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This paper aims to propose a biologically inspired processing architecture to recognize and classify fabrics with respect to the weave pattern (fabric texture) and yarn color (fabric color).

By using the fabric weave patterns image identification system, this study analyzed the fabric image based on the Hierarchical-MAX (HMAX) model of computer vision, to extract feature values related to texture of fabric. Red Green Blue (RGB) color descriptor based on opponent color channels simulating the single opponent and double opponent neuronal function of the brain is incorporated in to the texture descriptor to extract yarn color feature values. Finally, support vector machine classifier is used to train and test the algorithm.

This two-stage processing architecture can be used to construct a system based on computer vision to recognize fabric texture and to increase the system reliability and accuracy. Using this method, the stability and fault tolerance (invariance) was improved.

Traditionally, fabric texture recognition is performed manually by visual inspection. Recent studies have proposed automatic fabric texture identification based on computer vision. In the identification process, the fabric weave patterns are recognized by the warp and weft floats. However, due to the optical environments and the appearance differences of fabric and yarn, the stability and fault tolerance (invariance) of the computer vision method are yet to be improved. By using our method, the stability and fault tolerance (invariance) was improved.

AT THE INTERNATIONAL CONFERENCE ON GEARING arranged by the Institution of Mechanical Engineers in London from the 23rd to 25th September, a special session was set aside for the Discussion of Lubrication and the following papers were presented :—

The temperature response of properties of Single crystal tungsten (111) at high temperature is still not been thoroughly understood. All the mechanical properties are temperature dependent. The experiments are performed with tailor made Berkovich tip of radius 100 nm with temperatures of 373 K, 473 K and 623 K to study the behavior of Single crystal Tungsten at various temperatures. The new phenomena of material under the indenter bouncing back at the end of unloading were clearly noticed, due to the accumulation of high energy. One particularly interesting observation is the appearance of discrete plasticity during the unloading segment as evidenced by a displacement burst or pop‐in at ∼1 mN at elevated temperatures. It is also noted that the elastic recovery reduces at higher temperatures. The results for different temperatures are compared. Our experiments clearly show the periodic bursts and the softening effects. Pile up is observed. It is noticed that there is significant drop in hardness, elastic modulus and increase in displacement with increasing temperature. This softening phenomenon corresponds to the increase of indentation depth for the same loading conditions. Clear bursts are seen showing the nucleation of dislocations. At higher peak loads, the indentation contact in tungsten is not just elastic. Tungsten is chosen to illustrate the temperature dependence behaviour because of its isotropic elastic behaviour at low loads. This work attempts to explore the complete behaviour of metals at various temperatures, including the initial burst, the complete elastic recovery, the softening effect and the modulus and Hardness.

The paper describes an efficient method to extract the B‐H nonlinear characteristic from the experimental flux‐current Φ‐I data obtained using a non‐uniform magnetic field device. Both functions are monotonically piecewise linear approximated with the same number of breakpoints. The method was successfully applied to characterize the ribbon core material of a fluxset magnetic field sector. In this case the hysteresis loop and the lumped magnetic circuit were extracted. Comparison with experimental results validates the proposed method.

The e-commerce boom presents new challenges for last-mile delivery (LMD), which may be mitigated by new delivery technologies. This paper evaluates the impact of mobile parcel lockers (MPL) on costs and CO₂ equivalent (CO₂e) emissions in existing LMD networks, which include home delivery and shipments to stationary parcel lockers.

To describe customers’ preferences, we design a multinomial logit model based on recipients’ travel distance to pick-up locations and availability at home. Based on route cost estimation, we define the operating costs for MPLs. We devise a mathematical model with binary decision variables to optimize the location of MPLs.

Our study demonstrates that integrating MPLs leads to additional cost savings of 8.7% and extra CO₂e emissions savings of up to 5.4%. Our analysis of several regional clusters suggests that MPLs yield benefits in highly populous cities but may result in additional emissions in more rural areas where recipients drive longer distances to pick-ups.

This paper designs a suitable operating model for MPLs and demonstrates environmental and economic savings. Moreover, it adds recipients’ availability at home to receive parcels improving the accuracy of stochastic demand. In addition, MPLs are evaluated in the context of several regional clusters ranging from large cities to rural areas. Thus, we provide managerial guidance to logistics service providers how and where to deploy MPLs.

Partitioned analysis is a method by which sets of time‐dependent ordinary differential equations for coupled systems may be numerically integrated in tandem, thereby avoiding brute‐force simultaneous solution. The coupled systems addressed pertain to fluid—structure, fluid—soil, soil—structure, or even structure—structure interaction. The paper describes the partitioning process for certain discrete‐element equations of motion, as well as the associated computer implementation. It then delineates the procedure for designing a partitioned analysis method in a given application. Finally, examples are presented to illustrate the concepts. It is seen that a key element in the implementation of partitioned analysis is the use of integrated, as opposed to monolithic software.

The wear of different car parts is affected by a variety of external factors. Mechanical wear takes the greatest toll of moving surfaces. Minute as the particles which wear away are, in their total they are the essential factor which causes the surface structure, the original dimensions and the shape of the parts to change gradually. Moving parts are not the only ones to deteriorate from mechanical wear: stationary parts, such as connections by threads, wedges, slots, etc., also suffer heavily.

The face-centered cubic structured single-phase FeCoNiCrMn high-entropy alloys (HEAs) were prepared to study the friction and wear behavior of HEAs under MoS₂-oil lubrication.

FeCoNiCrMn alloys were subjected to ball-on-disc reciprocating sliding against the GCr15 ball. L₂₅(5⁶) orthogonal wear tests were designed for velocity V_rel (4.167-20.833 mm/s), load F_N (10-50 N), temperature T (RT-140 °C) and time t (5-20 min). Based on orthogonal test results, multivariate repeated measures ANOVA was performed, and further comparative experiments were conducted for V_rel, F_N and T. Energy dispersive spectrometer and scanning electron microscope were applied to characterize the surface morphology of wear scar and its element distribution.

V_rel, F_N and t exerted the most significant influence (p < 0.01) on the average friction coefficient f. V_rel and F_N were identified as the momentous effect (p < 0.01) on wear volume ΔV. T (≥50 °C) had positive correlation with f and ΔV, and both V_rel and F_N correlated negatively with f. The dominant abrasive wear was attributed to the large hardness difference of the friction pair. Fatigue wear and delamination wear were experienced at higher speeds (V_rel  ≥ 12.5 mm/s) and loading levels (F_N ≥ 40 N). Elevated temperature weakens the lubrication effect of MoS₂-oil and the mechanical properties of FeCoNiCrMn matrix, intensifying abrasive wear.

This study is expected to provide references for exploration on the wear behavior of single-phase HEAs under complex working conditions with lubrication and hence will help develop the application of HEAs in practical engineering.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-08-2019-0303

This paper reports further development and applications of a computational model permitting analysis of frequency response characteristics of simulated neurons. The original single‐neuron model, as described by Peddicord and Sampson in 1974, is briefly reviewed here. There follows a thorough description of a new interactive implementation of the model on a PDP‐11/45. The implementation permits high‐speed simulation of large neural networks, and is designed for easy use by investigators with no special knowledge of computers or programming. Experiments with the new system have included the design of improved bandpass filters, pacemaker neurons and networks, and a cerebellar circuit. Simulation results are presented and, in the last case, compared with available physiological data. The paper concludes with a critique of the system, suggestions for further experiments, and a comparison with the simulation system developed by Perkel. Two appendices document the system data structures and show a sample simulation run.

Two-handed automobile steering at low vehicle speeds may lead to reduced steering ability at large steering wheel angles and shoulder injury at high steering wheel rates (SWRs). As a first step toward solving these problems, this study aims, firstly, to design a surface electromyography (sEMG) controlled steering assistance interface that enables hands-free steering wheel rotation and, secondly, to validate the effect of this rotation on path-following accuracy.

A total of 24 drivers used biceps brachii sEMG signals to control the steering assistance interface at a maximized SWR in three driving simulator scenarios: U-turn, 90º turn and 45º turn. For comparison, the scenarios were repeated with a slower SWR and a game steering wheel in place of the steering assistance interface. The path-following accuracy of the steering assistance interface would be validated if it was at least comparable to that of the game steering wheel.

Overall, the steering assistance interface with a maximized SWR was comparable to a game steering wheel. For the U-turn, 90º turn and 45º turn, the sEMG-based human–machine interface (HMI) had median lateral errors of 0.55, 0.3 and 0.2 m, respectively, whereas the game steering wheel, respectively, had median lateral errors of 0.7, 0.4 and 0.3 m. The higher accuracy of the sEMG-based HMI was statistically significant in the case of the U-turn.

Although production automobiles do not use sEMG-based HMIs, and few studies have proposed sEMG controlled steering, the results of the current study warrant further development of a sEMG-based HMI for an actual automobile.