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The paper aims to study the challenges and solutions of city logistics in the new retail era. The new retail, which is characterized by omni-channel, fragmented orders and decentralized 2C distribution, is becoming the mainstream of the retail industry worldwide. In order to achieve a comprehensive breakthrough in new retail, the change of order fulfillment mode is the most noteworthy issue. The aim of this paper is to design a city logistics operation model for new retail and verify its feasibility and efficiency.

A physical internet (PI) enabled two-tier city logistics solution is proposed by redefining the key facilities in city logistics with the PI concept. A “Container-as-a-Warehouse” operation mode is designed to provide a more flexible store and transfer solution. A mathematical model of the proposed solution is established. An adaptive large neighborhood search (ALNS) is designed based upon an iterative procedure, which ensures consistent and optimal results.

To quantitatively assess the feasibility of the proposed solution, a computational experiment is designed to compare the performance of the proposed model against the conventional two-tier city logistics operation. The effects of geographical location pattern, utilization of PI-hub as well as the fluctuation of customer orders are analyzed. The results show that the PI-enabled city logistics is more advantageous than the conventional solution.

This study does not consider the impact of new technologies in city logistics; for example, the replenishment problem of unmanned vending machines and the charging problem of electric vehicles.

The proposed PI-enabled solution and analysis results in this paper have positive guiding significance for future practical application.

Based on the concept of PI, this paper proposes an innovative and practical operation model to solve the city logistics challenges.

Esthetic trend changes with the development of society and cultural differences. A minimizer bra designed to make breasts appear smaller is now popular with large-breasted women in China. To conform to the requirements of modern aesthetics in China, this paper aims to investigate vital features of breast appearance that influence people’s subjective evaluation of breast size and analyze how bra design parameters affect breast shape and make breasts appear smaller.

This study used 3D scanning technology and reverse engineering software to obtain objective breast measurements in detail. A subjective evaluation experiment was conducted to evaluate the overall performance of seven minimizer bras compared to a basic comparison bra. Around 20 design parameters of 8 sample bras were identified to make a further study about the correlation between bra design features and breast shaping effect. To gain a deeper understanding of how bras interact with breast tissue, this study presented heat maps of the breast surface to visualize the deformation of breast shape.

Nine breasts' characteristics, such as the distance between bust points, breast depth, outer breast curvature and slope, etc. have been determined to be highly correlated with the visual reduction effect of breasts. In addition, for the bras in this experiment, the high-performance bra for women with large breasts tends to have a wider side panel, a wider under band, higher gore and a stronger transverse rigidity of the bra cup. According to the observation of heat maps of the breast surface, soft full-figure bras provide a wider range of compression to the breasts and effectively flatten the breasts.

This paper first aimed at the need to shape the ideal breast appearance for large-breasted women and make a further study of several hot-selling minimizer bras in China. The suggestions given in this paper help lingerie manufacturers better understand how design features of bras can affect their shaping effect and improve the wearing effect of minimizer bras for large-breasted women.

The purpose of this paper is to generate quantitative managerial insights for the improvement of the energy-saving potential and the coordinated development between economic growth and environmental protection.

A novel data envelopment analysis (DEA) model, based on the classical DEA theory, is developed from the perspective of emission reduction.

The empirical results indicate that China’s overall environmental efficiency is low and that there is huge improvement space for energy saving. Under the concerns of emission reduction, the energy-saving potential of the central region exceeds that of both the eastern and western regions. With regard to water, electricity and gas consumption, the electricity-saving potential exceeds the potential for both water saving and gas saving.

Previous studies rarely focused on the energy-saving potential, while considering environmental pollution. This paper applies a novel DEA method to evaluate the energy-saving potential of 30 Chinese provinces for 2015 with a focus on emission reduction concerns. Furthermore, both regional differences and energy type differences of the saving potential were analyzed.

Existing hospital building operations involve numerous information technology applications and complex building systems; therefore, an intelligent facility management (FM) platform is required to ensure their continuous operation. To address the persistent issues of data silos, inefficient data interoperability, and workflow incoordination that have been identified in the current body of FM practice and literature, the present study develops a data-asset (DA) centric FM platform specifically designed for hospital buildings.

This study proposes a semi-customized approach to develop the DA-centric FM platform for hospital buildings. To elucidate the precise function requirements of the hospital FM platform, focus group interviews are employed. By seamlessly integrating the as-built BIM model, IoT sensor data and FM workflow data, the BIM-based DA model with a data transfer mechanism is developed. The development of the FM platform with function modules in a case study is guided by a five-tier architecture and the coordination theory (CT). The case study provides an in-depth introduction to the applications of DA management, space management and maintenance management modules.

The capabilities of the developed DA-centric hospital FM platform are validated through the case application and user satisfaction survey, which assess data quality, automation level, operation efficiency, flexibility and functionality. For hospital FM activities, this DA-centric FM platform realizes data integration and seamless transformation, optimizes workflow coordination and enhances operation performance.

The initial scholarly contribution is the establishment of the BIM-based DA model, which serves as the data middle platform for continuous data integration, transmission and sharing within the FM platform. Subsequently, under the guidance of the CT, the business process of function modules is designed, improving the intra-module and inter-module workflow coordination. The developed DA-centric FM system along with its performance benchmarking application, assists facility managers and decision-makers in implementing smart operations for hospital buildings and achieving the management goals of safety, efficiency, energy savings and convenience.

The application of industrial robots in modern production is becoming increasingly widespread. In the context of flexible production lines, quickly and accurately identifying and grasping specified workpieces is particularly important. This study aims to propose a grasping scheme that combines traditional methods with deep learning to improve grasping accuracy and efficiency.

First, a dataset generation method is proposed, which constructs a point cloud dataset close to the real scene without the need for extensive data collection. Then, the 3D object detection algorithm PointPillars is improved based on the features of the scene point cloud, allowing for the analysis of part poses to achieve grasping. Finally, a grasp detection strategy is proposed to match the optimal grasp pose.

Experimental results show that the proposed method can quickly and easily construct high-quality datasets, significantly reducing the time required for preliminary preparation. Additionally, it can effectively grasp specified workpieces, significantly improving grasping accuracy and reducing computation time.

The main contribution of this paper is the integration of a novel dataset generation method, improvements to the PointPillars algorithm for 3D object detection and the development of an optimal grasp detection strategy. These advancements enable the grasping system to handle real-world scenarios efficiently and accurately, demonstrating significant improvements over traditional methods.

The purpose of this paper is to investigate the wetting behaviors of Sn-5Sb-CuNiAg solders on copper substrates in different soldering processes and the effects of alloying elements on the wettability.

Sn-5Sb-CuNiAg solder balls (750 µm in diameter) were spread and wetted on 40 × 40 × 1 mm copper plates, in different fluxes, soldering temperatures and time. The contact angles were obtained by a home-made measuring instrument. The samples were polished and deep etched before analyzed by scanning electron microscopy. Energy dispersive X-ray spectroscopy was used to identify the composition of the joints.

The effects of different soldering processes and alloying elements on the wetting behaviors of Sn-5Sb-CuNiAg solders on copper substrates were calculated and expounded. The rosin-based flux could effectively remove oxidation layers and improve the wettability of Sn-5Sb-CuNiAg solders. Then with the increase of soldering temperature and time, the contact angles decreased gradually. The soldering processes suited for Sn-5Sb-CuNiAg solders were RMA218, 280°C and 30 s. Considered the effects of alloying elements, the wettability of Sn-5Sb-0.5Cu-0.1Ni-0.5Ag was relatively favorable on copper substrates. Besides, Ni could accumulate at the solder/Cu interface and form a jagged (Cu,Ni)6Sn5 IMC.

This work was carried out with our handmade experiment equipment and the production of the quinary lead-free solder alloy used in wetting tests belongs to us. The investigated Sn-5Sb-CuNiAg alloys exhibited higher melting point and preferable wettability, that was one of the candidates for high-temperature lead-free solders to replace high-Pb solders, and applied extremely to high temperature and frequency working environments of the third-generation semiconductors components, with a greater potential research and development value.

The aim of this paper is to solve the problem of low accuracy of traditional fatigue crack growth (FCG) prediction methods.

The GMSVR model was proposed by combining the grey modeling (GM) and the support vector regression (SVR). Meanwhile, the GMSVR model parameter optimal selection method based on the artificial bee colony (ABC) algorithm was presented. The FCG prediction of 7075 aluminum alloy under different conditions were taken as the study objects, and the performance of the genetic algorithm, the particle swarm optimization algorithm, the n-fold cross validation and the ABC algorithm were compared and analyzed.

The results show that the speed of the ABC algorithm is the fastest and the accuracy of the ABC algorithm is the highest too. The prediction performances of the GM (1, 1) model, the SVR model and the GMSVR model were compared, the results show that the GMSVR model has the best prediction ability, it can improve the FCG prediction accuracy of 7075 aluminum alloy greatly.

A new prediction model is proposed for FCG combined the non-equidistant grey model and the SVR model. Aiming at the problem of the model parameters are difficult to select, the GMSVR model parameter optimization method based on the ABC algorithm was presented. the results show that the GMSVR model has better prediction ability, which increase the FCG prediction accuracy of 7075 aluminum alloy greatly.

With the rapid development of the 3C industry, the problem of automated operation of 3C wire is becoming increasingly prominent. However, the 3C wire has high flexibility, and its deformation is difficult to model and control. How to realize the automation operation of flexible wire in 3C products is still an important issue that restricts the development of the 3C industry. Therefore, this paper designs a system that aims to improve the automation level of the 3C industry.

This paper designed a visual servo control system. Based on the perception of the flexible wire, a Jacobi matrix is used to relate the deformation of the wire to the action of the robot end; by building and optimizing the Jacobi matrix, the robot can control the flexible wire.

By using the visual servo control system, the shape and deformation of the flexible wire are perceived, and based on this, the robot can control the deformation of the flexible wire well. The experimental environment was built to evaluate the accuracy and stability of the system for controlling the deformation of the flexible wire.

An image-based visual servo system is proposed to operate the flexible wire, including the vision system, visual controller and joint velocity controller. It is a scheme suitable for flexible wire operation, which has helped to automate flexible wire-related industries. Its core is to correlate the motion of the robot end with the deformation of the flexible wire through the Jacobian matrix.