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Robot vision is a fundamental device for human–robot interaction and robot complex tasks. In this paper, the authors aim to use Kinect and propose a feature graph fusion (FGF) for robot recognition.

The feature fusion utilizes red green blue (RGB) and depth information to construct fused feature from Kinect. FGF involves multi-Jaccard similarity to compute a robust graph and word embedding method to enhance the recognition results.

The authors also collect DUT RGB-Depth (RGB-D) face data set and a benchmark data set to evaluate the effectiveness and efficiency of this method. The experimental results illustrate that FGF is robust and effective to face and object data sets in robot applications.

The authors first utilize Jaccard similarity to construct a graph of RGB and depth images, which indicates the similarity of pair-wise images. Then, fusion feature of RGB and depth images can be computed by the Extended Jaccard Graph using word embedding method. The FGF can get better performance and efficiency in RGB-D sensor for robots.

The purpose of this paper is to promote the efficiency of RGB-depth (RGB-D)-based object recognition in robot vision and find discriminative binary representations for RGB-D based objects.

To promote the efficiency of RGB-D-based object recognition in robot vision, this paper applies hashing methods to RGB-D-based object recognition by utilizing the approximate nearest neighbors (ANN) to vote for the final result. To improve the object recognition accuracy in robot vision, an “Encoding+Selection” binary representation generation pattern is proposed. “Encoding+Selection” pattern can generate more discriminative binary representations for RGB-D-based objects. Moreover, label information is utilized to enhance the discrimination of each bit, which guarantees that the most discriminative bits can be selected.

The experiment results validate that the ANN-based voting recognition method is more efficient and effective compared to traditional recognition method in RGB-D-based object recognition for robot vision. Moreover, the effectiveness of the proposed bit selection method is also validated to be effective.

Hashing learning is applied to RGB-D-based object recognition, which significantly promotes the recognition efficiency for robot vision while maintaining high recognition accuracy. Besides, the “Encoding+Selection” pattern is utilized in the process of binary encoding, which effectively enhances the discrimination of binary representations for objects.

Under multiaxial random loading, the material stress–strain response is not periodic, which makes it difficult to determine the direction of the critical plane on the material. Meanwhile, existing methods of constant loading cannot be directly applied to multiaxial random loading; this problem can be solved when an equivalent stress transformation method is used.

First, the Liu-Mahadevan critical plane is introduced into multiaxial random fatigue, which is enabled to determine the material's critical plane position under random loading. Then, an equivalent stress transformation method is proposed which can convert random load to constant load. Meanwhile, the ratio of mean stress to yield strength is defined as the new mean stress influence factor, and a new non-proportional additional strengthening factor is proposed by considering the effect of phase differences.

The proposed model is validated using multiaxial random fatigue test data of TC4 titanium alloy specimens and the results of the proposed model are compared with that based on Miner's rule and BSW model, showing that the proposed method is more accurate.

In this work, a new multiaxial random fatigue life prediction model is proposed based on equivalent stress transformation method, which considers the mean stress effect and the additional strengthening effect. Results show that the predicted fatigue lives given by the proposed model are in well accordance with the tested data.

This study aims to prepare UV protection and hydrophobic fabric through modifying cotton fabric by graphene oxide and silane coupling agent. The graphene oxide and silane coupling agent (KH570) are anchored on the cotton fabric by a stable chemical bond.

Graphene oxide was prepared by modified Hummers method. The fabric sample was treated with graphene oxide and silane coupling agent KH570 using simple dipping-padding-drying method. The effects of the dosage of graphene oxide, silane coupling agent KH570 and curing temperature were determined by single variable experiment and orthogonal experiment, The UVA and UVB transmittances in ultraviolet light of the sample fabric were characterized, and the contact angle test method with water was used to indicate the hydrophobicity of the sample fabric. The structure and surface of the fabric were analyzed using Fourier-transform infrared spectroscopy and scanning electron microscopy.

The cotton fabric was successfully modified by graphene oxide and silane coupling agent KH570. Compared with the untreated fabric, the surface of the fabric was smooth, and there was no gap on the fiber. The graphene oxide, silane coupling agent KH570 and cotton fabric combined tightly. The UPF value of the modified fabric was 50+, and the contact angle reached 138.1°. It had excellent UV protection and hydrophobic properties.

Although graphene oxide and silane coupling agents KH570 had successfully endowed the cotton fabric with good UV protection and hydrophobic properties, graphene oxide and silane coupling agent KH570 are expensive and used in large quantities. There are certain limitations in the actual life and production process.

After treating with silane coupling agent, the hydrophilic fabric treated with graphene oxide is being translated into hydrophobic, and graphene oxide bonded with cotton. The modified fabrics also have excellent UV protection. This fabric can be used for outdoor sports such as clothes and tents.

Cotton fabric treated with graphene oxide generally by simple dip-dry-cure method is hydrophilic and graphene oxide is easy to drop. The usage of silane coupling agent KH570 as a crosslinking agent to link graphene oxide and cotton fibers has not been reported yet. The modified fabrics have both UV protection and hydrophobic properties.

The stress state near the notch affects fatigue damage directly, but quantifying the stress field is difficult. The purpose of this study is to provide a mathematical description method of the stress field near the notch to achieve a reliable assessment of the fatigue life of notched specimens.

Firstly, the stress distribution of notched specimens of different materials and shapes under different stress levels is investigated, and a method for calculating the stress gradient impact factor is presented. Then, the newly defined stress gradient impact factor is used to describe the stress field near the notch, and an expression for the stress at any point along a specified path is developed. Furthermore, by combining the mathematical expressions for the stress field near the notch, a multiaxial fatigue life prediction model for notched shaft specimens is established based on the damage mechanics theory and closed solution method.

The stress gradient factor for notched specimens with higher stress concentration factors (V60-notch, V90-notch) varies to a certain extent when the external load and material change, but for notched specimens with relatively lower stress concentration factors (C-notch, U-notch, stepped shaft), the stress gradient factor hardly varies with the change in load and material, indicating that the shape of the notch has a greater influence on the stress gradient. It is also found that the effect of size on the stress gradient factor is not obvious for notched specimens with different shapes, there is an obvious positive correlation between the normal stress gradient factor and the normal stress concentration factor compared with the relationship between the shear stress gradient factor and the stress concentration factor. Moreover, the predicted results of the proposed model are in better agreement with the experimental results of five kinds of materials compared with the FS model, the SWT model, and the Manson–Coffin equation.

In this paper, a new stress gradient factor is defined based on the stress distribution of a smooth specimen. Then, a mathematical description of the stress field near the notch is provided, which contains the nominal stress, notch size, and stress concentration factor which is calculated by the finite element method (FEM). In addition, a multiaxial fatigue life prediction model for shaft specimens with different notch shapes is established with the newly established expressions based on the theory of damage mechanics and the closed solution method.

One of the intensively developed in recent years new materials are hybrid textiles modified with carbon nanotubes (CNT). In this paper, CNTs was modified by grafting dimethyl phosphite and perfluorohexyl iodine. It was applied to the cotton to obtain the flame-retardant, water-repellent, ultraviolet-resistant and conductive multifunctional fabric.

The modified CNTs were loaded onto cotton fabric by impregnation and drying. The CNTs-multi was synthesized by grafted dimethyl phosphite and perfluorohexyl chain and applied to the cotton by dipping-drying method. The surface chemistry of functionalized CNTs was characterized by Fourier transform infrared spectroscopy and X-ray photoelectron spectroscopy (XPS). The combustion properties were evaluated using a microscale combustion calorimeter, match test and TGA analysis. Surface hydrophilicity and hydrophobicity of fabric surface was characterized by static contact angle, and the UV resistance of the fabric was represented by the UPF value.

Dimethyl phosphite and perfluorohexyl chain were grafted on the surface of CNTs successively. The quantity of each component on the surface of CNTs was calculated according to XPS results. According to miniature combustion calorimeter data, both the value of maximum heat release rate (PHRR) and total heat release (THR) of CNTs -multi/cotton was about 65% lower than that of untreated cotton fabric. The residue after combustion of CNTs -multi/ cotton in the match test was more compact. The electrical conductivity of multi/ cotton is 225.6 kΩ/□, which is better than that of untreated cotton fabric. The UPF value of CNTs-multi/cotton reached 121, which was indicated that the anti-ultraviolet performance of CNTs-multi was greatly improved.

Modifying method to increase the functional component amuount on the CNTs surface still need to be explored, which could increase the hydrophobicity. How to further improve the functional effect and the general synthetic steps will be of great significance to the preparation of multifunctional modified cotton fabric.

This modifying method can be used in any of multifunctional textile preparation process. The UV-resistant and flame retardant cotton fabric was revealed as a sample for use in outdoor sports such as clothes and tents.

To meet the needs of multifunctional cotton fabric, the modification of CNTs with dimethyl phosphite and perfluorohexyl iodine has not been reported. The modified fabric has flame-retardant, UV-resistant conductive and conductive properties.

On one side, the purpose of this paper is to numerically analyze the emergency order allocation mechanism and help managers to understand the relationship between the emergency coefficient, uncertainty and emergency cost in two‐echelon logistics service supply chain. On the other side, the purpose of this paper is to help managers understand how to deal with the problem of order allocation in the two‐echelon logistics service supply chain better in the case of emergency.

The paper presents a multi‐objective planning model for emergency order allocation and then uses numerical methods with LINGO 8.0 software to identify the model's properties. The application of the order allocation model is then presented by means of a case study.

With the augment of uncertainty, the general cost of logistics service integrator (LSI) is increasing, while the total satisfaction of all functional logistics service providers (FLSPs) is decreasing, as well as the capacity reliability; at the same time the emergency cost coefficient is closely correlative with the satisfaction and general penalty intensity of FLSPs; finally, the larger the emergency cost coefficient is, the more satisfaction of FLSPs, but the capacity reliability goes up first and down later.

Management should note that it is not better when emergency cost coefficient is bigger. The general satisfaction degree of FLSP increases with the augment of emergency cost coefficient, but there is an upper limit of the value, i.e. it will not increase indefinitely with the augment of emergency cost coefficient. This paper also has some limitations. The optional emergency cost coefficient only adopted a group of data to analyze while the trend of the reliability of logistics capacity needs to be further discussed. In addition, the algorithm of emergency order allocation model in the case of multi‐objective remains to be solved.

Under emergency conditions, LSIs can adopt this kind of model to manage their FLSPs to obtain the higher logistics performance. But LSIs should be careful selecting emergency cost coefficient. In accordance with different degrees of emergency logistics demand, LSIs can determine reasonable emergency cost coefficient, but not the bigger, the better, on the premise that LSIs acquire maximum capacity guarantee degree and overall satisfaction degree of FLSPs. FLSPs can make contract bargaining of reasonable emergency coefficient with LSIs to make both sides get the best returns and realize the benefit balance.

Many studies have emphasized the capacity allocation of manufactures, order allocation of manufacturing supply chain and scheduling model of emergency resources without monographic study of supply chain order allocation of logistics service. Because the satisfaction degree of FLSPs the cost of integrators needs to be considered in the process of order allocation, and the inventory cost of capacity does not exist, it is different from the issue of capacity allocation planning of manufacture supply chain. Meanwhile, the match of different kinds of logistics service capacity must be considered for the reason of the integrated feature of logistics service. Additionally, cost is not the most important decision objective because of the characteristics of demand uncertainty and weak economy. Accordingly, this paper considers these issues.

This paper proposes an integrated IT2F-FMEA model under a group decision-making setting. In risk assessment models, experts' evaluations are often aggregated beforehand, and necessary computations are performed, which in turn, may cause a loss of information and valuable individual opinions. The proposed integrated IT2F-FMEA model aims to calculate risk priority numbers from the experts' evaluations and then fuse experts' judgments using a novel integrated model.

This paper presents a novel failure mode and effect analysis (FMEA) model by integrating the fuzzy inference system, best-worst method (BWM) and weighted aggregated sum-product assessment (WASPAS) methods under interval type-2 fuzzy (IT2F) environment. The proposed FMEA approach utilizes the Mamdani-type IT2F inference system to calculate risk priority numbers. The individual FMEA results are combined by using integrated IT2F-BWM and IT2F-WASPAS methods.

The proposed model is implemented in a real-life case study in the furniture industry. According to the case study, fifteen failure modes are considered, and the proposed integrated method is used to prioritize the failure modes.

Mamdani-type singleton IT2F inference model is employed in the FMEA. Additionally, the proposed model allows experts to construct their membership functions and fuzzy rules to capitalize on the experience and knowledge of the experts. The proposed group FMEA model aggregates experts' judgments by using IT2F-BWM and IT2F-WASPAS methods. The proposed model is implemented in a real-life case study in the furniture company.