital data indecipherable to the unauthorized person,a technique forfinding a crypto-graphically strong Substitution box(S-box)have presented.An S-box with sound cryptographic assets such as nonlinearity(NL),strict avalanche criterion(SAC),bit independence criteria(BIC),bit independence criteria of nonlinearity(BIC-NL),Bit independence criteria of Strict avalanche criteria(BIC-SAC),and Input/output XOR is considered as the robust S-box.The Decision-Making Trial and Evaluation Laboratory(DEMATEL)approach of multi-criteria decision making(MCDM)is proposed forfinding the interrelation among cryptographic properties.A combination of two MCDM methods namely Entropy and multi-objective optimization based on ratio analysis(MOORA)is applied for the best S-box selection.A robust substitution box is selected for secure communications in cryptography by using the combination of DEMETAL selection criteria,entro-py weight assigning,and MOORA ranking scheme.The combination of these three methods provides a fast selection procedure for the secure confusion com-ponent.The offered selection method can also be utilized for the choice of the best cryptosystem with highly secure properties and resistive against all possible linear and differential attacks in the cryptanalysis.

Observation of chimera patterns in a network of symmetric chaotic finance systems

The economic and financial systems consist of many nonlinear factors that make them behave as the complex systems.Recently many chaotic finance systems have been proposed to study the complex dynamics of finance as a noticeable problem in economics.In fact,the intricate structure between financial institutions can be obtained by using a network of financial systems.Therefore,in this paper,we consider a ring network of coupled symmetric chaotic finance systems,and investigate its behavior by varying the coupling parameters.The results show that the coupling strength and range have significant effects on the behavior of the coupled systems,and various patterns such as the chimera and multi-chimera states are observed.Furthermore,changing the parameters'values,remarkably influences on the oscillators attractors.When several synchronous clusters are formed,the attractors of the synchronized oscillators are symmetric,but different from the single oscillator attractor.

Chaotic dynamics of a fractional order glucose-insulin regulatory system

The fractional order model of a glucose-insulin regulatory system is derived and presented. It has been extensively proved in the literature that fractional order analysis of complex systems can reveal interesting and unexplored features of the system. In our investigations we have revealed that the glucose-insulin regulatory system shows multistability and antimonotonicity in its fractional order form. To show the effectiveness of fractional order analysis, all numerical investigations like stability of the equilibrium points, Lyapunov exponents, and bifurcation plots are derived. Various biological disorders caused by an unregulated glucose-insulin system are studied in detail. This may help better understand the regulatory system.