A Study on Modular Fixture Design with Intelligent Selection of Elements and Interactive Assembly

Based on the features of the design and assembly of rnodular fixtures, a new design system which combines intelligent selection of elements and interactive assembly is presented.Using the fixture design datum, the system can automatically select elements,and can interactively assemble together these elements based on AutoCAD. An example is given to illustrate it.

Optimization of Wind Turbine Hub Assembly Sequence Based on Intelligent Algorithm

A method for hub assembly sequence planning oriented to the fixed position layout is proposed.An assembly relationship model was constructed to describe the relationship between hub assembly components and workstations,considering the layout of the hub assembly line and process constraints,including the assembly precedence matrix,workstation assembly capability table and criticality table of components.The evaluation mechanism for the assembly sequence was established.Values from the evaluation functions with engineering significance were used to select the optimal assembly sequence from the perspective of assembly time,assembly index and assembly path distance.In function,the criticality of components was introduced into the traditional assemblability index,comparing the multi-objective dragonfly algorithm(MODA)with non-dominated sorting genetic algorithm-Ⅱ(NSGA-Ⅱ)to complete the assembly sequence planning and assignment for workstations.The optimized results show that the presented method is feasible and efficient for solving the hub assembly sequence planning problem.

Intelligent Recognition Using Ultralight Multifunctional Nano‑Layered Carbon Aerogel Sensors with Human‑Like Tactile Perception

Humans can perceive our complex world through multi-sensory fusion.Under limited visual conditions,people can sense a variety of tactile signals to identify objects accurately and rapidly.However,replicating this unique capability in robots remains a significant challenge.Here,we present a new form of ultralight multifunctional tactile nano-layered carbon aerogel sensor that provides pressure,temperature,material recognition and 3D location capabilities,which is combined with multimodal supervised learning algorithms for object recognition.The sensor exhibits human-like pressure(0.04–100 kPa)and temperature(21.5–66.2℃)detection,millisecond response times(11 ms),a pressure sensitivity of 92.22 kPa^(−1)and triboelectric durability of over 6000 cycles.The devised algorithm has universality and can accommodate a range of application scenarios.The tactile system can identify common foods in a kitchen scene with 94.63%accuracy and explore the topographic and geomorphic features of a Mars scene with 100%accuracy.This sensing approach empowers robots with versatile tactile perception to advance future society toward heightened sensing,recognition and intelligence.

Ionic Liquid-Enhanced Assembly of Nanomaterials for Highly Stable Flexible Transparent Electrodes

The controlled assembly of nanomaterials has demon-strated significant potential in advancing technological devices.However,achieving highly efficient and low-loss assembly technique for nanomate-rials,enabling the creation of hierarchical structures with distinctive func-tionalities,remains a formidable challenge.Here,we present a method for nanomaterial assembly enhanced by ionic liquids,which enables the fabrication of highly stable,flexible,and transparent electrodes featuring an organized layered structure.The utilization of hydrophobic and non-volatile ionic liquids facilitates the production of stable interfaces with water,effectively preventing the sedimentation of 1D/2D nanomaterials assembled at the interface.Furthermore,the interfacially assembled nanomaterial monolayer exhibits an alternate self-climbing behavior,enabling layer-by-layer transfer and the formation of a well-ordered MXene-wrapped silver nanowire network film.The resulting composite film not only demonstrates exceptional photoelectric performance with a sheet resistance of 9.4Ωsq^(-1) and 93%transmittance,but also showcases remarkable environmental stability and mechanical flexibility.Particularly noteworthy is its application in transparent electromagnetic interference shielding materials and triboelectric nanogenerator devices.This research introduces an innovative approach to manufacture and tailor functional devices based on ordered nanomaterials.

Cooperative User-Scheduling and Resource Allocation Optimization for Intelligent Reflecting Surface Enhanced LEO Satellite Communication

Lower Earth Orbit(LEO) satellite becomes an important part of complementing terrestrial communication due to its lower orbital altitude and smaller propagation delay than Geostationary satellite. However, the LEO satellite communication system cannot meet the requirements of users when the satellite-terrestrial link is blocked by obstacles. To solve this problem, we introduce Intelligent reflect surface(IRS) for improving the achievable rate of terrestrial users in LEO satellite communication. We investigated joint IRS scheduling, user scheduling, power and bandwidth allocation(JIRPB) optimization algorithm for improving LEO satellite system throughput.The optimization problem of joint user scheduling and resource allocation is formulated as a non-convex optimization problem. To cope with this problem, the nonconvex optimization problem is divided into resource allocation optimization sub-problem and scheduling optimization sub-problem firstly. Second, we optimize the resource allocation sub-problem via alternating direction multiplier method(ADMM) and scheduling sub-problem via Lagrangian dual method repeatedly.Third, we prove that the proposed resource allocation algorithm based ADMM approaches sublinear convergence theoretically. Finally, we demonstrate that the proposed JIRPB optimization algorithm improves the LEO satellite communication system throughput.

Response and assembly of abundant and rare taxa in Zaopei under different combination patterns of Daqu and pit mud:from microbial ecology to Baijiu brewing microecosystem

The quality and aroma of strong-flavor Baijiu are mainly dependent on Daqu,pit mud(PM),and the interaction of both.However,little is known about how their combination patterns affect the microbiome and metabolome of Zaopei,especially the metabolic function of rare taxa.Here,an experiment on industrial size was designed to assess the effects of 6 combinations(3 kinds of Daqu×2 kinds of PM)on the composition and assembly of different taxa,as well as the flavor profile.The results showed that Zaopei's microbiota was composed of a few abundant taxa and enormous rare taxa,and rare bacterial and abundant fungal subcommunities were significantly affected by combination patterns.The assembly processes of abundant/rare taxa and bacterial/fungal communities were distinct,and environmental changes mediated the balance between stochastic and deterministic processes in rare bacteria assembly.Furthermore,specific combination patterns improved the flavor quality of Zaopei by enhancing the interspecies interaction,which was closely related to rare taxa,especially rare bacteria.These findings highlighted that rare bacteria might be the keystone in involving community interaction and maintaining metabolic function,which provided a scientific foundation for better understanding and regulating the brewing microbiota from the viewpoint of microbial ecology.

Design and assembly of a nested imaging X-ray telescope for the Hot Universe Baryon Surveyor mission

The Hot Universe Baryon Surveyor (HUBS) mission will carry a nested X-ray telescope capable of observing an energy range from 0.5 keV to 2 keV to study hot baryon evolution. In this paper, we report the latest progress in the design and construction of nested X-ray telescopes which were designed to use a three-stage conic-approximation type assembly to simplify the manufacturing process. The mirror substrate is made using the thermal glass slumping method, with mirrors characterized by a root-mean-square roughness of 0.3 nm, with expected high reflectivity and good thermal stability. We also discuss methods of telescope construction and conduct a deformation analysis of the manufactured mirror. The in situ measurement system program is developed to guide the telescope assembly process.

Ensuring Secure Platooning of Constrained Intelligent and Connected Vehicles Against Byzantine Attacks:A Distributed MPC Framework

This study investigates resilient platoon control for constrained intelligent and connected vehicles(ICVs)against F-local Byzantine attacks.We introduce a resilient distributed model-predictive platooning control framework for such ICVs.This framework seamlessly integrates the predesigned optimal control with distributed model predictive control(DMPC)optimization and introduces a unique distributed attack detector to ensure the reliability of the transmitted information among vehicles.Notably,our strategy uses previously broadcasted information and a specialized convex set,termed the“resilience set”,to identify unreliable data.This approach significantly eases graph robustness prerequisites,requiring only an(F+1)-robust graph,in contrast to the established mean sequence reduced algorithms,which require a minimum(2F+1)-robust graph.Additionally,we introduce a verification algorithm to restore trust in vehicles under minor attacks,further reducing communication network robustness.Our analysis demonstrates the recursive feasibility of the DMPC optimization.Furthermore,the proposed method achieves exceptional control performance by minimizing the discrepancies between the DMPC control inputs and predesigned platoon control inputs,while ensuring constraint compliance and cybersecurity.Simulation results verify the effectiveness of our theoretical findings.

An Intelligent Identification Approach of Assembly Interface for CAD Models

Kinematic semantics is often an important content of a CAD model(it refers to a single part/solid model in this work)in many applications,but it is usually not the belonging of the model,especially for the one retrieved from a common database.Especially,the effective and automatic method to reconstruct the above information for a CAD model is still rare.To address this issue,this paper proposes a smart approach to identify each assembly interface on every CAD model since the assembly interface is the fundamental but key element of reconstructing kinematic semantics.First,as the geometry of an assembly interface is formed by one or more adjacent faces on each model,a face-attributed adjacency graph integrated with face structure fingerprint is proposed.This can describe each CAD model as well as its assembly interfaces uniformly.After that,aided by the above descriptor,an improved graph attention network is developed based on a new dual-level anti-interference filtering mechanism,which makes it have the great potential to identify all representative kinds of assembly interface faces with high accuracy that have various geometric shapes but consistent kinematic semantics.Moreover,based on the abovementioned graph and face-adjacent relationships,each assembly interface on a model can be identified.Finally,experiments on representative CAD models are implemented to verify the effectiveness and characteristics of the proposed approach.The results show that the average assembly-interface-face-identification accuracy of the proposed approach can reach 91.75%,which is about 2%–5%higher than those of the recent-representative graph neural networks.Besides,compared with the state-of-the-art methods,our approach is more suitable to identify the assembly interfaces(with various shapes)for each individual CAD model that has typical kinematic pairs.

Intelligent diagnosis of retinal vein occlusion based on color fundus photographs

AIM:To develop an artificial intelligence(AI)diagnosis model based on deep learning(DL)algorithm to diagnose different types of retinal vein occlusion(RVO)by recognizing color fundus photographs(CFPs).METHODS:Totally 914 CFPs of healthy people and patients with RVO were collected as experimental data sets,and used to train,verify and test the diagnostic model of RVO.All the images were divided into four categories[normal,central retinal vein occlusion(CRVO),branch retinal vein occlusion(BRVO),and macular retinal vein occlusion(MRVO)]by three fundus disease experts.Swin Transformer was used to build the RVO diagnosis model,and different types of RVO diagnosis experiments were conducted.The model’s performance was compared to that of the experts.RESULTS:The accuracy of the model in the diagnosis of normal,CRVO,BRVO,and MRVO reached 1.000,0.978,0.957,and 0.978;the specificity reached 1.000,0.986,0.982,and 0.976;the sensitivity reached 1.000,0.955,0.917,and 1.000;the F1-Sore reached 1.000,0.9550.943,and 0.887 respectively.In addition,the area under curve of normal,CRVO,BRVO,and MRVO diagnosed by the diagnostic model were 1.000,0.900,0.959 and 0.970,respectively.The diagnostic results were highly consistent with those of fundus disease experts,and the diagnostic performance was superior.CONCLUSION:The diagnostic model developed in this study can well diagnose different types of RVO,effectively relieve the work pressure of clinicians,and provide help for the follow-up clinical diagnosis and treatment of RVO patients.

Digital Twin Modeling and Simulation Optimization of Transmission Front and Middle Case Assembly Line

As the take-off of China’s macro economy,as well as the rapid development of infrastructure construction,real estate industry,and highway logistics transportation industry,the demand for heavy vehicles is increasing rapidly,the competition is becoming increasingly fierce,and the digital transformation of the production line is imminent.As one of themost important components of heavy vehicles,the transmission front andmiddle case assembly lines have a high degree of automation,which can be used as a pilot for the digital transformation of production.To ensure the visualization of digital twins(DT),consistent control logic,and real-time data interaction,this paper proposes an experimental digital twin modeling method for the transmission front and middle case assembly line.Firstly,theDT-based systemarchitecture is designed,and theDT model is created by constructing the visualization model,logic model,and data model of the assembly line.Then,a simulation experiment is carried out in a virtual space to analyze the existing problems in the current assembly line.Eventually,some improvement strategies are proposed and the effectiveness is verified by a new simulation experiment.

Introduction to the Special Issue on Machine Learning-Guided Intelligent Modeling with Its Industrial Applications

With the advancement of Artificial Intelligence(AI)technology,traditional industrial systems are undergoing an intelligent transformation,bringing together advanced computing,communication and control technologies,Machine Learning(ML)-based intelligentmodelling has become a newparadigm for solving problems in the industrial domain[1–3].With numerous applications and diverse data types in the industrial domain,algorithmic and data-driven ML techniques can intelligently learn potential correlations between complex data and make efficient decisions while reducing human intervention.However,in real-world application scenarios,existing algorithms may have a variety of limitations,such as small data volumes,small detection targets,low efficiency,and algorithmic gaps in specific application domains[4].Therefore,many new algorithms and strategies have been proposed to address the challenges in industrial applications[5–8].

Self-assembly of tau fragments as a key pathologic event in tauopathies

Tau protein is encoded by the microtubuleassociated protein tau(MAPT)gene and stabilizes microtubules in the neurons.Tau has unique biophysical properties that make it both highly water-soluble and positively charged.Although tau is an intrinsically disordered protein lacking defined secondary structures,it can acquire highly organized-sheet structures and stack into a filamentous inclusion such as a paired helical filament(PHF).

Vision based intelligent traffic light management system using Faster R‐CNN

Transportation systems primarily depend on vehicular flow on roads. Developed coun-tries have shifted towards automated signal control, which manages and updates signal synchronisation automatically. In contrast, traffic in underdeveloped countries is mainly governed by manual traffic light systems. These existing manual systems lead to numerous issues, wasting substantial resources such as time, energy, and fuel, as they cannot make real‐time decisions. In this work, we propose an algorithm to determine traffic signal durations based on real‐time vehicle density, obtained from live closed circuit television camera feeds adjacent to traffic signals. The algorithm automates the traffic light system, making decisions based on vehicle density and employing Faster R‐CNN for vehicle detection. Additionally, we have created a local dataset from live streams of Punjab Safe City cameras in collaboration with the local police authority. The proposed algorithm achieves a class accuracy of 96.6% and a vehicle detection accuracy of 95.7%. Across both day and night modes, our proposed method maintains an average precision, recall, F1 score, and vehicle detection accuracy of 0.94, 0.98, 0.96 and 0.95, respectively. Our proposed work surpasses all evaluation metrics compared to state‐of‐the‐art methodologies.

Intelligent casting:Empowering the future foundry industry

Emerging technological advances are reshaping the casting sector in latest decades.Casting technology is evolving towards intelligent casting paradigm that involves automation,greenization and intelligentization,which attracts more and more attention from the academic and industry communities.In this paper,the main features of casting technology were briefly summarized and forecasted,and the recent developments of key technologies and the innovative efforts made in promoting intelligent casting process were discussed.Moreover,the technical visions of intelligent casting process were also put forward.The key technologies for intelligent casting process comprise 3D printing technologies,intelligent mold technologies and intelligent process control technologies.In future,the intelligent mold that derived from mold with sensors,control devices and actuators will probably incorporate the Internet of Things,online inspection,embedded simulation,decision-making and control system,and other technologies to form intelligent cyber-physical casting system,which may pave the way to realize intelligent casting.It is promising that the intelligent casting process will eventually achieve the goal of real-time process optimization and full-scale control,with the defects,microstructure,performance,and service life of the fabricated castings can be accurately predicted and tailored.

An intelligent prediction model of epidemic characters based on multi-feature

The epidemic characters of Omicron(e.g.large-scale transmission)are significantly different from the initial variants of COVID-19.The data generated by large-scale transmission is important to predict the trend of epidemic characters.However,the re-sults of current prediction models are inaccurate since they are not closely combined with the actual situation of Omicron transmission.In consequence,these inaccurate results have negative impacts on the process of the manufacturing and the service industry,for example,the production of masks and the recovery of the tourism industry.The authors have studied the epidemic characters in two ways,that is,investigation and prediction.First,a large amount of data is collected by utilising the Baidu index and conduct questionnaire survey concerning epidemic characters.Second,theβ-SEIDR model is established,where the population is classified as Susceptible,Exposed,Infected,Dead andβ-Recovered persons,to intelligently predict the epidemic characters of COVID-19.Note thatβ-Recovered persons denote that the Recovered persons may become Sus-ceptible persons with probabilityβ.The simulation results show that the model can accurately predict the epidemic characters.

A telomere-to-telomere genome assembly of Zhonghuang 13,a widely-grown soybean variety from the original center of Glycine max

Soybean(Glycine max)stands as a globally significant agricultural crop,and the comprehensive assembly of its genome is of paramount importance for unraveling its biological characteristics and evolutionary history.Nevertheless,previous soybean genome assemblies have harbored gaps and incompleteness,which have constrained in-depth investigations into soybean.Here,we present Telomere-to-Telomere(T2T)assembly of the Chinese soybean cultivar Zhonghuang 13(ZH13)genome,termed ZH13-T2T,utilizing PacBio Hifi and ONT ultralong reads.We employed a multi-assembler approach,integrating Hifiasm,NextDenovo,and Canu,to minimize biases and enhance assembly accuracy.The assembly spans 1,015,024,879 bp,effectively resolving all 393 gaps that previously plagued the reference genome.Our annotation efforts identified 50,564 high-confidence protein-coding genes,707 of which are novel.ZH13-T2T revealed longer chromosomes,421 not-aligned regions(NARs),112 structure variations(SVs),and a substantial expansion of repetitive element compared to earlier assemblies.Specifically,we identified 25.67 Mb of tandem repeats,an enrichment of 5S and 48S rDNAs,and characterized their genotypic diversity.In summary,we deliver the first complete Chinese soybean cultivar T2T genome.The comprehensive annotation,along with precise centromere and telomere characterization,as well as insights into structural variations,further enhance our understanding of soybean genetics and evolution.

An Improved Chromosome-Level Genome Assembly and Annotation of Belted Beard Grunt(Hapalogenys analis)

Hapalogenys analis(order Lobotiformes)is an economically and ecologically significant fish species.It is a typical sedentary rocky reef fish and is primarily found in the northern Pacific Ocean.Here,we used Hi-C and PacBio sequencing technique to assemble a high-quality,chromosome-level genome for this species.The 539 Mb genome had a contig N50 with a size of 3.43 Mb,while 755 contigs clustered into 24 chromosomal groups with an anchoring rate of 99.02%.Of the total genomic sequence,132.74Mb(24.39%)were annotated as repeat elements.A total of 21360 protein-coding genes were identified,of which 20787 genes(97.32%)were successfully annotated to public databases.The BUSCO evaluation indicated that 96.90%of the total orthologous genes were matched.The phylogenetic tree representing H.analis and 14 other bony fish species indicated that the H.analis genome contained 364 expanded gene families related to olfactory receptor activity,compared with the common ancestor of H.analis and Sciaenidae.Comparative genomic analysis further identified 3584 contracted gene families.Branch-site modeling identified 277 genes experiencing positive selection,which may facilitate the adaptation to rocky reef environments.The genome reported here is helpful for ecological and evolutionary studies of H.analis.

Optimization of Fixture Number in Large Thin-Walled Parts Assembly Based on IPSO

There are lots of researches on fixture layout optimization for large thin-walled parts.Current researches focus on the positioning problem,i.e.,optimizing the positions of a constant number of fixtures.However,how to determine the number of fixtures is ignored.In most cases,the number of fixtures located on large thin-walled parts is determined based on engineering experience,which leads to huge fixture number and extra waste.Therefore,this paper constructs an optimization model to minimize the number of fixtures.The constraints are set in the optimization model to ensure that the part deformation is within the surface profile tolerance.In addition,the assembly gap between two parts is also controlled.To conduct the optimization,this paper develops an improved particle swarm optimization(IPSO)algorithm by integrating the shrinkage factor and adaptive inertia weight.In the algorithm,particles are encoded according to the fixture position.Each dimension of the particle is assigned to a sub-region by constraining the optional position range of each fixture to improve the optimization efficiency.Finally,a case study on ship curved panel assembly is provided to prove that our method can optimize the number of fixtures while meeting the assembly quality requirements.This research proposes a method to optimize the number of fixtures,which can reduce the number of fixtures and achieve deformation control at the same time.

Intelligent Transformation: General Intelligence Theory

This paper aims to formalize a general definition of intelligence beyond human intelligence. We accomplish this by re-imagining the concept of equality as a fundamental abstraction for relation. We discover that the concept of equality = limits the sensitivity of our mathematics to abstract relationships. We propose a new relation principle that does not rely on the concept of equality but is consistent with existing mathematical abstractions. In essence, this paper proposes a conceptual framework for general interaction and argues that this framework is also an abstraction that satisfies the definition of Intelligence. Hence, we define intelligence as a formalization of generality, represented by the abstraction ∆∞Ο, where each symbol represents the concepts infinitesimal, infinite, and finite respectively. In essence, this paper proposes a General Language Model (GLM), where the abstraction ∆∞Ο represents the foundational relationship of the model. This relation is colloquially termed “The theory of everything”.