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Micro ultra-thin tubes have important implications in aerospace, nuclear energy and other fields. In microassembly process, these parts are characterized by following reasons: the small size can easily lead to damage when gripping, even for low intensity and the parts are mainly affected by the instability of light source, for vision-based systems, the visual information about ultra-thin tubes is difficult to gather and the contact state is hard to monitor.

The paper presents a new method to adjust the position deviations based on contact forces during microassembly processes. Specific research is such that the assembly model was established based both on mechanic calculation and numerical simulation; the assembly task was carried out on an in-house microassembly system with coaxial alignment function (MSCA), the contact statements were controlled based on force sensor feedback signals and the model of the relationship between contact force and assembly deviations was established. Through a comparative study, the results of experiment and simulation differ by less than 11 per cent, validating the accuracy and feasibility of the method.

The model of assembly force and position deviations of micro ultra-thin tubes based on MSCA has been built. Besides, the assembly force threshold, and the assembly process parameters have been obtained.

The assembly process parameters obtained from experiments can be applied in the precision assembly and provide theoretical guidance and technical support to the precision assembly of the multi-scale parts.

The purpose of this paper is to modify light hollow polymer microsphere (LHPM) with titanium dioxide nanoparticles (nano-TiO2) to improve its compatibility with latex and apply the obtained nano-TiO2/LHPM composite particles in external wall thermal insulation coatings.

The nano-TiO2/LHPM composite particles were prepared via vigorous stirring. The morphology and chemical composition of the produced nano-TiO2/LHPM composite particles were characterized using scanning electron microscopy, energy dispersion spectrum, thermo-gravimetric analyzer and Fourier transform infrared. The performance of this new composite coating was evaluated by checking its stability, density, radiation reflectivity, thermal conductivity and the resulting insulation temperature difference when forming coating film.

It was found that a 9:1 mass ratio of nano-TiO2/LHPM with total 10 weight per cent composite particles in the thermal insulation paint showed low density, good stability, low thermal conductivity (0.1687 W/m·K) and high insulation temperature difference (5.8°C).

The LHPM can be modified by other nanoparticles to improve its insulation performance in thermal insulation coatings.

This work provides a simple, robust, but effective approach to produce new thermal insulation coatings with nano-TiO2/LHPM composite particles.

This method for surface modification of LHPMs is novel and the modified hollow polymer microspheres could be applied to external wall insulation coatings.

This paper seeks to examine the growth of the Chinese online gaming industry and disentangle the mechanisms behind the emergence of unique online gaming culture in China.

This is a review paper that provides a detailed and state‐of‐the‐art overview of the development of the Chinese online gaming Industry.

The findings indicate that online gaming is a remarkable example of an industry that is rapidly growing due to innovative business models of Chinese companies. Chinese companies are also working with the government to improve formal institutions to promote the growth of online gaming. Furthermore, we also found that Chinese online gaming industry resembles other technology industries in the country such as those related to handset and PC. Although Chinese companies were traditionally weak in creating new technologies, they have demonstrated success in some modern technologies in recent years. In the early stage of the growth, foreign players dominated the Chinese gaming industry. In recent years, this industry is characterized by the dominance of domestic players in the ecosystem catering to the full value chain of the industry.

A lack of primary data and empirical documentation and a lack of in‐depth treatment of some of the key issues are major limitations here.

The paper examines the implications of China's rapidly growing online gaming industry for high‐technology businesses all over the world. The findings of this paper would help understand the opportunities for foreign multinational companies to enter the Chinese technology market or to intensify their operations in the country as well as the risks associated with China's unique institutions.

This paper's greatest value stems from the fact that it analyzes demand conditions, industry structure and transfer and export conditions from the standpoint of the Chinese online gaming industry and market.

Three-dimensional (3D) printing is popular for many applications including the production of photocatalysts. This paper aims to focus on developing of 3D-printed photocatalyst-nano composite lattice structure. Digital light processing (DLP) 3D printing of photocatalyst composites was performed using photosensitive resin mixed with 0.5% Wt. of TiO₂ powder and varying amounts (0.025% Wt. to 0.2% Wt.) of graphene nanoplatelet powder. The photocatalytic efficiency of DLP 3D-printed photocatalyst TiO₂ composite was investigated, and the effects of nano graphite powder incorporation on the photocatalytic activity, thermal and mechanical properties were investigated.

Methods involve 3D computer-aided design modeling, printing parameters and comprehensive characterization techniques such as structural equation modeling, X-ray diffraction, thermogravimetric analysis, Fourier-transform infrared (FTIR) and mechanical testing.

Results highlight successful dispersion and characteristics of TiO₂ and graphene nanoplatelet (GNP) powders, intricate designs of 3D-printed lattice structures, and the influence of GNPs on thermal behavior and mechanical properties.

The study suggests applicability in wastewater treatment and environmental remediation, showcasing the adaptability of 3 D printing in designing effective photocatalysts. Future research should focus on practical applications and the long-term durability of these 3D-printed composites.

This paper aims to describe the use of a meta-learning framework for recommending cost-sensitive classification methods with the aim of answering an important question that arises in machine learning, namely, “Among all the available classification algorithms, and in considering a specific type of data and cost, which is the best algorithm for my problem?”

This paper describes the use of a meta-learning framework for recommending cost-sensitive classification methods for the aim of answering an important question that arises in machine learning, namely, “Among all the available classification algorithms, and in considering a specific type of data and cost, which is the best algorithm for my problem?” The framework is based on the idea of applying machine learning techniques to discover knowledge about the performance of different machine learning algorithms. It includes components that repeatedly apply different classification methods on data sets and measures their performance. The characteristics of the data sets, combined with the algorithms and the performance provide the training examples. A decision tree algorithm is applied to the training examples to induce the knowledge, which can then be used to recommend algorithms for new data sets. The paper makes a contribution to both meta-learning and cost-sensitive machine learning approaches. Those both fields are not new, however, building a recommender that recommends the optimal case-sensitive approach for a given data problem is the contribution. The proposed solution is implemented in WEKA and evaluated by applying it on different data sets and comparing the results with existing studies available in the literature. The results show that a developed meta-learning solution produces better results than METAL, a well-known meta-learning system. The developed solution takes the misclassification cost into consideration during the learning process, which is not available in the compared project.

The proposed solution is implemented in WEKA and evaluated by applying it to different data sets and comparing the results with existing studies available in the literature. The results show that a developed meta-learning solution produces better results than METAL, a well-known meta-learning system.

The paper presents a major piece of new information in writing for the first time. Meta-learning work has been done before but this paper presents a new meta-learning framework that is costs sensitive.

This paper aims to deal with the force and position tracking problem when a robot performs a task in interaction with an unknown environment and presents a hybrid control strategy based on variable admittance control and fixed-time control.

A hybrid control strategy based on variable admittance control and fixed-time control is presented. Firstly, a variable stiffness admittance model control based on proportional integral and differential (PID) is adopted to maintain the expected force value during the task execution. Secondly, a fixed-time controller based on radial basis function neural network (RBFNN) is introduced to handle the model uncertainties and ensure the fast position tracking convergence of the robot system, while the singularity problem is also avoided by designing the virtual control variable with piecewise function.

Simulation studies conducted on the robot manipulator with two degrees of freedom have verified the superior performance of the proposed control strategy comparing with other methods.

A hybrid control scheme for robot–environment interaction is presented, in which the variable stiffness admittance method is adopted to adjust the interaction force to the desired value, and the RBFNN-based fixed-time position controller without singularity problem is designed to ensure the fast convergence of the robot system with model uncertainty.

Advanced driving assistance system (ADAS) has been applied in commercial vehicles. This paper aims to evaluate the influence factors of commercial vehicle drivers’ acceptance on ADAS and explore the characteristics of each key factors. Two most widely used functions, forward collision warning (FCW) and lane departure warning (LDW), were considered in this paper.

A random forests algorithm was applied to evaluate the influence factors of commercial drivers’ acceptance. ADAS data of 24 commercial vehicles were recorded from 1 November to 21 December 2018, in Jiangsu province. Respond or not was set as dependent variables, while six influence factors were considered.

The acceptance rate for FCW and LDW systems was 69.52% and 38.76%, respectively. The accuracy of random forests model for FCW and LDW systems is 0.816 and 0.820, respectively. For FCW system, vehicle speed, duration time and warning hour are three key factors. Drivers prefer to respond in a short duration during daytime and low vehicle speed. While for LDW system, duration time, vehicle speed and driver age are three key factors. Older drivers have higher respond probability under higher vehicle speed, and the respond time is longer than FCW system.

Few research studies have focused on the attitudes of commercial vehicle drivers, though commercial vehicle accidents were proved to be more severe than passenger vehicles. The results of this study can help researchers to better understand the behavior of commercial vehicle drivers and make corresponding recommendations for ADAS of commercial vehicles.

This paper aims to assess precise correlations between intermetallic compounds (IMCs) microstructure evolutions and the reliability of micro-joints with a Cu/SAC305solder/Ni structure using thermal shock (TS) tests.

This paper uses 200-µm pitch silicon flip chips with nickel (Ni) pads and stand-off height of approximately 60 µm, assembled on substrates with copper (Cu) pads. After assembly, the samples were subjected to air-to-air thermal shock testing from 55 to 125 per cent. The transfer time was less than 5 s, and the dwell time at each temperature extreme was 15 min. To investigate the microstructure evolution and crack growth, two samples were removed from the thermal shock chamber at 0, 400, 1,200, 2,000, 5,800 and 7,000 cycles.

The results showed that one (Cu, Ni)₆Sn₅/(Ni, Cu)₃Sn₄ dual-layer structure formed at the Ni pad interface of chip side dominates the micro-joints failure. This is because substantial (Ni, Cu)₃Sn₄ grain boundaries provide a preferential pathway for the catastrophic crack growth. Other IMCs microstructure evolutions that cause the prevalent joints failure as previously reported, i.e. thickened interfacial (Cu, Ni)₆Sn₅ and Ni₃P layer, and coarsened IMCs inside the solder matrix, only contributed to the occurrence of fine cracks. Moreover, the typical interfacial IMCs spalling triggered by thermally induced stress did not take place in this study, showing a positive impact in the micro-joint reliability.

As sustained trends toward multi-functionality and miniaturization of microelectronic devices, the joints size is required to be constantly scaled down in advanced packages. This arises a fact that the reliability of small-size joints is more sensitive to the IMCs because of their high volume proportion and greatly complicated microstructure evolutions. This paper evaluated precise correlations between IMCs microstructure evolutions and the reliability of micro-joints with a Cu/SAC305solder/Ni structure using TS tests. It found that one (Cu, Ni)₆Sn₅/(Ni, Cu)₃Sn₄ dual-layer structure formed at the Ni pad interface dominate the micro-joints failure, whereas other IMCs microstructure evolutions that cause the prevalent joints failure exhibited nearly negligible effects.

To date, intersectional feminist criminological enquiry concerned with exploring junctions of gender and ethnicity amongst incarcerated women, has mainly come from studies undertaken in western nations. In this chapter, we present findings from research undertaken in Thailand that explored incarcerated ethnic minority women’s backgrounds, situational contexts surrounding their criminalization and criminal justice system experiences, with particular attention paid to women’s time in prison. Our purpose was to examine how gender and ethnicity intersected, impacting the lived experiences of criminalized ethnic minority women before and during their incarceration. Findings revealed the ways in which these women are marginalized inside and outside prison walls. On the outside, the women struggled with patriarchal systems of power, both within and beyond their communities. They were subjugated as women and by discourses of ethnic othering. Under-education, poverty, living with state, community, familial and intimate partner violence, trauma, and other adversity were key aspects of the women’s pre-prison lives and created the contexts from which they came into conflict with the law. The women faced challenges in accessing justice and, once imprisoned, gender and ethnicity intersected in several domains, to impact their carceral experiences.