Three-layer Hybrid Research Articles

A double-layer Q-learning driven memetic algorithm for integrated scheduling of procurement, production and maintenance with distributed resources

The existing research on integrated production scheduling typically focuses on activities related to both production and post-production (e.g., operation and maintenance), with limited consideration for simultaneously integrating pre-production activities (e.g., raw material procurement). However, achieving the equilibrium between the manufacturer and the demander for intelligent manufacturing systems requires the optimal scheduling solution that integrates both pre-production and post-production activities. Inspired by this, we investigate a novel integrated scheduling problem that concurrently considers raw material procurement, production scheduling and equipment maintenance (abbreviated as SIPPM). A mixed-integer linear programming model is developed to simultaneously minimize the total costs for the manufacturer and the demander. Furthermore, a double-layer Q-learning driven memetic algorithm (DQMA) is proposed to solve the SIPPM. In DQMA, a well-tailored three-layer hybrid encoding method is presented for chromosome representation. The global search of DQMA employs three crossover and three mutation operators. Moreover, a knowledge-based local search operator with six methods, guided by an effective double-layer Q-learning structure, is devised to enhance local exploitation capabilities. The superiority of DQMA is verified through comparison with three popular multi-objective optimization algorithms on 108 newly established benchmark instances. The proposed integrated scheduling mode is proven to be more effective than two separated scheduling modes without considering raw material procurement.

Multi-factor integrated configuration model and three-layer hybrid optimization algorithm framework: turnkey project-oriented rapid manufacturing system configuration

Multi-factor integrated configuration model and three-layer hybrid optimization algorithm framework: turnkey project-oriented rapid manufacturing system configuration

Date-Palm-Based Sustainable Hybrid Composite with Cotton and Kevlar Fibre Participation

This research aims to evaluate the physical and mechanical performance of three types of hybrid composites made of date palm (Phoenix dactylifera L.) (DP), additional layers of cotton (DP/C) and Kevlar fibres (DP/K). The fibres were formed into flat sheets and employed as reinforcement layers embedded in a polyester matrix. Three-layer and five-layer hybrid composites were created using the hand layup method. The layers have alternative longitudinal–transversal orientation. The composites were investigated for density, thickness swelling (TS), water absorption (WA), flexural strength and modulus of elasticity (MOE) properties. Moreover, the composites were subjected to cycles of water immersion, freezing and drying, and the changes in mass and mechanical performance were analysed before and after the cyclic testing. The hybrid composite with Kevlar as the inner layers displayed better physical and mechanical properties when compared to the other two hybrid composites. A stereo-microscopic investigation revealed that poor adhesion between the layers of composites contributed to a reduction in the mechanical properties of DP/C and DP hybrid composites. The DP/C composite had the highest thickness swelling and water absorption, with the water uptake more pronounced than in the cases of the other composites. The hybridisation of date palms with Kevlar fibres improved the properties of the hybrid composites.

Multiscale Frozen Density Embedding/Molecular Mechanics Approach for Simulating Magnetic Response Properties of Solvated Systems.

We present a three-layer hybrid quantum mechanical/quantum embedding/molecular mechanics approach for calculating nuclear magnetic resonance (NMR) shieldings and J-couplings of molecular systems in solution. The model is based on the frozen density embedding (FDE) and polarizable fluctuating charges (FQ) and fluctuating dipoles (FQFμ) force fields and permits the accurate ab initio description of short-range nonelectrostatic interactions by means of the FDE shell and cost-effective treatment of long-range electrostatic interactions through the polarizable force field FQ(Fμ). Our approach's accuracy and potential are demonstrated by studying NMR spectra of Brooker's merocyanine in aqueous and nonaqueous solutions.

The Effect Analysis of the Application of CAI to Japanese Oral Teaching in Colleges

Abstract In this paper, we first analyze the requirements for teaching spoken Japanese in colleges and universities, design a computer-assisted teaching system using C/S and three-layer hybrid architecture, and create a business flow diagram of the system. The second step is to conduct a technical analysis of the computer-assisted teaching system, and Bayesian theory is employed to model the complex system with multi-factor synergy. The effect of the computer-assisted system on Japanese-speaking teaching courses in colleges and universities was analyzed. The results indicated that the students dictated 4,500 words, while the lowest dictated as little as 300 words, but overall, they were more balanced. The prompt word ratio was directly proportional to the number of repetitions by observing the number of single dictations of students.

Developing the transboundary Long Term Vision of the Scheldt Estuary – an untold story

ABSTRACT The development of the bilateral Long Term Vision for the Scheldt Estuary between 1999 and 2001 reveals that it is possible to move from a history of conflict to cooperation in just two years. A retrospective, insider perspective is used to analyse the integrated three-layer hybrid modelling at the heart of this groundbreaking agreement. We tell an untold story of the collaborative eco-morphological modelling activity that served as a boundary object supporting communication and contributing to a model-based metaphor of the intrinsic character of the estuary – its most lasting contribution.

Study of Properties and Mechanism of Bonding Line in Three-Layer Hybrid Cross-Laminated Timber

The physical and chemical properties of three kinds of laminations relative to the bonding properties of three-layer hybrid cross-laminated timber (CLT) were studied. The density of the parallel layer lamination of CLT was 640.47±61.85 kg/m3, and the perpendicular layer laminations for CLT larch wood, poplar, and oriented strand board (OSB) were 392.51±40.14, 343.73±17.16, and 384.41±12.93 kg/m3. Block shear bond strength (BBS), wood failure percentage (WFP), and delamination rate (DR) of the hybrid CLT specimens were also determined. The results showed that the three kinds of hybrid CLT prepared with polyurethane (PUR) adhesive had good bonding properties under 1.2 MPa of bonding pressure. The BBS values of CLT with larch wood, poplar hybrid, and OSB hybrid were 2.32, 2.41, and 1.98 MPa, respectively; furthermore, their WFPs were all greater than 80%, and their DRs were 9.32%, 0.37%, and 0.11%, respectively. Regarding the relationship between perpendicular layer material properties and bonding properties, analysis revealed that delamination performance was strongly correlated with pH, buffer capacity, and the surface free energy of the perpendicular layer, whereas the WFP and BBS values had a strong correlation with pH and buffer capacity. Density was determined to be unrelated to bonding performance in the CLT prepared in this experiment. Microscopic analysis of the bonding line proves that the PUR adhesive can effectively penetrate into three different laminations under a bonding pressure of 1.2 MPa and form enough nails to ensure bonding strength.

Optimal spare parts production–distribution scheduling considering operational utility on customer equipment

Integrated scheduling of production and distribution is conducive to saving transportation cost and improving customer satisfaction. However, in previous related literature, no optimization objective has been set to intuitively reflect the influence of the scheduling scheme on the customer side, ignoring the fact that: 1) the production and distribution of spare parts directly affect the performance of operation and maintenance and further affect the operational utility of customer equipment; 2) the delivery time of spare parts has a positive effect on optimizing the operational utility of customer equipment corresponding to the delayed spare parts. To fill this gap, in the paper, we construct an optimal spare parts production scheduling model integrating logistics distribution in flowshop environment, in which equipment operation utility on the customer side is set as an optimization objective and a speed adjustment strategy is introduced, so that the manufacturer can adjust the operation strategy of the equipment corresponding to the delayed spare parts and guide the equipment operation and maintenance in the customer side. There are two objectives in our model. The first is to maximize equipment operational utility on the customer side, and the second is to minimize the total cost on the manufacturing side. To solve the problem, a three-layer hybrid coding memetic algorithm (THMA) is constructed. Two initial heuristics, respectively named Heuristics 1 and Heuristics 2, are constructed. Two local search operators operated respectively on the production and distribution stages of spare parts are constructed. By performing extensive contrast experiments, the superiority of THMA and the effectiveness of all the above operators are verified.

Crashworthiness reinforcements of multi-cell thin-walled tubes through topology optimized lattice structures under axial and lateral loadings

Thin-walled tubes have been predominantly utilized in passive vehicle safety systems as crash energy absorbers. With the increasing popularity of additive manufacturing technique, it is feasible to fabricate novel internal reinforcement structures to further reinforce the crashworthy performances of thin-walled tubes. In the present work, a novel nonuniform Lattice-reinforced multi-cell tube based on topology optimization was put forward to explore the crashworthy performances under axial loading and lateral bending. Numeric models validated against the experiments were established to reveal the crashworthy performances of lattice material infilled multi-cell tubes (MCTs). It is observed that the optimized nonuniform lattice structure absorbs more energy than the uniform counterpart. In addition, the hybrid multi-cell filled tubes exhibit remarkable improvements in terms of energy absorption and crushing force efficiency in contrast to the corresponding empty tubes. Furthermore, the specific energy absorption of the three-layer hybrid multi-cell tube is improved by 38.2% and 20.0% under two loading conditions respectively relative to the sum of individual components on account of interplay effect. Collectively, the hybrid nonuniform lattice reinforcement tube provides a promising method for the crashworthy design of MCTs, which can be recommended as an underlying candidate for passive safety protection applications.

Bioinspired drag reduction surfaces via triple lithography method based on three-layer hybrid masks

Drag reduction is a significant challenge for many industries, such as ships, pipelines, aircraft, energy, and transportation. Multilayer hierarchical microstructures can inhibit the development of vortices near the wall, which is beneficial to drag reduction. However, existing methods have difficulty performing the controlled fabrication of complex multilayer hierarchical microstructure arrays. Here, a novel triple lithography method based on three-layer hybrid masks is proposed for the controlled fabrication of three-dimensional multilayer hierarchical microstructure surfaces. The capability of the proposed process is verified by the multilayer hierarchical microstructures. In the fabrication process, a special lithography sequence is designed based on the hybrid mask materials. The drag reduction ability of the multilayer hierarchical microstructures is investigated in a closed air channel measurement system. The experimental results demonstrate that the fabricated multilayer hierarchical microstructures exhibit significant drag reduction ability under certain conditions. Conceptual models based on the fluid-solid coupling interface interaction are proposed to explain the drag reduction mechanism of multilayer hierarchical microstructures. The proposed fabrication method provides a powerful means for practical engineering applications of various bioinspired functional surfaces, such as drag reduction, anti-icing, antifouling, self-cleaning, and superhydrophobic surfaces.

A novel load balancing scheme for mobile edge computing

To overcome long propagation delays for data exchange between the remote cloud data center and end devices in Mobile Cloud Computing (MCC), Mobile Edge Computing (MEC) is emerging to push mobile computing, network control and storage to the network edges. A cloudlet in MEC is a mobility-enhanced small-scale cloud, which contains several MEC servers located in close proximity to mobile devices. The main purpose of a cloudlet is to stably provide services to mobile devices with low latency. When a cloudlet offers hundreds kinds of services to millions of mobile devices, it is critical to balance the loads so as to improve performance.In this paper, we propose a three-layer mobile hybrid hierarchical P2P (MHP2P) model as a cloudlet. MHP2P performs satisfactory service lookup efficiency and system scalability as well as high stability. More importantly, a load balance scheme is provided so that the loads of MHP2P can be well balanced with the increasing of MEC servers and query load. A large number of simulation experiments indicate that the proposed scheme is efficient for enhancing the load balancing performance in MHP2P based MEC systems.

Low Air Drag Surface via Multilayer Hierarchical Riblets.

Riblets inspired by shark skin exhibit a great air drag reduction potential in many industries, such as the aircraft, energy, and transportation industries. Many studies have reported that blade riblets attain the highest air drag reduction ability, with a current limit of ∼11%. Here, we propose multilayer hierarchical riblets (MLHRs) to further improve the air drag reduction ability. MLHRs were fabricated via a three-layer hybrid mask lithography method, and the air drag reduction ability was studied in a closed air channel. The experimental results indicated that the maximum air drag reduction achieved with MLHRs in the closed channel was 16.67%, which represents a 52% higher reduction than the highest previously reported. Conceptual models were proposed to explain the experiments from a microscopic perspective. MLHRs enhanced the stability of lifting and pinning vortices, while vortices gradually decelerated further, reducing the momentum exchange occurring near the wall. This verified that MLHRs overcome the current air drag reduction limit of riblets. The conceptual models lay a foundation to further improve the air drag reduction ability of riblets.

Three-layer hybrid intrusion detection model for smart home malicious attacks

With the development of Internet of Things and the increasingly rampant malicious network activities, higher requirements are put forward for security to detect malicious behavior and prevent attackers from obtaining sensitive data in the smart home environment. In this paper, an intrusion detection system is proposed to detect and classify abnormal behavior in the smart home environment. The two-layer feature processing method based on random forest and principal component analysis can reduce the loss of data information and is suitable for massive data. The three-layer detection model can detect four common attacks with binary classifiers and effectively improve the accuracy. The experimental evaluation of the proposed model is conducted using the real smart home traffic dataset and achieves a classification accuracy of 95.90%. The experimental results show that our model has a good performance in detecting and classifying malicious attacks in the smart home.

Structural performance of hybrid Poplar-Beech cross-laminated-timber (CLT)

The purpose of this research was to investigate the structural out-of-plane bending performance of three-layer hybrid cross-laminated-timber manufactured from outer layers of fast-growing Poplar (Populus alba) and a cross-layer of Iranian Beech species (Fagus orientalism) using polyurethane as a binder. The bending performance of the hybrid CLT was determined in both major and minor axis orientations in diverse span-to-thickness ratios by experimental and theoretical methods. It was compared to that of Poplar CLT reported in our previous research. The experimental and theoretical methods indicated that the bending performances comprising maximum shear force (Vmax), maximum bending moment (Mmax), apparent modulus of elasticity (MOEapp), modulus of rupture (MOR), shear strength (τmax), effective bending stiffness (EIeff), and effective shear stiffness (GAeff) of hybrid Poplar-Beech CLT in all span-to-thickness ratios at both major and orientations were greater than those of Poplar CLT. Moreover, in both orientations, the results of bending and shear stress distributions of the specimens showed that the hybrid Poplar-Beech CLT had greater load-carrying capacity than Poplar CLT. However, in both orientations, the failure modes of hybrid CLT were similar to those of Poplar CLT. The experimental dominant failure modes in the major axis orientation of CLTs were rolling shear and delamination, while tensile failure and crack were mainly observed in the minor axis orientation. In summary, in comparison with Poplar CLT, both experimental and theoretical results revealed that hybrid Poplar-Beech CLT had more tremendous potential for structural bending performance in the construction and building sector.

Allocation and Scheduling of Handling Resources in the Railway Container Terminal Based on Crossing Crane Area

The integrated allocation and scheduling of handling resources are crucial problems in the railway container terminal (RCT). We investigate the integrated optimization problem for handling resources of the crane area, dual-gantry crane (GC), and internal trucks (ITs). A creative handling scheme is proposed to reduce the long-distance, full-loaded movement of GCs by making use of the advantages of ITs. Based on this scheme, we propose a flexible crossing crane area to balance the workload of dual-GC. Decomposing the integrated problem into four sub-problems, a multi-objective mixed-integer programming model (MIP) is developed. By analyzing the characteristic of the integrated problem, a three-layer hybrid heuristic algorithm (TLHHA) incorporating heuristic rule (HR), elite co-evolution genetic algorithm (ECEGA), greedy rule (GR), and simulated annealing (SA) is designed for solving the problem. Numerical experiments were conducted to verify the effectiveness of the proposed model and algorithm. The results show that the proposed algorithm has excellent searching ability, and the simultaneous optimization scheme could ensure the requirements for efficiency, effectiveness, and energy-saving, as well as the balance rate of dual-GC.

Trust-based energy-efficient routing protocol for Internet of things–based sensor networks

Internet of things grew swiftly and many services, software, sensors-embedded electronic devices and related protocols were developed and still in progress with full swing. Internet of things enabling physically existing things to see, hear, think and perform a notable task by allowing them to talk to each other and share useful information while making decision and caring-on/out their important tasks. Internet of things is greatly promoted by wireless sensor network as it becomes a perpetual layer for it. Wireless sensor network works as a base-stone for most of the Internet of things applications. There are severe general and specific threats and technical challenges to Internet of things–based sensor networks which must overcome to ensure adaptation and diffusion of it. Most of the limitations of wireless sensor networks are due to its resource constraint objects nature. The specified open research challenges in Internet of things–based sensor network are power consumption, network lifespan, network throughput, routing and network security. To overcome aforementioned problems, this work aimed to prolong network lifetime, improve throughput, decrease packet latency/packet loss and further improvise in encountering malicious nodes. To further tune the network lifetime in terms of energy, wireless harvesting energy is suggested in proposed three-layer cluster-based wireless sensor network routing protocol. The proposed mechanism is a three-tier clustering technique with implanted security mechanism to encounter malicious activities of sensor nodes and to slant them into blacklist. It is a centred-based clustering protocol, where selection of cluster head and grid head is carried out by sink node based on the value of its cost function. Moreover, hardware-based link quality estimators are used to check link effectiveness and to further improve routing efficiency. At the end, excessive experiments have been carried out to check efficacy of the proposed protocol. It outperforms most of its counterpart protocols such as fuzzy logic–based unequal clustering and ant colony optimization–based routing hybrid, Artificial Bee Colony-SD, enhanced three-layer hybrid clustering mechanism and energy aware multi-hop routing in terms of network lifetime, network throughput, average energy consumption and packet latency.

Influence of Aspect Ratio on Rolling Shear Properties of Fast-Grown Small Diameter Eucalyptus Lumber

Eucalyptus is a major fast-grown species in South China, which has the potential for producing structural wood products such as cross-laminated timber (CLT). Aspect ratio (board width vs. board thickness) of eucalyptus lumbers is small due to the small diameter of fast-grown eucalyptus wood. To evaluate its rolling shear modulus and strength for potential CLT applications, three-layer hybrid CLT shear block specimens with different aspect ratios (2,4,6), were tested by planar shear test method. Digital image correlation (DIC) was employed to measure the rolling shear strain distribution and development during the planar shear tests. The mean values of rolling shear modulus and strength of eucalyptus lamination were 260.3% and 88.2% higher than those of SPF(Spruce-pine-fir) lamination with the same aspect ratio of 4, respectively. The rolling shear properties of eucalyptus laminations increased as the aspect ratio increased. Aspect ratio had a significant influence on rolling shear modulus compared to rolling shear strength. The high shear strain regions were primarily found around the gaps between segments of cross layer. The quantity of high shear strain regions increased as the aspect ratio of lamination decreased. Other high shear strain regions also occurred around the pith and along the glue line. The sudden failure of specimen occurred in the high strain region. In conclusion, the rolling shear strength and modulus of fast-grown eucalyptus laminations exceed the respective characteristic values for softwoods in the current standard by roughly factors of 3 and 8, indicating great potential for fast-grown eucalyptus wood cross-layers in CLT.

Ultrasmall broadband wavelength and polarization router based on hybrid waveguide of monolithic-LiNbO3

The nanoscale wavelength and polarization router, which can simultaneously separate wavelength and polarization modes, is an essential component of on-chip nanophotonic devices. Here, an on-chip wavelength and polarization router is realized experimentally based on a three-layer hybrid waveguide of Au-SiO2-LiNbO3 etched with asymmetric nano-cavities. The central area size of the device is only 1.60×1.96 μm2. A broad operation band covers from 500nm to 1150nm with low cross talk of under 10dB. The monolithic-LiNbO3is introduced for the first time, to the best of our knowledge, to on-chip multichannel wavelength and polarization routers. This work plays a key role for dense chip integration, visible light displays, and communications, and can inspire LiNbO3-based nanophotonic devices.

A Novel Hybrid Clustering Algorithm for Topic Detection on Chinese Microblogging

The hot topics discussed on microblogs mirror public opinion, so the topic detection on microblogs is of great significance for the detection and management of public opinion. However, it is difficult for traditional clustering algorithms to handle the large-scale microblogging data with various topics and high noise. Therefore, we propose a three-layer hybrid algorithm to tackle this problem. In the first layer, we use the $K$ -means algorithm, in which the initial center selection optimized to group the microblog texts efficiently. We then subdivide big clusters and isolate noise text to get purer clusters. In the second layer, we adopt the agglomerative nesting (AGNES) algorithm to merge the small clusters referring to the same topic. Then, we exclude most noise, reducing their further impact on the $K$ -means in the third layer which corrects the erroneous merging occurring in AGNES. Experiments show that our algorithm outperforms some related traditional algorithms on the clustering of real microblogging data set and performs well in the topic detection.

A New Hybrid Image Encryption Algorithm Based on 2D-CA, FSM-DNA Rule Generator, and FSBI

Image encryption is an efficient and vital way to protect classified and secret images. With the advancement of the processing power of the computer, AES, DES, or chaotic series type just alike image encryption schemes are not as secure as before. Therefore, in this paper, we present a new hybrid image encryption method for protecting secret and imperative images by employing logistic sine system (LSS) together with two-dimensional cellular automata and FSM-based DNA rule generator. The secure hash (SHA-256) algorithm is used to generate a secret key and to compute initial values for the LSS. In our proposed method, there are three stages and each stage has its own rule. After the scrambling process, the first stage is the Feistel structure-based bit inversion (FSBI) to change the pixels’ value. The second stage is 2D-CA with Moore neighborhood structure-based local rules. The third is DNA conversion based on finite-state machine (FSM-DNA) rule generator. The proposed encryption scheme is robust against the well-known attacks, such as statistical attacks, brute force attacks, differential attacks, and pixel correlation attacks, and also possesses strong key sensitivity. The results show that our three-layer hybrid image encryption technique is robust against many well-known attacks and can be applied directly to all types of classified gray-scale images to make them more secure from such cryptography attacks.