Optimization of multi-color laser waveform for high-order harmonic generation

With the development of laser technologies,multi-color light-field synthesis with complete amplitude and phase control would make it possible to generate arbitrary optical waveforms.A practical optimization algorithm is needed to generate such a waveform in order to control strong-field processes.We review some recent theoretical works of the optimization of amplitudes and phases of multi-color lasers to modify the single-atom high-order harmonic generation based on genetic algorithm.By choosing different fitness criteria,we demonstrate that：（i） harmonic yields can be enhanced by 10 to 100 times,（ii） harmonic cutoff energy can be substantially extended,（iii） specific harmonic orders can be selectively enhanced,and（iv） single attosecond pulses can be efficiently generated.The possibility of optimizing macroscopic conditions for the improved phase matching and low divergence of high harmonics is also discussed.The waveform control and optimization are expected to be new drivers for the next wave of breakthrough in the strong-field physics in the coming years.

Mesh generation and optimization from digital rock fractures based on neural style transfer

The complex geometric features of subsurface fractures at different scales makes mesh generation challenging and/or expensive.In this paper,we make use of neural style transfer(NST),a machine learning technique,to generate mesh from rock fracture images.In this new approach,we use digital rock fractures at multiple scales that represent’content’and define uniformly shaped and sized triangles to represent’style’.The 19-layer convolutional neural network(CNN)learns the content from the rock image,including lower-level features(such as edges and corners)and higher-level features(such as rock,fractures,or other mineral fillings),and learns the style from the triangular grids.By optimizing the cost function to achieve approximation to represent both the content and the style,numerical meshes can be generated and optimized.We utilize the NST to generate meshes for rough fractures with asperities formed in rock,a network of fractures embedded in rock,and a sand aggregate with multiple grains.Based on the examples,we show that this new NST technique can make mesh generation and optimization much more efficient by achieving a good balance between the density of the mesh and the presentation of the geometric features.Finally,we discuss future applications of this approach and perspectives of applying machine learning to bridge the gaps between numerical modeling and experiments.

Improved Multileader Optimization with Shadow Encryption for Medical Images in IoT Environment

Nowadays,security plays an important role in Internet of Things(IoT)environment especially in medical services’domains like disease prediction and medical data storage.In healthcare sector,huge volumes of data are generated on a daily basis,owing to the involvement of advanced health care devices.In general terms,health care images are highly sensitive to alterations due to which any modifications in its content can result in faulty diagnosis.At the same time,it is also significant to maintain the delicate contents of health care images during reconstruction stage.Therefore,an encryption system is required in order to raise the privacy and security of healthcare data by not leaking any sensitive data.The current study introduces Improved Multileader Optimization with Shadow Image Encryption for Medical Image Security(IMLOSIE-MIS)technique for IoT environment.The aim of the proposed IMLOSIE-MIS model is to accomplish security by generating shadows and encrypting them effectively.To do so,the presented IMLOSIE-MIS model initially generates a set of shadows for every input medical image.Besides,shadow image encryption process takes place with the help of Multileader Optimization(MLO)withHomomorphic Encryption(IMLO-HE)technique,where the optimal keys are generated with the help of MLO algorithm.On the receiver side,decryption process is initially carried out and shadow image reconstruction process is conducted.The experimentation analysis was carried out on medical images and the results inferred that the proposed IMLOSIE-MIS model is an excellent performer compared to other models.The comparison study outcomes demonstrate that IMLOSIE-MIS model is robust and offers high security in IoT-enabled healthcare environment.

Remote Sensing Image Encryption Using Optimal Key Generation-Based Chaotic Encryption

The Internet of Things(IoT)offers a new era of connectivity,which goes beyond laptops and smart connected devices for connected vehicles,smart homes,smart cities,and connected healthcare.The massive quantity of data gathered from numerous IoT devices poses security and privacy concerns for users.With the increasing use of multimedia in communications,the content security of remote-sensing images attracted much attention in academia and industry.Image encryption is important for securing remote sensing images in the IoT environment.Recently,researchers have introduced plenty of algorithms for encrypting images.This study introduces an Improved Sine Cosine Algorithm with Chaotic Encryption based Remote Sensing Image Encryption(ISCACE-RSI)technique in IoT Environment.The proposed model follows a three-stage process,namely pre-processing,encryption,and optimal key generation.The remote sensing images were preprocessed at the initial stage to enhance the image quality.Next,the ISCACERSI technique exploits the double-layer remote sensing image encryption(DLRSIE)algorithm for encrypting the images.The DLRSIE methodology incorporates the design of Chaotic Maps and deoxyribonucleic acid(DNA)Strand Displacement(DNASD)approach.The chaotic map is employed for generating pseudorandom sequences and implementing routine scrambling and diffusion processes on the plaintext images.Then,the study presents three DNASD-related encryption rules based on the variety of DNASD,and those rules are applied for encrypting the images at the DNA sequence level.For an optimal key generation of the DLRSIE technique,the ISCA is applied with an objective function of the maximization of peak signal to noise ratio(PSNR).To examine the performance of the ISCACE-RSI model,a detailed set of simulations were conducted.The comparative study reported the better performance of the ISCACE-RSI model over other existing approaches.

Test Case Generation from UML-Diagrams Using Genetic Algorithm

Software testing has been attracting a lot of attention for effective software development.In model driven approach,Unified Modelling Language(UML)is a conceptual modelling approach for obligations and other features of the system in a model-driven methodology.Specialized tools interpret these models into other software artifacts such as code,test data and documentation.The generation of test cases permits the appropriate test data to be determined that have the aptitude to ascertain the requirements.This paper focuses on optimizing the test data obtained from UML activity and state chart diagrams by using Basic Genetic Algorithm(BGA).For generating the test cases,both diagrams were converted into their corresponding intermediate graphical forms namely,Activity Diagram Graph(ADG)and State Chart Diagram Graph(SCDG).Then both graphs will be combined to form a single graph called,Activity State Chart Diagram Graph(ASCDG).Both graphs were then joined to create a single graph known as the Activity State Chart Diagram Graph(ASCDG).Next,the ASCDG will be optimized using BGA to generate the test data.A case study involving a withdrawal from the automated teller machine(ATM)of a bank was employed to demonstrate the approach.The approach successfully identified defects in various ATM functions such as messaging and operation.

An Effective Signcryption with Optimization Algorithm for IoT-enabled Secure Data Transmission

Internet of Things(IoT)allows several low resources and controlled devices to interconnect,calculate processes and make decisions in the communication network.In the heterogeneous environment for IoT devices,several challenging issues such as energy,storage,efficiency,and security.The design of encryption techniques enables the transmission of the data in the IoT environment in a secured way.The proper selection of optimal keys helps to boost the encryption performance.With this motivation,the study presents a signcryption with quantum chaotic krill herd algorithm for secured data transmission(SCQCKH-SDT)in IoT environment.The proposed SCQCKHSDT technique aims to effectively encrypts the data by the use of optimal keys generated by the CQKH algorithm.The proposed SCQCKH-SDT technique initially employs the signcryption technique for the encryption of data.In order to optimize the secrecy,the optimal key generation process is carried out using Chaotic Krill Herd(CQKH)algorithm.The CQKH algorithm incorporates the concept of quantum computing and chaotic theory into the traditional KH algorithm.The performance validation of the SCQCKH-SDT technique is performed using benchmark dataset.An extensive comparative analysis reported the superior performance of the SCQCKH-SDT technique over the recent approaches.

Wind Driven Optimization-Based Medical Image Encryption for Blockchain-Enabled Internet of Things Environment

Internet of Things(IoT)and blockchain receive significant interest owing to their applicability in different application areas such as healthcare,finance,transportation,etc.Medical image security and privacy become a critical part of the healthcare sector where digital images and related patient details are communicated over the public networks.This paper presents a new wind driven optimization algorithm based medical image encryption(WDOA-MIE)technique for blockchain enabled IoT environments.The WDOA-MIE model involves three major processes namely data collection,image encryption,optimal key generation,and data transmission.Initially,the medical images were captured from the patient using IoT devices.Then,the captured images are encrypted using signcryption technique.In addition,for improving the performance of the signcryption technique,the optimal key generation procedure was applied by WDOA algorithm.The goal of the WDOA-MIE algorithm is to derive a fitness function dependent upon peak signal to noise ratio(PSNR).Upon successful encryption of images,the IoT devices transmit to the closest server for storing it in the blockchain securely.The performance of the presented method was analyzed utilizing the benchmark medical image dataset.The security and the performance analysis determine that the presented technique offers better security with maximum PSNR of 60.7036 dB.

Creation of multi-frequency terahertz waves by optimized cascaded difference frequency generation

A new scheme which generates multi-frequency terahertz(THz)waves from planar waveguide by the optimized cascaded difference frequency generation(OCDFG)is proposed.A THz wave with frequencyω_(T1)is generated by the OCDFG with two infrared pump waves,and simultaneously a series of cascaded optical waves with a frequency intervalω_(T1)is generated.The THz wave with a frequency of M-timesω_(T1)is generated by mixing the m-th-order and the(m+M)-th-order cascaded optical wave.The phase mismatch distributions of cascaded difference frequency generation(CDFG)are modulated by changing the thickness of planar waveguide step by step,thereby satisfying the phase-matching condition from first-order to high-order cascaded Stokes process step by step.As a result,the intensity of THz wave can be enhanced and modulated by controlling the cascading order of OCDFG.

Theoretical research on terahertz wave generation from planar waveguide by optimized cascaded difference frequency generation

A novel scheme for high-efficiency terahertz(THz)wave generation based on optimized cascaded difference frequency generation(OCDFG)with planar waveguide is presented.The phase mismatches of each-order cascaded difference frequency generation(CDFG)are modulated by changing the thickness of the waveguide,resulting in a decrement of phase mismatches in cascaded Stokes processes and an increment of phase mismatches in cascaded anti-Stokes processes simultaneously.The modulated phase mismatches enhance the cascaded Stokes processes and suppress the cascaded anti-Stokes processes simultaneously,yielding energy conversion efficiencies over 25%from optical wave to THz wave at 100 K.

High-efficiency terahertz wave generation with multiple frequencies by optimized cascaded difference frequency generation

High-efficiency terahertz(THz) wave generation with multiple frequencies by optimized cascaded difference frequency generation(OCDFG) is investigated at 100 K using a nonlinear crystal consisting of a periodically poled lithium niobate(PPLN) part and an aperiodically poled lithium niobate(APPLN) part.Two infrared pump waves with a frequency difference ω_(T1) generate THz waves and a series of cascaded optical waves in the PPLN part by cascaded difference frequency generation(CDFG).The generated cascaded optical waves with frequency interval ω_(T1) then further interact in the APPLN part by OCDFG,yielding the following two advantages.First,OCDFG in the APPLN part is efficiently stimulated by inputting multi-order cascaded optical waves rather than the only two intense infrared pump waves,yielding unprecedented energy conversion efficiencies in excess of 37% at 1 THz at 100 K.Second,THz waves with M timesω_(T1) are generated by mixing the mth-order and the(m+M)th-order cascaded optical waves by designing poling period distributions of the APPLN part.

THz wave generation by repeated and continuous frequency conversions from pump wave to high-order Stokes waves

We propose a novel scheme for THz wave generation by repeated and continuous frequency conversions from pump wave to high-order Stokes waves(HSWs).The repeated frequency conversions are accomplished by oscillations of Stoke waves in resonant cavity(RC)where low-order Stokes waves(LSWs)are converted to high-order Stokes waves again and again.The continuous frequency conversions are accomplished by optimized cascaded difference frequency generation(OCDFG)where the poling periods of the optical crystal are aperiodic leading to the frequency conversions from low-order Stokes waves to high-order Stokes waves uninterruptedly and unidirectionally.Combined with the repeated and continuous frequency conversions,the optical-to-THz energy conversion efficiency(OTECE)exceeds 26%at 300 K and 43%at 100 K with pump intensities of 300 MW/cm^(2).

Encryption with User Authentication Model for Internet of Medical Things Environment

Internet of Medical Things(IoMT)enabled e-healthcare has the potential to greately improve conventional healthcare services significantly.However,security and privacy become major issues of IoMT because of the restricted processing abilities,storage,and energy constraints of the sensors.Therefore,it leads to infeasibility of developing traditional cryptographic solutions to the IoMT sensors.In order to ensure security on sensitive medical data,effective encryption and authentication techniques need to be designed to assure security of the patients and healthcare service providers.In this view,this study designs an effective metaheuristic optimization based encryption with user authentication(EMOE-UA)technique for IoMT environment.This work proposes an EMOE-UA technique aims to accomplish mutual authentication for addressing the security issues and reducing the computational complexity.Moreover,the EMOE-UA technique employs optimal multikey homomorphic encryption(OMKHE)technique to encrypt the IoMT data.Furthermore,the improved social spider optimization algorithm(ISSOA)was employed for the optimal multikey generation of the MKHE technique.The experimental result analysis of the EMOE-UA technique takes place using benchmark data and the results are examined under various aspects.The simulation results reported the considerably better performance of the EMOE-UA technique over the existing techniques.

Tuning the second-harmonic generation in AlGaAs nanodimers via non-radiative state optimization [Invited]

Dielectric nanocavities are emerging as a versatile and powerful tool for the linear and nonlinear manipulation of light at the nanoscale. In this work, we exploit the effective coupling of electric and toroidal modes in Al Ga As nanodimers to locally enhance both electric and magnetic fields while minimizing the optical scattering, thereby optimizing their second-harmonic generation efficiency with respect to the case of a single isolated nanodisk. We also demonstrate that proper near-field coupling can provide further degrees of freedom to control the polarization state and the radiation diagram of the second-harmonic field.

Optimization of highly efficient terahertz generation in lithium niobate driven by Ti:sapphire laser pulses with 30 fs pulse duration

We systematically study the optimization of highly efficient terahertz（THz） generation in lithium niobate（LN）crystal pumped by 800 nm laser pulses with 30 fs pulse duration. At room temperature, we obtain a record optical-to-THz energy conversion efficiency of 0.43% by chirping the pump laser pulses. Our method provides a new technique for producing millijoule THz radiation in LN via optical rectification driven by joule-level Ti：sapphire laser systems, which deliver sub-50-fs pulse durations.

Novel Image Encryption and Compression Scheme for IoT Environment

Latest advancements made in the processing abilities of smartdevices have resulted in the designing of Intelligent Internet of Things (IoT)environment. This advanced environment enables the nodes to connect, collect, perceive, and examine useful data from its surroundings. Wireless Multimedia Surveillance Networks (WMSNs) form a vital part in IoT-assistedenvironment since it contains visual sensors that examine the surroundingsfrom a number of overlapping views by capturing the images incessantly.Since IoT devices generate a massive quantity of digital media, it is thereforerequired to save the media, especially images, in a secure way. In order toachieve security, encryption techniques as well as compression techniques areemployed to reduce the amount of digital data, being communicated overthe network. Encryption Then Compression (ETC) techniques pave a wayfor secure and compact transmission of the available data to prevent unauthorized access. With this background, the current research paper presentsa new ETC technique to accomplish image security in IoT environment.The proposed model involves three major processes namely, IoT-based imageacquisition, encryption, and compression. The presented model involves optimal Signcryption Technique with Whale Optimization Algorithm (NMWOA)abbreviated as ST-NMWOA. The optimal key generation of signcryptiontechnique takes place with the help of NMWOA. Besides, the presented modelalso uses Discrete Fourier Transform (DFT) and Matrix Minimization (MM)algorithm-based compression technique. Extensive set of experimental analysis was conducted to validate the effective performance of the proposed model.The obtained values infer that the presented model is superior in terms of bothcompression efficiency and data secrecy in resource-limited IoT environment.

An Identity-Based Secure and Optimal Authentication Scheme for the Cloud Computing Environment

Security is a critical issue in cloud computing(CC)because attackers can fabricate data by creating,copying,or deleting data with no user authorization.Most of the existing techniques make use of password-based authentication for encrypting data.Password-based schemes suffer from several issues and can be easily compromised.This paper presents a new concept of hybrid metaheuristic optimization as an identity-based secure and optimal authentication(HMO-ISOA)scheme for CC environments.The HMOISOA technique makes use of iris and fingerprint biometrics.Initially,the HMO-ISOA technique involves a directional local ternary quantized extrema pattern–based feature extraction process to extract features from the iris and fingerprint.Next,the features are fed into the hybrid social spider using the dragon fly algorithm to determine the optimal solution.This optimal solution acts as a key for an advanced encryption standard to encrypt and decrypt the data.A central benefit of determining the optimal value in this way is that the intruder cannot determine this value.The attacker also cannot work out which specific part of the fingerprint and iris feature values are acted upon as a key for the AES technique.Finally,the encrypted data can be saved in the cloud using a cloud simulator.Experimental analysis was performed on five fingerprint and iris images for a man-in-the-middle attack.The simulation outcome validated that the presented HMO-ISOA model achieved better results compared with other existing methods.

Energy Management System Design and Testing for Smart Buildings Under Uncertain Generation (Wind/Photovoltaic) and Demand

This study provides details of the energy management architecture used in the Goldwind microgrid test bed. A complete mathematical model, including all constraints and objectives, for microgrid operational management is first described using a modified prediction interval scheme. Forecasting results are then achieved every 10 min using the modified fuzzy prediction interval model, which is trained by particle swarm optimization.A scenario set is also generated using an unserved power profile and coverage grades of forecasting to compare the feasibility of the proposed method with that of the deterministic approach. The worst case operating points are achieved by the scenario with the maximum transaction cost. In summary, selection of the maximum transaction operating point from all the scenarios provides a cushion against uncertainties in renewable generation and load demand.

Real-time AGC dispatch units considering wind power and ramping capacity of thermal units

The high penetration of wind energy sources in power systems has substantially increased the demand for faster-ramping thermal units participating in the frequency regulation service.To fulfill the automatic generation control(AGC)and compensate the influence of wind power fluctuations simultaneously,ramping capacity should be considered in the dispatch model of thermals.Meanwhile,conventional methods in this area do not take the impact of transmission loss into the dispatch model,or rely on offline network model and parameters,failing to reflect the real relationships between the wind farms and thermal generators.This paper proposes an online approach for AGC dispatch units considering the above issues.Firstly,the power loss sensitivity is online identified using recursive least square method based on the real-time data of phasor measurement units.It sets up power balance constraint and results in a more accurate dispatch model.Then,an improved multi-objective optimization model of dispatch is proposed and a connection is established between the thermal units with fast ramping capacity and the wind farms with rapid fluctuations.Genetic algorithm is used to solve the dispatch model.The proposed method is compared with conventional methods in simulation case in the IEEE 30-bus system.Finally,simulation results verify the validity and the feasibility of identification method and optimization model.