Artificial Circulation System Algorithm:A Novel Bio-Inspired Algorithm

Metaheuristics are commonly used in various fields,including real-life problem-solving and engineering applications.The present work introduces a novel metaheuristic algorithm named the Artificial Circulatory System Algorithm(ACSA).The control of the circulatory system inspires it and mimics the behavior of hormonal and neural regulators involved in this process.The work initially evaluates the effectiveness of the suggested approach on 16 two-dimensional test functions,identified as classical benchmark functions.The method was subsequently examined by application to 12 CEC 2022 benchmark problems of different complexities.Furthermore,the paper evaluates ACSA in comparison to 64 metaheuristic methods that are derived from different approaches,including evolutionary,human,physics,and swarm-based.Subsequently,a sequence of statistical tests was undertaken to examine the superiority of the suggested algorithm in comparison to the 7 most widely used algorithms in the existing literature.The results show that the ACSA strategy can quickly reach the global optimum,avoid getting trapped in local optima,and effectively maintain a balance between exploration and exploitation.ACSA outperformed 42 algorithms statistically,according to post-hoc tests.It also outperformed 9 algorithms quantitatively.The study concludes that ACSA offers competitive solutions in comparison to popüler methods.

A self-healing strategy with fault-cell reutilization of bio-inspired hardware

The self-healing strategy is a key component in designing the bio-inspired embryonics circuit with the structure of cell arrays. However, the existing self-healing strategies of embryonics circuits mainly focus on permanent faults inside the modules of cells such as the function module and the configuration register, while little attention is paid to transient faults. From the point of view of obtaining high efficiency of hardware utilization, it would be a huge waste of hardware resources by permanent elimination when a cell only suffers a transient fault which can be repaired by a configuration mechanism. A new self-healing strategy, the Fault-Cell Reutilization Self-healing Strategy(FCRSS) which presents a method for reusing transient fault cells, is proposed in this paper. The circuit structures of all the modules in the cells are described in detail. In the new strategy, two processes of elimination and reconfiguration are combined. Within the process of fault-cell elimination, cells with transient faults in the embryonics circuit array could be reused simultaneously to replace the functions of the cells on their left side in the same row. Therefore, transient fault-cells in a transparent state can be reconfigured to realize the fault-cell reutilization. Finally,a circuit simulation, resource consumption, a reliability analysis and a detailed normalization analysis are presented. The FCRSS can improve the hardware utilization rate and system reliability at the expense of a small amount of hardware resources and reconfiguration time. Following the conclusion, the method of determining the optimal self-healing strategy is presented according to the environmental conditions.

Frilled Lizard Optimization: A Novel Bio-Inspired Optimizer for Solving Engineering Applications

This research presents a novel nature-inspired metaheuristic algorithm called Frilled Lizard Optimization(FLO),which emulates the unique hunting behavior of frilled lizards in their natural habitat.FLO draws its inspiration from the sit-and-wait hunting strategy of these lizards.The algorithm’s core principles are meticulously detailed and mathematically structured into two distinct phases:(i)an exploration phase,which mimics the lizard’s sudden attack on its prey,and(ii)an exploitation phase,which simulates the lizard’s retreat to the treetops after feeding.To assess FLO’s efficacy in addressing optimization problems,its performance is rigorously tested on fifty-two standard benchmark functions.These functions include unimodal,high-dimensional multimodal,and fixed-dimensional multimodal functions,as well as the challenging CEC 2017 test suite.FLO’s performance is benchmarked against twelve established metaheuristic algorithms,providing a comprehensive comparative analysis.The simulation results demonstrate that FLO excels in both exploration and exploitation,effectively balancing these two critical aspects throughout the search process.This balanced approach enables FLO to outperform several competing algorithms in numerous test cases.Additionally,FLO is applied to twenty-two constrained optimization problems from the CEC 2011 test suite and four complex engineering design problems,further validating its robustness and versatility in solving real-world optimization challenges.Overall,the study highlights FLO’s superior performance and its potential as a powerful tool for tackling a wide range of optimization problems.

Mechanical Performance of Bio-inspired Bidirectional Corrugated Sandwich Pressure Shell Under External Hydrostatic Pressure

This paper aims to enhance the compression capacity of underwater cylindrical shells by adopting the corrugated sandwich structure of cuttlebone.The cuttlebone suffers uniaxial external compression,while underwater cylindrical shells are in a biaxial compressive stress state.To suit the biaxial compressive stress state,a novel bidirectional corrugated sandwich structure is proposed to improve the bearing capacity of cylindrical shells.The static and buckling analysis for the sandwich shell and the unstiffened cylindrical shell with the same volume-weight ratio are studied by numerical simulation.It is indicated that the proposed sandwich shell can effectively reduce the ratio between circumferential and axial stress from 2 to 1.25 and improve the critical buckling load by about 1.63 times.Numerical simulation shows that optimizing and adjusting the structural parameters could significantly improve the advantage of the sandwich shell.Then,the hydrostatic pressure tests for shell models fabricated by 3D printing are carried out.According to the experimental results,the overall failure position of the sandwich shell is at the center part of the sandwich shell.It has been found the average critical load of the proposed sandwich shell models exceeds two times that of the unstiffened shell models.Hence,the proposed bio-inspired bidirectional corrugated sandwich structure can significantly enhance the pressure resistance capability of cylindrical shells.

Cascaded ELM-Based Joint Frame Synchronization and Channel Estimation over Rician Fading Channel with Hardware Imperfections

Due to the interdependency of frame synchronization(FS)and channel estimation(CE),joint FS and CE(JFSCE)schemes are proposed to enhance their functionalities and therefore boost the overall performance of wireless communication systems.Although traditional JFSCE schemes alleviate the influence between FS and CE,they show deficiencies in dealing with hardware imperfection(HI)and deterministic line-of-sight(LOS)path.To tackle this challenge,we proposed a cascaded ELM-based JFSCE to alleviate the influence of HI in the scenario of the Rician fading channel.Specifically,the conventional JFSCE method is first employed to extract the initial features,and thus forms the non-Neural Network(NN)solutions for FS and CE,respectively.Then,the ELMbased networks,named FS-NET and CE-NET,are cascaded to capture the NN solutions of FS and CE.Simulation and analysis results show that,compared with the conventional JFSCE methods,the proposed cascaded ELM-based JFSCE significantly reduces the error probability of FS and the normalized mean square error(NMSE)of CE,even against the impacts of parameter variations.

Enhancing Cancer Classification through a Hybrid Bio-Inspired Evolutionary Algorithm for Biomarker Gene Selection

In this study,our aim is to address the problem of gene selection by proposing a hybrid bio-inspired evolutionary algorithm that combines Grey Wolf Optimization(GWO)with Harris Hawks Optimization(HHO)for feature selection.Themotivation for utilizingGWOandHHOstems fromtheir bio-inspired nature and their demonstrated success in optimization problems.We aimto leverage the strengths of these algorithms to enhance the effectiveness of feature selection in microarray-based cancer classification.We selected leave-one-out cross-validation(LOOCV)to evaluate the performance of both two widely used classifiers,k-nearest neighbors(KNN)and support vector machine(SVM),on high-dimensional cancer microarray data.The proposed method is extensively tested on six publicly available cancer microarray datasets,and a comprehensive comparison with recently published methods is conducted.Our hybrid algorithm demonstrates its effectiveness in improving classification performance,Surpassing alternative approaches in terms of precision.The outcomes confirm the capability of our method to substantially improve both the precision and efficiency of cancer classification,thereby advancing the development ofmore efficient treatment strategies.The proposed hybridmethod offers a promising solution to the gene selection problem in microarray-based cancer classification.It improves the accuracy and efficiency of cancer diagnosis and treatment,and its superior performance compared to other methods highlights its potential applicability in realworld cancer classification tasks.By harnessing the complementary search mechanisms of GWO and HHO,we leverage their bio-inspired behavior to identify informative genes relevant to cancer diagnosis and treatment.

Bio-Inspired Screwed Conduits from the Microfluidic Rope-Coiling Effect for Microvessels and Bronchioles

Tubular microfibers have recently attracted extensive interest for applications in tissue engineering.However,the fabrication of tubular fibers with intricate hierarchical structures remains a major challenge.Here,we present a novel one-step microfluidic spinning method to generate bio-inspired screwed conduits(BSCs).Based on the microfluidic rope-coiling effect,a viscous hydrogel precursor is first curved into a helix stream in the channel,and then consecutively packed as a hollow structured stream and gelated into a screwed conduit(SC)via ionic and covalent crosslinking.By taking advantage of the excellent fluid-controlling ability of microfluidics,various tubes with diverse structures are fabricated via simple control over fluid velocities and multiple microfluidic device designs.The perfusability and permeability results,as well as the encapsulation and culture of human umbilical vein endothelial cells(HUVECs),human pulmonary alveolar epithelial cells(HPAs),and myogenic cells(C2C12),demonstrate that these SCs have good perfusability and permeability and the ability to induce the formation of functional biostructures.These features support the uniqueness and potential applications of these BSCs as biomimetic blood vessels and bronchiole tissues in combination with tissue microstructures,with likely application possibilities in biomedical engineering.

A Novel Quantization and Model Compression Approach for Hardware Accelerators in Edge Computing

Massive computational complexity and memory requirement of artificial intelligence models impede their deploy-ability on edge computing devices of the Internet of Things(IoT).While Power-of-Two(PoT)quantization is pro-posed to improve the efficiency for edge inference of Deep Neural Networks(DNNs),existing PoT schemes require a huge amount of bit-wise manipulation and have large memory overhead,and their efficiency is bounded by the bottleneck of computation latency and memory footprint.To tackle this challenge,we present an efficient inference approach on the basis of PoT quantization and model compression.An integer-only scalar PoT quantization(IOS-PoT)is designed jointly with a distribution loss regularizer,wherein the regularizer minimizes quantization errors and training disturbances.Additionally,two-stage model compression is developed to effectively reduce memory requirement,and alleviate bandwidth usage in communications of networked heterogenous learning systems.The product look-up table(P-LUT)inference scheme is leveraged to replace bit-shifting with only indexing and addition operations for achieving low-latency computation and implementing efficient edge accelerators.Finally,comprehensive experiments on Residual Networks(ResNets)and efficient architectures with Canadian Institute for Advanced Research(CIFAR),ImageNet,and Real-world Affective Faces Database(RAF-DB)datasets,indicate that our approach achieves 2×∼10×improvement in the reduction of both weight size and computation cost in comparison to state-of-the-art methods.A P-LUT accelerator prototype is implemented on the Xilinx KV260 Field Programmable Gate Array(FPGA)platform for accelerating convolution operations,with performance results showing that P-LUT reduces memory footprint by 1.45×,achieves more than 3×power efficiency and 2×resource efficiency,compared to the conventional bit-shifting scheme.

Integration of bio-inspired limb-like structure damping into motor suspension of high-speed trains to enhance bogie hunting stability

Hunting stability is an important performance criterion in railway vehicles.This study proposes an incorporation of a bio-inspired limb-like structure(LLS)-based nonlinear damping into the motor suspension system for traction units to improve the nonlinear critical speed and hunting stability of high-speed trains(HSTs).Initially,a vibration transmission analysis is conducted on a HST vehicle and a metro vehicle that suffered from hunting motion to explore the effect of different motor suspension systems from on-track tests.Subsequently,a simplified lateral dynamics model of an HST bogie is established to investigate the influence of the motor suspension on the bogie hunting behavior.The bifurcation analysis is applied to optimize the motor suspension parameters for high critical speed.Then,the nonlinear damping of the bio-inspired LLS,which has a positive correlation with the relative displacement,can further improve the modal damping of hunting motion and nonlinear critical speed compared with the linear motor suspension system.Furthermore,a comprehensive numerical model of a high-speed train,considering all nonlinearities,is established to investigate the influence of different types of motor suspension.The simulation results are well consistent with the theoretical analysis.The benefits of employing nonlinear damping of the bio-inspired LLS into the motor suspension of HSTs to enhance bogie hunting stability are thoroughly validated.

Energy Efficiency Maximization for Cooperative NOMA with Hardware Impairments

The massive connectivity and limited energy pose significant challenges to deploy the enormous devices in energy-efficient and environmentally friendly in the Internet of Things(IoT).Motivated by these challenges,this paper investigates the energy efficiency(EE)maximization problem for downlink cooperative non-orthogonal multiple access(C-NOMA)systems with hardware impairments(HIs).The base station(BS)communicates with several users via a half-duplex(HD)amplified-and-forward(AF)relay.First,we formulate the EE maximization problem of the system under HIs by jointly optimizing transmit power and power allocated coefficient(PAC)at BS,and transmit power at the relay.The original EE maximization problem is a non-convex problem,which is challenging to give the optimal solution directly.First,we use fractional programming to convert the EE maximization problem as a series of subtraction form subproblems.Then,variable substitution and block coordinate descent(BCD)method are used to handle the sub-problems.Next,a resource allocation algorithm is proposed to maximize the EE of the systems.Finally,simulation results show that the proposed algorithm outperforms the downlink cooperative orthogonal multiple access(C-OMA)scheme.

V2I Physical Layer Security Beamforming with Antenna Hardware Impairments under RIS Assistance

The Internet of Vehicles(IoV)will carry a large amount of security and privacy-related data,which makes the secure communication between the IoV terminals increasingly critical.This paper studies the joint beamforming for physical-layer security transmission in the coexistence of Vehicle-to-Infrastructure(V2I)and Vehicle-toVehicle(V2V)communication with Reconfigurable Intelligent Surface(RIS)assistance,taking into account hardware impairments.A communication model for physical-layer security transmission is established when the eavesdropping user is present and the base station antenna has hardware impairments assisted by RIS.Based on this model,we propose to maximize the V2I physical-layer security transmission rate.To solve the coupled non-convex optimization problem,an alternating optimization algorithm based on second-order cone programming and semidefinite relaxation is proposed to obtain the optimal V2I base station transmit precoding and RIS reflect phase shift matrix.Finally,simulation results are presented to verify the convergence and superiority of our proposed algorithm while analyzing the impact of system parameters on the V2I physical-layer security transmission rate.The simulation results further demonstrate that the proposed robust beamforming algorithm considering hardware impairments will achieve an average performance improvement of 0.7 dB over a non-robustly designed algorithm.Furthermore,increasing the number of RIS reflective units from 10 to 50 results in an almost 2 dB enhancement in secure transmission rate.

Laser Powder Bed Fusion of Multifunctional Bio-inspired Vertical Honeycomb Sandwich Structures:For the Application of Lightweight Bipolar Plates of Proton Exchange Membrane Fuel Cells

The bipolar plate(BPP)is a crucial component of proton exchange membrane fuel cells(PEMFC).However,the weight of BPPs can account for around 80%of a PEMFC stack,posing a hindrance to the commercialization of PEMFCs.Therefore,the lightweight design of BPPs should be considered as a priority.Honeycomb sandwich structures meet some requirements for bipolar plates,such as high mechanical strength and lightweight.Animals and plants in nature provide many excellent structures with characteristics such as low density and high energy absorption capacity.In this work,inspired by the microstructures of the Cybister elytra,a novel bio-inspired vertical honeycomb sandwich(BVHS)structure was designed and manufactured by laser powder bed fusion(LPBF)for the application of lightweight BPPs.Compared with the conventional vertical honeycomb sandwich(CVHS)structure formed by LPBF under the same process parameters setting,the introduction of fractal thin walls enabled self-supporting and thus improved LPBF formability.In addition,the BVHS structure exhibited superior energy absorption(EA)capability and bending properties.It is worth noting that,compared with the CVHS structure,the specific energy absorption(SEA)and specific bending strength of the BVHS structure increased by 56.99%and 46.91%,respectively.Finite element analysis(FEA)was employed to study stress distributions in structures during bending and analyze the influence mechanism of the fractal feature on the mechanical properties of BVHS structures.The electrical conductivity of structures were also studied in this work,the BVHS structures were slightly lower than the CVHS structure.FEA was also conducted to analyze the current flow direction and current density distribution of BVHS structures under a constant voltage,illustrating the influence mechanism of fractal angles on electrical conductivity properties.Finally,in order to solve the problem of trapped powder inside the enclosed unit cells,a droplet-shaped powder outlet was designed for LPBF-processed components.The number of powder outlets was optimized based on bending properties.Results of this work could provide guidelines for the design of lightweight BPPs with high mechanical strength and high electrical conductivity.

A High Efficiency Hardware Implementation of S-Boxes Based on Composite Field for Advanced Encryption Standard

The SubBytes (S-box) transformation is the most crucial operation in the AES algorithm, significantly impacting the implementation performance of AES chips. To design a high-performance S-box, a segmented optimization implementation of the S-box is proposed based on the composite field inverse operation in this paper. This proposed S-box implementation is modeled using Verilog language and synthesized using Design Complier software under the premise of ensuring the correctness of the simulation result. The synthesis results show that, compared to several current S-box implementation schemes, the proposed implementation of the S-box significantly reduces the area overhead and critical path delay, then gets higher hardware efficiency. This provides strong support for realizing efficient and compact S-box ASIC designs.

BIO-INSPIRED SELF-ADAPTIVE MANUFACTURING SYSTEM CONTROL ARCHITECTURE

Future manufacturing systems need to cope with frequent changes and disturbances, therefore their control architectures require constant adaptability, agility, stability, self-organization, intelligence, and robustness. Bio-inspired manufacturing system can well satisfy these requirements. For this purpose, by referencing the biological organization structure and the mechanism, a bio-inspired manufacturing cell is presented from a novel view, and then a bio-inspired self-adaptive manufacturing model is established based on the ultra-short feedback mechanism of the neuro-endocrine system. A hio-inspired self-adaptive manufacturing system coordinated model is also established based on the neuro-endocrine-immunity system （NEIS）. Finally, an example based on pheromone communication mechanism indicates that the robustness of the whole manufacturing system is improved by bio-inspired technologies.

HARDWARE DEMODULATION METHOD FOR &D EDGEDETEOTION AND ERROR OOMPENSATION

A hardwale demodulation method for 2-D edge detection is proposed. The filtering step and the differential step are implemented by using the hardware circuit. This demodulation circuit simplifies the edgefinder and reduces the measuring cycle. The calibration method of scale setting is also presented,and bymeasuring some calibrated objects,the demodulation errors and the error correction table is obtained.

Campus Information Network Hardware System Design

The emphasis of constructing and developing the campus information network is how to design and optimize the network hardware system. This paper mainly studies the network system structure design, the server system structure design and the network export design, and discusses the network hardware system design and optimization for different scale universities according to different practical demand. The objective is that the network hardware system can meet the demand and have been made full use.

Formation Control for Water-Jet USV Based on Bio-Inspired Method

The formation control problem for underactuated unmanned surface vehicles(USVs) is addressed by a distributed strategy based on virtual leader strategy. The control system takes account of disturbance induced by external environment. With the coordinate transformation, the advantage of the proposed scheme is that the control point can be any point of the ship instead of the center of gravity. By introducing bio-inspired model, the formation control problem is addressed with backstepping method. This avoids complicated computation, simplifies the control law,and smoothes the input signals. The system uniform ultimate boundness is proven by Lyapunov stability theory with Young inequality. Simulation results are presented to verify the effectiveness and robust of the proposed controller.

Spinal fusion-hardware construct: Basic concepts and imaging review

The interpretation of spinal images fixed with metallic hardware forms an increasing bulk of daily practice in a busy imaging department. Radiologists are required to be familiar with the instrumentation and operative options used in spinal fixation and fusion procedures, especially in his or her institute. This is critical in evaluating the position of implants and potential complications associated with the operative approaches and spinal fixation devices used. Thus, the radiologist can play an important role in patient care and outcome. This review outlines the advantages and disadvantages of commonly used imaging methods and reports on the best yield for each modality and how to overcome the problematic issues associated with the presence of metallic hardware during imaging. Baseline radiographs are essential as they are the baseline point for evaluation of future studies should patients develop symptoms suggesting possible complications. They may justify further imaging workup with computed tomography, magnetic resonance and/or nuclear medicine studies as the evaluation of a patient with a spinal implant involves a multi-modality approach. This review describes imaging features of potential complications associated with spinal fusion surgery as well as the instrumentation used. This basic knowledge aims to help radiologists approach everyday practice in clinical imaging.

Nanoscale All-Oxide-Heterostructured Bio-inspired Optoresponsive Nociceptor

Retina nociceptor,as a key sensory receptor,not only enables the transport of warning signals to the human central nervous system upon its exposure to noxious stimuli,but also triggers the motor response that minimizes potential sensitization.In this study,the capability of two-dimensional all-oxide-heterostructured artificial nociceptor as a single device with tunable properties was confirmed.Newly designed nociceptors utilize ultra-thin sub-stoichiometric TiO2–Ga2O3 heterostructures,where the thermally annealed Ga2O3 films play the role of charge transfer controlling component.It is discovered that the phase transformation in Ga2O3 is accompanied by substantial jump in conductivity,induced by thermally assisted internal redox reaction of Ga2O3 nanostructure during annealing.It is also experimentally confirmed that the charge transfer in alloxide heterostructures can be tuned and controlled by the heterointerfaces manipulation.Results demonstrate that the engineering of heterointerfaces of two-dimensional(2D)films enables the fabrication of either high-sensitive TiO2–Ga2O3(Ar)or high-threshold TiO2–Ga2O3(N2)nociceptors.The hypersensitive nociceptor mimics the functionalities of corneal nociceptors of human eye,whereas the delayed reaction of nociceptor is similar to high-threshold nociceptive characteristics of human sensory system.The long-term stability of 2D nociceptors demonstrates the capability of heterointerfaces engineering for e ective control of charge transfer at 2D heterostructured devices.

Influence of bio-inspired flow channel designs on the performance of a PEM fuel cell

Performance of the proton exchange membrane fuel cell(PEMFC)is appreciably affected by the channel geometry.The branching structure of a plant leaf and human lung is an efficient network to distribute the nutrients in the respective systems.The same nutrient transport system can be mimicked in the flow channel design of a PEMFC,to aid even reactant distribution and better water management.In this work,the effect of bio-inspired flow field designs such as lung and leaf channel design bipolar plates,on the performance of a PEMFC was examined experimentally at various operating conditions.A PEMFC of 49 cm2 area,with a Nafion 212 membrane with a 40%catalyst loading of 0.4 mg·cm-2 on the anode side and also 0.6 mg·cm-2 on the cathode side is assembled by incorporating the bio-inspired channel bipolar plate,and was tested on a programmable fuel-cell test station.The impact of the working parameters like reactants’relative humidity(RH),back pressure and fuel cell temperature on the performance of the fuel cell was examined;the operating pressure remains constant at 0.1 MPa.It was observed that the best performance was attained at a back pressure of 0.3 MPa,75°C operating temperature and 100%RH.The three flow channels were also compared at different operating pressures ranging from 0.1 MPa to 0.3 MPa,and the other parameters such as operating temperature,RH and back pressure were set as 75°C,100%and 0.3 MPa.The experimental outcomes of the PEMFC with bio-inspired channels were compared with the experimental results of a conventional triple serpentine flow field.It was observed that among the different flow channel designs considered,the leaf channel design gives the best output in terms of power density.Further,the experimental results of the leaf channel design were compared with those of the interdigitated leaf channel design.The PEMFC with the interdigitated leaf channel design was found to generate 6.72%more power density than the non-interdigitated leaf channel design.The fuel cell with interdigitated leaf channel design generated5.58%more net power density than the fuel cell with non-interdigitated leaf channel design after considering the parasitic losses.