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Developing general closed-form solutions for six-degrees-of-freedom (DOF) serial robots is a significant challenge. This paper thus aims to present a general solution for six-DOF robots based on the product of exponentials model, which adapts to a class of robots satisfying the Pieper criterion with two parallel or intersecting axes among its first three axes.

The proposed solution can be represented as uniform expressions by using geometrical properties and a modified Paden–Kahan sub-problem, which mainly adopts the screw theory.

A simulation and experiments validated the correctness and effectiveness of the proposed method (general resolution for six-DOF robots based on the product of exponentials model).

The Rodrigues rotation formula is additionally used to turn the complex problem into a solvable trigonometric function and uniformly express six solutions using two formulas.

The aim of this study was to investigate the effectiveness of restoration of gold foils on Dazu Grottoes using different parylene coatings.

The gold foil samples were applied with two types of parylene coating with six different thicknesses, C‐10, C‐15, C‐20, N‐10, N‐20, N‐25, respectively. Electrochemical impedance, surface morphology, and hydrophobicity properties were used to examine the behavior of the coatings.

The results showed that an increase in electrochemical corrosion resistance was observed as the degree of coating thickness was increased for both C‐parylene and N‐parylene coatings. In addition, the surface morphology study, using 3D topography measurement, indicated that the surface roughness was decreased for all parylene coatings. Furthermore, the parylene‐C coating was comparatively more effective than was the parylene‐N coating.

The results obtained from the three methods were in close agreement. This is an indication that the parylene‐C coating can be used to restore the gold foils on Dazu Grottoes and to support future restoration and consolidation to be applied on site on the Grottoes.

Quality communication is a big challenge in mobile ad hoc networks because of a restricted environment for mobile devices, bandwidth-constrained radio connections, random mobility of connected devices, etc. High-quality communication through wireless links mainly depends on available bandwidth, link stability, energy of nodes, etc. Many researchers proposed stability and link quality methods to improve these issues, but they still require optimization. This study aims to contribute towards better quality communication in temporarily formed networks. The authors propose the stable and bandwidth aware dynamic routing (SBADR) protocol with the aim to provide an efficient, stable path with sufficient bandwidth and enough energy hold nodes for all types of quality of service (QoS) data communication.

The proposal made in this work used received signal strength from the media access control (MAC) layer to estimate the stability of the radio connection. The proposed path stability model combines the stability of the individual link to compute path stability. The amount of bandwidth available for communication at a specific time on a link is defined as the available link bandwidth that is understood as the maximum throughput of that link. Bandwidth as a QoS parameter ensures high-quality communication for every application in such a network. One other improvement, towards quality data transmission, is made by incorporating residual energies of communicating and receiving nodes in the calculation of available link bandwidth.

Communication quality in mobile ad hoc network (MANET) does not depend on a single parameter such as bandwidth, energy, path stability, etc. To address and enhance quality communication, this paper focused on high impact factors, such as path stability, available link bandwidth and energy of nodes. The performance of SBADR is evaluated on the network simulator and compared with that of other routing protocols, i.e. route stability based QoS routing (RSQR), route stability based ad-hoc on-demand distance vector (RSAODV) and Ad-hoc on-demand distance vector (AODV). Experimental outcomes show that SBADR significantly enhanced network performance in terms of throughput, packet delivery ratio (PDR) and normalized control overhead (NCO). Performance shows that SBADR is suitable for any application of MANET having random and high mobility.

QoS in MANET is a challenging task. To achieve high-quality communication, the authors worked on multiple network parameters, i.e. path stability, available link bandwidth and energy of mobile nodes. The performance of the proposed routing protocol named SBADR is evaluated by a network simulator and compared with that of other routing protocols. Statistical analysis done on results proves significant enhancement in network performance. SBADR is suitable for applications of MANET having random and high mobility. It is also efficient for applications having a requirement of high throughput.

SBADR shows a significant enhancement in received data bytes, which are 1,709, 788 and 326 more in comparison of AODV, RSAODV and RSQR, respectively. PDR increased by 21.27%, 12.1%, 4.15%, and NCO decreased by 9.67%, 5.93%, 2.8% in comparison of AODV, RSAODV and RSQR, respectively.

Outcomes show SBADR will perform better with applications of MANET such as disaster recovery, city tours, university or hospital networks, etc. SBADR is suitable for every application of MANET having random and high mobility.

This is to certify that the reported work in the paper entitled “SBADR: stable and bandwidth aware dynamic routing protocol for mobile ad hoc network” is an original one and has not been submitted for publication elsewhere. The authors further certify that proper citations to the previously reported work have been given and no data/tables/figures have been quoted verbatim from the other publications without giving due acknowledgment and without permission of the author(s).

The purpose of this paper is to investigate the evolution of the permeability of spherical packing during cold compaction by pore-scale modeling.

The discrete element method (DEM) is used to generate spherical packing structure under different compressive pressures and the Lattice Boltzmann method (LBM) is adopted to calculate the permeability of each spherical assembly.

It is found that the decrease of the porosity is the main reason of the reduction in permeability in the initial compression stage, but its influence becomes insufficient in the late compression stages. Besides, two empirical formulas are obtained, which describe the relation between the permeability and the equivalent mean diameter and the variation of normalized permeability with compressive pressure, respectively.

In this study, the authors study the spherical particles and ignore the non-spherical effects. Besides, the classical contact model, the linear-spring-damping model, is used in DEM, so the plastic deformation cannot be considered.

The DEM and the LBM are well combined to study the compaction effects on permeability of spherical packing. Two simple expressions of the spherical packing structure with uniform diameter distribution are given for the first time.

The purpose of this paper is to explore the flow and heat transfer characteristics of the jet impingement onto a conical heat sink and evaluate the ability of heat transfer enhancement.

A numerical study of the flow and heat transfer of liquid impingement on cone heat sinks was conducted, and transition SST turbulence model was validated and adopted. The flow and thermal performances were investigated with the Reynolds number that ranges from 5,000 to 23,000 and cone angle that ranges from 0° to 70° in four regions.

Local Nusselt numbers are large, and pressure coefficients drop rapidly near the stagnation point. In the conical bottom edge, a secondary inclined jet was observed, thereby introducing a horseshoe vortex that causes drastic fluctuations in the curves of the flow and heat transfer. The average Nusselt numbers are higher in a conical protuberance than in flat plates in most cases, thus indicating that the heat transfer performance of jet impingement can be improved by a cone heat sink. The maximum increase is 13.6 per cent when the cone angle is 60°, and the Reynolds number is 23,000.

The flow and heat transfer behavior at the bottom edge of the cone heat sink is supplemented. The average heat transfer capacity of different heat transfer radii was evaluated, which provided a basis for the study of cone arrays.

The purpose of this paper is to present a novel scheme of high‐dynamic global positioning system (GPS) software receiver in order to improve the capturing speed and trading accuracy of GPS receiver.

First, the beginning of C/A code can be found through the delay and multiply approach. To solve the problems of estimating a certain satellite's Doppler shift from the signals of several visible satellites, the “delay and accumulation unit” is put forward, and besides, performance of inertial navigation system‐assisted tracking loop in high‐dynamic circumstance is analysed by means of mathematical modelling and simulation experiments, whose results verified the validity of the proposed tracking scheme.

In this paper, the two‐dimension searching process in conventional acquisition scheme is transformed into two one‐dimension searching processes, thus improving the capturing speed.

This software receiver has only been verified by means of mathematical simulation, and the validity in hardware receiver is still obscured.

This paper presents a novel high‐dynamic GPS software receiver scheme, which can be seen as a reference of engineering application and simulation research.

Inadequate balancing of resources often results in resource conflict in the multiproject management process. Past research has focused on how to allocate a small amount of resources optimally but has scarcely explored how to foresee multiproject resource conflict risk in advance. The purpose of this study is to address this knowledge gap by developing a model to predict multiproject resource conflict risk.

A fuzzy comprehensive evaluation method is used to transform subjective judgments into quantitative information, based on which an evaluation index system for multiproject resource conflict risk that focuses on the interdependence of multiple project resources is proposed. An artificial neural network (ANN) model combined with this system is proposed to predict the comprehensive risk score that can describe the severity of risk.

Accurately predicting multiproject resource conflict risks in advance can reduce the risk to the organization and increase the probability of achieving the project objectives. The ANN model developed in this paper by the authors can capture the essential components of the underlying nonlinear relevance and is capable of predicting risk appropriately.

The authors explored the prediction of the risks associated with multiproject resource conflicts, which is important for improving the success rate of projects but has received limited attention in the past. The authors established an evaluation index system for these risks considering the interdependence among project resources to describe the underlying factors that contribute to resource conflict risks. The authors proposed an effective model to forecast the risk of multiproject resource conflicts using an ANN. The model can effectively predict complex phenomena with complicated and highly nonlinear performance functions and solve problems with many random variables.

To study the application of three‐dimensional differential geometric (DG) guidance commands to a realistic missile defense engagement, and the application of the Newton's iterative algorithm to DG guidance problems.

The classical differential geometry theory is introduced firstly to transform all the variables in DG guidance commands from an arc length system to the time domain. Then, an algorithm for the angle‐of‐attack and the sideslip angle is developed by assuming the guidance curvature command and guidance torsion command equal to its corresponding value of current trajectory. Furthermore, Newton's iteration is utilized to develop iterative solution of the stated algorithm and the two‐dimensional DG guidance system so as to facilitate easy computation of the angle‐of‐attack and the sideslip angle, which are formulated to satisfy the DG guidance law.

DG guidance law is viable and effective in the realistic missile defense engagement, and it is shown to be a generalization of gain‐varying proportional navigation (PN) guidance law and performs better than the classical PN guidance law in the case of intercepting a maneuvering target. Moreover, Newton's iterative algorithm has sufficient accuracy for DG guidance problem.

Provides further study on DG guidance problem associated with its iterative solution.

The purpose of this paper is to improve the overall heat transfer performance and the temperature uniformity of the heat sink and to explore the effects of the jet Reynolds number and the nanoparticle volume fraction of the nanofluids on the flow and heat transfer performance.

A heat sink with discontinuous arc protrusions in the wall jet region is proposed for confined slot jet impingement. A sloping upper cover plate is added to improve the heat transfer effect in this area. An Al₂O₃–water nanofluid is selected as the working fluid of the jet for better heat transfer. The Standard k-e turbulence model is used for numerical calculation. The key structural parameters of the heat sink are optimized by the response surface method and a genetic algorithm. The effects of the jet Reynolds number (Re) and the nanofluid concentration (ϕ) on the flow and heat transfer performance of the optimized heat sink are investigated.

The average Nusselt number of the optimal heat sink is 8.2% higher and the friction resistance is 5.9% lower than that of the initial flat plate heat sink when ϕ = 0.02 and Re = 8,000. The discontinuous arc protrusions and the sloping upper cover plate substantially enhance the heat transfer in the later stage of jet development, improving the temperature uniformity of the heat sink. The maximum temperature difference of the optimal heat sink is 28.1% lower than that of the flat plate heat sink at the same nozzle height. As the jet Reynolds number and the nanofluid particle concentration increase, the Nusselt number of the optimized heat sink and the friction coefficients increase, resulting in a decrease in the evaluation coefficient. However, the overall temperature uniformity of the heat sink is improved under all conditions.

The novel heat sink structure provides a new way to enhance the heat transfer and temperature uniformity of confined slot jet impingement. The flow and heat transfer performance of the heat sink impinged by confined slot jet of nanofluids are obtained. The combination of response surface method and genetic algorithm can be applied to the multi-objective optimization of heat resistance and flow resistance of heat sink.

With the development of deep learning-based analytical techniques, increased research has focused on fatigue data analysis methods based on deep learning, which are gaining in popularity. However, the application of deep neural networks in the material science domain is mainly inhibited by data availability. In this paper, to overcome the difficulty of multifactor fatigue life prediction with small data sets,

A multiple neural network ensemble (MNNE) is used, and an MNNE with a general and flexible explicit function is developed to accurately quantify the complicated relationships hidden in multivariable data sets. Moreover, a variational autoencoder-based data generator is trained with small sample sets to expand the size of the training data set. A comparative study involving the proposed method and traditional models is performed. In addition, a filtering rule based on the R2 score is proposed and applied in the training process of the MNNE, and this approach has a beneficial effect on the prediction accuracy and generalization ability.

A comparative study involving the proposed method and traditional models is performed. The comparative experiment confirms that the use of hybrid data can improve the accuracy and generalization ability of the deep neural network and that the MNNE outperforms support vector machines, multilayer perceptron and deep neural network models based on the goodness of fit and robustness in the small sample case.

The experimental results imply that the proposed algorithm is a sophisticated and promising multivariate method for predicting the contact fatigue life of a coating when data availability is limited.

A data generated model based on variational autoencoder was used to make up lack of data. An MNNE method was proposed to apply in the small data case of fatigue life prediction.