A Review of Hybrid Cyber Threats Modelling and Detection Using Artificial Intelligence in IIoT

The Industrial Internet of Things(IIoT)has brought numerous benefits,such as improved efficiency,smart analytics,and increased automation.However,it also exposes connected devices,users,applications,and data generated to cyber security threats that need to be addressed.This work investigates hybrid cyber threats(HCTs),which are now working on an entirely new level with the increasingly adopted IIoT.This work focuses on emerging methods to model,detect,and defend against hybrid cyber attacks using machine learning(ML)techniques.Specifically,a novel ML-based HCT modelling and analysis framework was proposed,in which L1 regularisation and Random Forest were used to cluster features and analyse the importance and impact of each feature in both individual threats and HCTs.A grey relation analysis-based model was employed to construct the correlation between IIoT components and different threats.

Oxygen functionalization-assisted anionic exchange toward unique construction of flower-like transition metal chalcogenide embedded carbon fabric for ultra-long life flexible energy storage and conversion

The metal-organic framework(MOF)derived Ni–Co–C–N composite alloys(NiCCZ)were“embedded”inside the carbon cloth(CC)strands as opposed to the popular idea of growing them upward to realize ultrastable energy storage and conversion application.The NiCCZ was then oxygen functionalized,facilitating the next step of stoichiometric sulfur anion diffusion during hydrothermal sulfurization,generating a flower-like metal hydroxysulfide structure(NiCCZOS)with strong partial implantation inside CC.Thus obtained NiCCZOS shows an excellent capacity when tested as a supercapacitor electrode in a three-electrode configuration.Moreover,when paired with the biomass-derived nitrogen-rich activated carbon,the asymmetric supercapacitor device shows almost 100%capacity retention even after 45,000 charge–discharge cycles with remarkable energy density(59.4 Wh kg^(-1)/263.8μWh cm^(–2))owing to a uniquely designed cathode.Furthermore,the same electrode performed as an excellent bifunctional water-splitting electrocatalyst with an overpotential of 271 mV for oxygen evolution reaction(OER)and 168.4 mV for hydrogen evolution reaction(HER)at 10 mA cm−2 current density along with 30 h of unhinged chronopotentiometric stability performance for both HER and OER.Hence,a unique metal chalcogenide composite electrode/substrate configuration has been proposed as a highly stable electrode material for flexible energy storage and conversion applications.

Design of Human Adaptive Mechatronics Controller for Upper Limb Motion Intention Prediction

Human Adaptive Mechatronics(HAM)includes human and computer system in a closed loop.Elderly person with disabilities,normally carry out their daily routines with some assistance to move their limbs.With the short fall of human care takers,mechatronics devices are used with the likes of exoskeleton and exosuits to assist them.The rehabilitation and occupational therapy equipments utilize the electromyography(EMG)signals to measure the muscle activity potential.This paper focuses on optimizing the HAM model in prediction of intended motion of upper limb with high accuracy and to increase the response time of the system.Limb characteristics extraction from EMG signal and prediction of optimal controller parameters are modeled.Time and frequency based approach of EMG signal are considered for feature extraction.The models used for estimating motion and muscle parameters from EMG signal for carrying out limb movement predictions are validated.Based on the extracted features,optimal parameters are selected by Modified Lion Optimization(MLO)for controlling the HAM system.Finally,supervised machine learning makes predictions at different points in time for individual sensing using Support Vector Neural Network(SVNN).This model is also evaluated based on optimal parameters of motion estimation and the accuracy level along with different optimization models for various upper limb movements.The proposed model of human adaptive controller predicts the limb movement by 96%accuracy.

Diffusion Equations of the Electric Charges and Magnetic Flux

Innovative definitions of the electric and magnetic diffusivities through conducting mediums and innovative diffusion equations of the electric charges and magnetic flux are verified in this article. Such innovations depend on the analogy of the governing laws of diffusion of the thermal, electrical, and magnetic energies and newly defined natures of the electric charges and magnetic flux as energy, or as electromagnetic waves, that have electric and magnetic potentials. The introduced diffusion equations of the electric charges and magnetic flux involve Laplacian operator and the introduced diffusivities. Both equations are applied to determine the electric and magnetic fields in conductors as the heat diffusion equation which is applied to determine the thermal field in steady and unsteady heat diffusion conditions. The use of electric networks for experimental modeling of thermal networks represents sufficient proof of similarity of the diffusion equations of both fields. By analysis of the diffusion phenomena of the three considered modes of energy transfer;the rates of flow of these energies are found to be directly proportional to the gradient of their volumetric concentration, or density, and the proportionality constants in such relations are the diffusivity of each energy. Such analysis leads also to find proportionality relations between the potentials of such energies and their volumetric concentrations. Validity of the introduced diffusion equations is verified by correspondence their solutions to the measurement results of the electric and magnetic fields in microwave ovens.

A review:On path planning strategies for navigation of mobile robot

This paper presents the rigorous study of mobile robot navigation techniques used so far.The step by step investigations of classical and reactive approaches are made here to understand the development of path planning strategies in various environmental conditions and to identify research gap.The classical approaches such as cell decomposition(CD),roadmap approach(RA),artificial potential field(APF);reactive approaches such as genetic algorithm(GA),fuzzy logic(FL),neural network(NN),firefly algorithm(FA),particle swarm optimization(PSO),ant colony optimization(ACO),bacterial foraging optimization(BFO),artificial bee colony(ABC),cuckoo search(CS),shuffled frog leaping algorithm(SFLA)and other miscellaneous algorithms(OMA)are considered for study.The navigation over static and dynamic condition is analyzed(for single and multiple robot systems)and it has been observed that the reactive approaches are more robust and perform well in all terrain when compared to classical approaches.It is also observed that the reactive approaches are used to improve the performance of the classical approaches as a hybrid algorithm.Hence,reactive approaches are more popular and widely used for path planning of mobile robot.The paper concludes with tabular data and charts comparing the frequency of individual navigational strategies which can be used for specific application in robotics.

Thermal deformation of aluminum alloy casting materials for tire mold by numerical analysis

Thermal deformation of aluminum alloy casting materials for manufacturing the tire mold was numerically investigated.The AC7A and AC4C casting material was selected as casting material and the metal casting device was used in order to manufacture the mold product of automobile tire in the actual industrial field.The temperature distribution and the cooling time of casting materials were numerically calculated by finite element analysis (FEA).Also,the thermal deformation such as displacement and stress distribution was calculated from the temperature results.The thermal deformation was closely related to the temperature difference between the surface and inside of the casting.The numerical analysis results reveal that the thermal deformation of AC7A casting material is higher than that of AC4C casting material.Also,the thermal deformation results at the central part are larger than that on the side of casting because of the shrinkage caused by the cooling speed difference.

Role of friction stir welding parameters on tensile strength of AA6061-B_4C composite joints

Friction stir welding（FSW） is a solid state joining technique developed to join high strength aluminum alloys and various ceramic reinforced metal matrix composites（MMCs）.FSW produces sound welds in MMCs without any deleterious reaction between reinforcement and matrix.The present work focused on the effect of FSW parameters on the tensile strength of Al-B4C composite joints.The central composite design of four factors and five levels was used to control the number of experiments.A mathematical model was developed to analyze the influence of FSW parameters.The results indicated that the joint fabricated using rotational speed of 1000 r/min,welding speed of 1.3 mm/s,axial force of 10 kN and the reinforcement of 12% showed larger tensile strength compared with the other joints.The developed model was optimized to maximize the tensile strength using generalized reduced gradient method.The metallographic analysis of the joints showed the presence of various zones such as weld nugget（WN） zone,thermo mechanically affected zone（TMAZ） and heat affected zone（HAZ）.The substantial grain refinement of aluminum matrix as well as significant size reduction of B4C particles was observed in the weld nugget.TMAZ was plastically deformed,thermally affected and exhibited elongated aluminum grains.

Kriging Surrogate-Based Genetic Algorithm Optimization for Blade Design of a Horizontal Axis Wind Turbine

Horizontal axis wind turbines are some of the most widely used clean energy generators in the world.Horizontal axis wind turbine blades need to be designed for optimization in order to maximize efficiency and simultaneously minimize the cost of energy.This work presents the optimization of new MEXICO blades for a horizontal axis wind turbine at the wind speed of 10 m/s.The optimization problem is posed to maximize the power coefficient while the design variables are twist angles on the blade radius and rotating axis positions on a chord length of the airfoils.Computational fluid dynamics was used for the aerodynamic simulation.Surrogate-assisted optimization was applied to reduce computational time.A surrogate model called a Kriging model,using a Gaussian correlation function along with various regression models,was applied while a genetic algorithm was used as an optimizer.The results obtained in this study are discussed and compared with those obtained from the original model.It was found that the Kriging model with linear regression gives better results than the Kriging model with second-order polynomial regression.The optimum blade obtained in this study showed better performance than the original blade at a low wind speed of 10 m/s.

Measurement on Morphology and Kinematics of Crucian Vertebral Joints

In order to provide data for joints control of our recently designed crucian hke biomlmetlc robot fish, an A-ray photograph technology was adopted to determine the number and length of vertebral joints. A frame-by-frame analysis of high-speed videotapes was conducted to quantify the kinematics of crucian at four speeds （12.651 cm·s^-1, 18.201 cm·s^-1, 21.901 cm·s^-1, 24.368cm·s^-1） during cruising. In addition to a brief introduction to experimental conditions and methods, we analyzed the influence of individual diversity on the absolute length as well as the non-dimensional length of vertebral joints. We also presented the maximal angular velocity and acceleration of vertebral joints under four swimming speeds, and provided the change of relative rotation angle, angular difference, angular velocity and angular acceleration of the rear vertebral joints with time at a certain swimming speed of 12.651 cm·s^-1. At last, we presented the maximal lateral displacement of each mark at that speed. The study found that the influence of individual diversity on the non-dimensional length of vertebral joints is not significant; the maximal angular velocity and acceleration of vertebral joints increase with swimming speed; angular difference, angular velocity and angular acceleration exhibit two maximal values over one period at a certain swimming speed.

Effect of Process Parameters on Tensile Strength of Friction Stir Welded Cast LM6 Aluminium Alloy Joints

This paper reports the effect of friction stir welding （FSW） process parameters on tensile strength of cast LM6 aluminium alloy. Joints were made by using different combinations of tool rotation speed, welding speed and axial force each at four levels. The quality of weld zone was investigated using macrostructure and microstructure analysis. Tensile strength of the joints were evaluated and correlated with the weld zone hardness and microstructure. The joint fabricated using a rotational speed of 900 r/min, a welding speed of 75 mm/min and an axial force of 3 kN showed superior tensile strength compared with other joints. The tensile strength and microhardness of the welded joints for the optimum conditions were 166 MPa and 64.8 Hv respectively.

Nanofluid Applications in Future Automobiles: Comprehensive Review of Existing Data

In recent years fluids containing suspension of nanometer sized particles have been an active area of research due to their enhanced thermo physical properties over the base fluids like water,oil etc.Nanofluids possess immense potential applications to improve heat transfer and energy efficient in several areas including automobile,micro electronics,nuclear,space and power generation.Nowadays most of the researchers are trying to use the nanofluids in automobile for various applications such as coolant,fuel additives,lubricant,shock absorber and refrigerant.The goal of this paper is to create the awareness on the promise of nanofluids and the impact it will have on the future automotive industry.This paper also presents a comprehensive data of nanofluids application in automobile for various aspects.

Effect of cavitation bubble collapse on hydraulic oil temperature

Cavitation bubble collapse has a great influence on the temperature of hydraulic oil. Herein, cone-type throttle valve experiments are carried out to study the thermodynamic processes of cavitation. First, the processes of growth and collapse are analysed, and the relationships between the hydraulic oil temperature and bubble growth and collapse are deduced. The effect of temperature is then considered on the hydraulic oil viscosity and saturated vapour pressure. Additionally, an improved form of the Rayleigh–Plesset equation is developed. The effect of cavitation on the hydraulic oil temperature is experimentally studied and the effects of cavitation bubble collapse in the hydraulic system are summarised. Using the cone-type throttle valve as an example, a method to suppress cavitation is proposed.

Microstructure and mechanical properties of rutile-reinforced AA6061 matrix composites produced via stir casting process

A novel process of fabricating aluminium matrix composites(AMCs)with requisite properties by dispersing rutile particles in the aluminum matrix was studied.A novel bi-stage stir casting method was employed to prepare composites,by varying the mass fractions of the rutile particles as 1%,2%,3%and 4%in AA6061 matrix.The density,tensile strength,hardness and microstructures of composites were investigated.Bi-stage stir casting method engendered AMCs with uniform distribution of the reinforced rutile particles in the AA6061 matrix.This was confirmed by the enhancement of the properties of AMCs over the parent base material.Rutile-reinforced AMCs exhibited higher tensile strength and hardness as compared with unreinforced parent material.The properties of the composites were enhanced with the increase in the mass fraction of the rutile particles.However,beyond 3 wt.%of rutile particles,the tensile strength decreased.The hardness and tensile strength of the AMCs reinforced with 3 wt.%of rutile were improved by 36%and 14%respectively in comparison with those of matrix alone.

Easy calibration method of vision system for in-situ measurement of strain of thin films

An easy calibration method was presented for in-situ measurement of displacement in the order of nanometer during micro-tensile test for thin films by using CCD camera as a sensing device. The calibration of the sensing camera in the system is a central element part to measure displacement in the order of nanometer using images taken with the camera. This was accomplished by modeling the optical projection through the camera lens and relative locations between the object and camera in 3D space. A set of known 3D points on a plane where the film is located on is projected to an image plane as input data. These points, known as a calibration points, are then used to estimate the projection parameters of the camera. In the measurement system of the micro-scale by CCD camera, the calibration data acquisition and one-to-one matching steps between the image and 3D planes need precise data extraction procedures and repetitive user's operation to calibrate the measuring devices. The lack of the robust image feature extraction and easy matching prevent the practical use of these methods. A data selection method was proposed to overcome these limitations and offer an easy and convenient calibration of a vision system that has the CCD camera and the 3D reference plane with calibration marks of circular type on the surface of the plane. The method minimizes the user's intervention such as the fine tuning of illumination system and provides an efficient calibration method of the vision system for in-situ axial displacement measurement of the micro-tensile materials.

Web Tension Regulation of Multispan Roll-to-Roll System using Integrated Active Dancer and Load Cells for Printed Electronics Applications

The mass production of primed electronics can be achieved by roll-to-roll（R2R） printing system, so highly accurate web tension is required that can minimize the register error and keep the thickness and roughness of printed devices in limits. The web tension of a R2R system is regulated by the use of integrated load cells and active dancer system for printed electronics applications using decentralized multi-input-single-output（MISO） regularized variable learning rate backpropagation artificial neural networks. The active dancer system is used before printing system to reduce disturbances in the web tension of process span. The classical PID control result in tension spikes with the change in roll diameter of winder and unwinder rolls. The presence of dancer in R2R system shows that improved web tension control in printing span and the web tension can be enhanced from 3.75 N to 4.75 N. The overshoot of system is less than ±2.5 N and steady state error is within ± 1 N where load cells have a signal noise of ±0.7 N. The integration of load cells and active dancer with self-adapting neural network control provide a solution to the web tension control of multispan roll-to-roll system.

Enhancement of wear resistance of Ti–6Al–4V alloy by picosecond laser surface micro texturing process

A pulsed,picosecond Nd:YAG laser with a wavelength of 532 nm is used to texture the surface of grade 5 titanium alloy(Ti–6Al–4V)for minimizing its wear rate.The wear properties of the base samples and laser surface textured samples are analyzed by conducting wear tests under a sliding condition using pin-on-disk equipment.The wear tests are conducted based on the Box–Benhken design,and the interaction of the process parameters is analyzed using response surface methodology.The wear analysis is conducted by varying the load,rotating speed of the disc,and track diameter at room temperature with a sliding distance of 1500 m.The results demonstrate that the laser textured surfaces exhibited a lower coefficient of friction and good anti-wear properties as compared with the non-textured surfaces.A regression model is developed for the wear analysis of titanium alloy using the analysis of variance technique.It is also observed from the analysis that the applied load and sliding distance are the parameters that have the greatest effect on the wear behavior followed by the wear track diameter.The optimum operating conditions have been suggested based on the results obtained from the numerical optimization approach.

H_∞ control of an overactuated tilt rotors quadcopter

In recent years,unmanned aerial vehicles(UAVs)have acquired an increasing interest due to their wide range of applications in military,scientific,and civilian fields.One of the quadcopter limitations is its lack of full actuation property which limits its mobility and trajectory tracking capabilities.In this work,an overactuated quadcopter design and control,which allows independent tilting of the rotors around their arm axis,is presented.Quadcopter with this added tilting mechanism makes it possible to overcome the aforementioned mobility limitation by achieving full authority on torque and force vectoring.The tilting property increases the control inputs to 8(the 4 propeller rotation speed plus the 4 rotor tilting angles)which gives a full control on the quadcopter states.Extensive mathematical model for the tilt rotor quadcopter is derived based on the Newton-Euler method.Furthermore,the feedback linearization method is used to linearize the model and a mixed sensitivity H∞optimal controller is then designed and synthesized to achieve the required performance and stability.The controlled system is simulated to assure the validity of the proposed controller and the quadcopter design.The controller is tested for its effectiveness in rejecting disturbances,attenuating sensor noise,and coping with the model uncertainties.Moreover,a complicated trajectory is examined in which the tilt rotor quadcopter has been successfully followed.The test results show the supremacy of the overactuated quadcopter over the traditional one.

Synthesis and optimization of high surface area mesoporous date palm fiber-based nanostructured powder activated carbon for aluminum removal

Date palm fiber(DPF)derived from agrowaste was utilized as a new precursor for the optimized synthesis of a costeffective,nanostructured,powderactivated carbon(nPAC)for aluminum(Al3+)removal from aqueous solutions using carbonization,KOH activation,response surface methodology(RSM)and central composite design(CCD).The optimum synthesis condition,activation temperature,time and impregnation ratio were found to be 650℃,1.09 hour and 1:1,respectively.Furthermore,the optimum conditions for removal were 99.5%and 9.958 mgg 1 in regard to uptake capacity.The optimum conditions of nPAC was analyzed and characterized using XRD,FTIR,FESEM,BET,TGA and Zeta potential.Moreover,the adsorption of the Al3+conditions was optimized with an integrated RSMCCD experimental design.Regression results revealed that the adsorption kinetics data was well fitted by the pseudosecond order model,whereas the adsorption isotherm data was best represented by the Freundlich isotherm model.Optimum activated carbon indicated that DPF can serve as a costeffective precursor adsorbent for Al^(3+)removal.

Crushing behavior of lightmass structural member

Carbon fiber reinforced plastic (CFRP) of the advanced composite materials is widely used in lightmass structural materials of air planes, ship and automobiles because of high strength and stiffness. In this study, experimental investigation was performed for each specimen. The square section members consist of aluminum, CFRP and hybrid (aluminum/CFRP) member, and hat-shaped section members consist of CFRP and hybrid (aluminum/CFRP) members specimen. Based on the collapse characteristics of aluminum square section member, the collapse characteristics and energy absorption capability of hat-shaped section members were analyzed. The axial static collapse tests were carried out for each section member. The collapse modes and the energy absorption capability of the members were analyzed. In the lightmass design aspect, the collapse characteristics and energy absorption capability of the members were compared.

Inverse displacement analysis of the general six degree-of-freedom serial robot based on optimization method

The paper presents a new solution of inverse displacement analysis of the general six degree-of-freedom serial robot.The inverse displacement analysis of the general serial robot is transformed into a minimization problem and then the optimization method is adopted to solve the nonlinear least squares problem with the analytic form of new Jacobian matrix.In this way,joint variables of the general serial robot can be searched out quickly under the desired precision when positions of the three non-collinear end effector points are given.Compared with the general Newton iterative method,the proposed algorithm can search out the solution when the robot is at the singular configuration and the initial configuration used in the optimization method may also be the singular configuration.So the convergence domain is bigger than that of the general Newton iterative method.Another advantage of the proposed algorithm is that positions of the three non-collinear end effector points are usually much easier to be measured than the orientation of the end effector.The inverse displacement analysis of the general 6R(six-revolute-joint) serial robot is illustrated as an example and the simulation results verify the efficiency of the proposed algorithm.Because the three non-collinear points can be selected at random,the method can be applied to any other types of serial robots.