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In this paper a case study of mystery shopping is described, which was jointly conducted by a large apparel retailing company headquartered in Hong Kong and a management school in Shanghai. The program of mystery shopping in the stores of the company has been carried out for six years, and the scope of the activity covers some 30 cities in China. The reinforcement learning model is used to explain how mystery shopping can be employed as one strategy to improve service quality. The paper summarizes the main measures adopted by the company for continuous improvement. The whole processes of mystery shopping, the follow-up measures, and the evaluation sheet and work instruction are described as well. The paper also suggests the ways to select, train and control college students as mystery shoppers

PBO and p-aramids fibers were compared on thermal degradation in TG and DTG experiments, and PBO fiber showed the highest degradation temperature in both air and nitrogen atmosphere. Annealed under high temperature of 100°C, 200°C, 300°C and 400°C for 1.5 hours, the tenacity of these samples all decreased with the temperature, while PBO fiber showed the best tensile retention property. Whereas using the xenon arc light to simulate sunlight irradiated on the PBO and Kevlar samples for different time respectively, PBO showed the worst tensile retention property. In contrast, the p-aramid fibers showed their relatively good mechanical stability when exposed to the simulated sunlight. Therefore, the application of PBO fibers should be careful in the state of sunlight irradiation although PBO has the highest original mechanical and thermal property.

The purpose of this paper is to evaluate effects of different contents of composite ferrotitanium pigment on corrosion protection performance of epoxy resin coatings.

Different contents of composite ferrotitanium pigment were added to the epoxy resin coatings and the corrosion performance of the coatings were investigated by electrochemical test (in 5 wt.% KCl solutions at 60°C), salt spray test and simulated test. The morphology of the coating before and after corrosion was characterised by scanning electron microscopy (SEM) and energy dispersive spectroscopy (EDS).

The composite ferrotitanium improved anti‐corrosion properties of the coating due to complex reaction of ferrous ions and phosphates as well as introduction of nano powder to the composite ferrotitanium. The coating with 10 wt.% composite ferrotitanium pigment had better anti‐corrosion properties than that of 5 wt.%. Simulated experiment in an autoclave indicated that the composite ferrotitanium pigment had the best protective performance among the three green pigments such as zinc phosphate, aluminium tri‐phosphate, and composite ferrotitanium.

The pigments were added into the coating by high energy ball milling. Some of them dispersed in the coating heterogeneously and affected property of the coatings.

Composite ferrotitanium can be used to replace red lead and chromate pigments to meet environmental requirements.

The paper shows how the anti‐corrosion mechanism of the composite ferrotitanium pigment was investigated and several green pigments were selected to compare their protective performance in the autoclave.

Vision transformers (ViT) detectors excel in processing natural images. However, when processing remote sensing images (RSIs), ViT methods generally exhibit inferior accuracy compared to approaches based on convolutional neural networks (CNNs). Recently, researchers have proposed various structural optimization strategies to enhance the performance of ViT detectors, but the progress has been insignificant. We contend that the frequent scarcity of RSI samples is the primary cause of this problem, and model modifications alone cannot solve it.

To address this, we introduce a faster RCNN-based approach, termed QAGA-Net, which significantly enhances the performance of ViT detectors in RSI recognition. Initially, we propose a novel quantitative augmentation learning (QAL) strategy to address the sparse data distribution in RSIs. This strategy is integrated as the QAL module, a plug-and-play component active exclusively during the model’s training phase. Subsequently, we enhanced the feature pyramid network (FPN) by introducing two efficient modules: a global attention (GA) module to model long-range feature dependencies and enhance multi-scale information fusion, and an efficient pooling (EP) module to optimize the model’s capability to understand both high and low frequency information. Importantly, QAGA-Net has a compact model size and achieves a balance between computational efficiency and accuracy.

We verified the performance of QAGA-Net by using two different efficient ViT models as the detector’s backbone. Extensive experiments on the NWPU-10 and DIOR20 datasets demonstrate that QAGA-Net achieves superior accuracy compared to 23 other ViT or CNN methods in the literature. Specifically, QAGA-Net shows an increase in mAP by 2.1% or 2.6% on the challenging DIOR20 dataset when compared to the top-ranked CNN or ViT detectors, respectively.

This paper highlights the impact of sparse data distribution on ViT detection performance. To address this, we introduce a fundamentally data-driven approach: the QAL module. Additionally, we introduced two efficient modules to enhance the performance of FPN. More importantly, our strategy has the potential to collaborate with other ViT detectors, as the proposed method does not require any structural modifications to the ViT backbone.

In recent years, a great number of top conferences and workshops on artificial intelligence (AI) were held in China, showing Chinese AI plays an important role in the world. Meanwhile, Chinese government announced an ambitious scheme, “New Generation Artificial Intelligence Development Plan,” for the country to become a world leader in AI technologies by 2030. The AI research in China has covered various aspects, ranging from chips to algorithms. This chapter attempts to give an overview of the recent advances of AI research and development in China, as well as some perspectives on the future development of AI in China.

Trajectory tracking is an important issue to underactuated unmanned surface vehicles (USVs). However, parametric uncertainties and environmental disturbances bring great challenges to the precise trajectory tracking control of USVs. This paper aims to propose a robust trajectory tracking control algorithm with exponential stability for underactuated USVs with parametric uncertainties and unknown environmental disturbances.

In this method, the backstepping method and sliding mode control method are combined to ensure that the underactuated USV can track and maintain the desired trajectory. In addition, a modified switching-gain adaptation algorithm is adopted to enhance the robustness and reduce chattering. Besides, the global exponential stability of the closed-loop system is proved by Lyapunov’s direct method.

The proposed method in this paper offers a robust trajectory tracking solution to underactuated USVs and it is verified by simulations and experiments. Compared with the traditional proportion-integral-derivative method and several state-of-the-art algorithms, the proposed method has superior performance in simulation and experimental results.

This paper proposes a robust trajectory tracking control algorithm with exponential stability for underactuated USVs. The proposed method achieves exponential stability with better robustness and transient performance.

The purpose of this paper is to design and measure an H‐plane substrate integrated waveguide (SIW) 72 GHz backfired horn antenna chip. The SIW horn was fabricated on a standard 0.5‐μm GaAs process with substrate thickness of 100 μm.

Planar SIW horn design method with standard GaAs circuit design rule was adopted. The input reflection coefficient and output antenna gain was simulated at the FEM‐based 3D full‐wave EM solver, Ansoft HFSS and measured at the Agilent E8361C Network Analyzer and Cascade 110 GHz probe station.

The measured input −6 dB bandwidth is about 0.9 GHz at a center frequency of 72.39 GHz. The maximum antenna power gain extracted from the path loss at 72.39 GHz is about −3.64 dBi.

Thin substrate exhibits larger capacitance and energy stores rather than radiates. Flat cutting restricts the arc lens design and results in the radiation plane mismatches to the air. Simple taper transition design makes the input bandwidth much narrower. The problems can be further improved by selecting thicker substrate and the multi‐section input CPW GSG pads to microstrip transition.

Unlike the traditional anechoic chamber, the antenna measurement station is exposed to the open space and chip antenna was supported by the FR4 substrate and the metal probing station plate. A fully characterization of the antenna open space environment before the measurement is needed.

An H‐plane SIW 72 GHz horn antenna was designed and studied. The antenna was using the GaAs 0.5‐μm MMICs process design rule includes the SIW designed cylindrical metal bars all being restricted in standard rectangular shape. Compare to traditional bulky waveguide horn antenna, the antenna chip size is only 1.8×1.7 mm². The on‐wafer measurement is conducted to measure the input return loss and the maximum antenna power gain of the on‐chip antenna. The designed on‐chip SIW horn antenna is useful for the integrated design of the E band GaAs MMICs single‐chip RF transceiver.

This paper aims to consider a sustainable inventory model with price dependent demand, non-instantaneous deterioration rate, discount facility, partially backlogged shortages and advance and delay in payments for a two-warehouse system.

This model considered a non-instantaneous deterioration, which starts after a certain period with a constant rate. The deterioration rate in the rented warehouse is more compared to own warehouse. The proposed model focused on two things. The first one is to the benefits of the advance payments strategy and delayed payment for the retailer and supplier, where the two-warehouse system is available and the second one is using an appropriate discount facility on no of the installment to maximize the total profit. The classical optimization technique is used to solve the problem.

The combination of trade-credits and advance payments is initiated to provide more benefits to the retailer. The findings prove that advance payments, which are received from the retailer to the supplier are beneficial for the supplier, who can influence the demand increase because of higher lower selling prices. Decreasing the selling price is used as a catalyst to increase demand. It also extends the discount concept of Khan et al. (2019, 2019b).

This model is limited by the fact that it does not consider variable deterioration. Therefore, the proposed inventory model could be extended by considering variable deterioration, as well as fully backlogged shortages and time-dependent demand function.

The study simultaneously considers a non-instantaneous deterioration inventory model, advance-payment, trade-credit for a sustainable two-warehouse inventory system. From the literature search to the best of knowledge no researcher has undergone this sort of study.

The purpose of this paper is to extend the attitudinal approach to entrepreneurial intentions by using a structural analysis to explore overlooked personal values as the antecedents of entrepreneurial attitude. Based on the widely adopted value system proposed by Schwartz, this study argues that while one cluster of personal values is positively correlated with entrepreneurial attitude that leads to entrepreneurial intention, another cluster of personal values is negatively correlated with entrepreneurial attitude.

Questionnaire responses obtained from a sample of 276 MBA were analyzed using structural equation models to examine the influences of values on entrepreneurial intentions via entrepreneurial attitude.

The results of this study demonstrate that personal values of self-direction, stimulation, achievement, and universalism are all positively correlated with entrepreneurial attitude, which together constitute a comfort zone for entrepreneurship, whereas values in the opposite end of the circumplex including benevolence, tradition, conformity, security, and power are negatively correlated with entrepreneurial attitude. The values that discourage the formation of an entrepreneurial attitude also counter the positive effect of entrepreneurial attitude on intention, making the relationship between entrepreneurial attitude and intention contingent upon value conflicts.

This study regards entrepreneurship as a career development and contributes to the entrepreneurship study by differentiating the influences of a vital construct, i.e., personal values, which should not be regarded as a universalism. The value circumplex with a comfort and discomfort zone developed by this study can serve as a platform to help build the view on entrepreneurial intentions in terms of personal values.

The purpose of this paper is to evaluate the performance of the semiconductor industry in Taiwan, which is the main economic life‐line in Taiwan. Operational performance is normally deemed as a key factor in industry. The importance of this issue can be measured through performance indices to observe the operational performance of Taiwan's semiconductor industry.

A combination of the data envelopment analysis (DEA) and the balanced scorecard (BSC) was employed

This study finds that the efficiency of every domestic semiconductor manufacturer is generally good, and concerning the four perspectives of the balanced scorecard, the most important for the domestic firm is the financial perspective, second is the internal process perspective, third the learning and innovation perspective, and most unimportantly customer perspective.

Owing to the difficulties in data collection and the widespread ranges of the four major aspects, the application of the indices is limited in this paper. Therefore, the main suggestion of this study regarding future research directions is to expand the indices of the four aspects, in the hope of measuring the operating efficiency of enterprises in each aspect using more and improved indices.

This application can be extended by the usage of the ratio analysis and the BSC method to enhance the validity of the DEA.

When implementing DEA, traditional financial indices cannot obtain an in‐depth understanding of an enterprise, hence this study considers the four major constructs of the balanced scorecard in index selection, and employed these four major contracts to expand the indices that can be available for selection and gain a deeper understanding not only of the financial aspects, but also of customers, the internal process, learning, and innovation. It should be noted that the balanced scorecard can develop the performance goal from the perspective of job fulfillment, and uses this view to assess management performance. These indicators can reflect different focuses regarding job fulfillment, and produce pluralism in the performance indices.