Search results

Robotic arms play a crucial role in various industrial operations, such as sorting, assembly, handling and spraying. However, traditional robotic arm control algorithms often struggle to adapt when faced with the challenge of dynamic obstacles. This paper aims to propose a dynamic obstacle avoidance method based on reinforcement learning to address real-time processing of dynamic obstacles.

This paper introduces an innovative method that introduces a feature extraction network that integrates gating mechanisms on the basis of traditional reinforcement learning algorithms. Additionally, an adaptive dynamic reward mechanism is designed to optimize the obstacle avoidance strategy.

Validation through the CoppeliaSim simulation environment and on-site testing has demonstrated the method's capability to effectively evade randomly moving obstacles, with a significant improvement in the convergence speed compared to traditional algorithms.

The proposed dynamic obstacle avoidance method based on Reinforcement Learning not only accomplishes the task of dynamic obstacle avoidance efficiently but also offers a distinct advantage in terms of convergence speed. This approach provides a novel solution to the obstacle avoidance methods for robotic arms.

Continuous fiber reinforced thermoplastic composites (CFRTPCs) are becoming more significant in industrial applications but are limited by the high cost of molds, the manufacturing boundedness of complex constructions and the inability of special fiber alignment. The purpose of this paper is to put forward a novel three-dimensional (3D) printing process for CFRTPCs to realize the low-cost rapid fabrication of complicated composite components.

For this purpose, the mechanism of the proposed process, which consists of the thermoplastic polymer melting, the continuous fiber hot-dipping and the impregnated composites extruding, was investigated. A 3D printing equipment for CFRTPCs with a novel composite extrusion head was developed, and some composite samples have been fabricated for several mechanical tests. Moreover, the interface performance was clarified with scanning electron microscopy images.

The results showed that the flexural strength and the tensile strength of these 10 Wt.% continuous carbon fiber (CCF)/acrylonitrile-butadiene-styrene (ABS) specimens were improved to 127 and 147 MPa, respectively, far greater than the one of ABS parts and close to the one of CCF/ABS (injection molding) with the same fiber content. Moreover, these test results also exposed the very low interlaminar shear strength (only 2.81 MPa) and the inferior interface performance. These results were explained by the weak meso/micro/nano scale interfaces in the 3D printed composite parts.

The 3D printing process for CFRTPCs with its controlled capabilities for the orientation and distribution of fiber has great potential for manufacturing of load-bearing composite parts in the industrial circle.

Hydrostatic thrust bearing is a key component of the vertical CNC machining equipment, and often results in friction failure under the working condition of high speed and heavy load. The lubricating oil film becomes thin or breaks because of high speed and heavy load and it affects the high precision and stable operation of the vertical CNC machining equipment; hence, it is an effective way of avoiding friction failure for achieving the oil film shape prediction

For the hydrostatic thrust bearing with double rectangular cavities, researchers solve the deformation of the friction pairs in hydrostatic bearing by using the computation of hydrodynamics, elasticity theory, finite element method and fluid-thermal-mechanical coupled method. The deformation includes heat deformation and elasticity deformation, the shape of gap oil film is got according to the deformation of the friction pairs in hydrostatic bearing, and gets the shape of gap oil film, and determines the influencing factors and laws of the oil film shape, and achieves the prediction of oil film shape, and ascertains the mechanism of friction failure. An experimental verification is carried out.

Results show that the deformation of the rotational workbench is upturned along its radial direction under the working condition of high speed and heavy load. However, the deformation of the base is downturned along its radial direction and the deformation law of the gap oil film along the radius direction is estimated; the outer diameter is close but the inner diameter is divergent wedge.

The conclusion can provide a theoretical basis for the oil film control of hydrostatic thrust bearing and improve the stability of vertical CNC machining equipment.

The existing literature has a lack of modeling of procedural fairness concerns in the supply chain level. This paper aims to investigate how procedural fairness concerns affect channel decisions, performance and coordination.

This paper considers a supply chain consisting of one supplier and one retailer who have procedural fairness concerns in a classic Stackelberg game setting. The model is set in sales promotional environment. According to the existing literature, engagement is used to depict fair process. Some findings are made through analyzing respective decisions of the supplier and the retailer under the influence of procedural fairness concerns.

The results show that the channel efficiency can be improved when the retailer exhibits procedural fairness concerns, but if the aversion to unfair process exceeds a certain threshold, the retailer cannot benefit from it. Besides, the retailer profits more when he cares about distributional fairness, although the whole channel surplus can be improved by procedural fairness concerns.

This is the first paper to study the influences of procedural fairness concerns on supply chain decisions and channel performance. Finally, a mechanism combining a wholesale price contract with slotting allowances is proposed to coordinate the supply chain.

This study aims to investigate the factors responsible for substrate cracking reliability problem in through-glass vias (TGVs), which are critical components for glass-based 2.5 D integration.

Numerical models were used to examine the driving force for substrate cracking in glass interposers due to stress coupling during heating. An analytical solution was used to demonstrate how the energy release rate (ERR) for the glass substrate cracking is affected by the via design and the mismatch in thermal strain. Then, the numerical models were implemented to investigate the design factors effects, such as the pitch distance, via diameter, via pattern, via design, effect from a stress buffer layer and the interposer materials selection on the susceptibility to substrate cracking.

ERR for substrate cracking was found to be directly proportional to the via diameter and the thermal mismatch strain. When a via pattern is implemented for high-density integration, a coupling in the stress fields was identified. This coupling effect was found to depend on the pitch distance, the position of the vias, and the via arrangement, suggesting a via pattern-dependent reliability behavior for glass interposers. Changing the design of the via to an annular shape or a substrate-cored via was found to be a promising approach to reduce the susceptibility to substrate cracking compared to a fully filled solid via. Also, the use of a stress buffer layer, an encouraging design prospect presented for the first time for TGVs in this study, was found to significantly reduce cracking. Finally, alternative via and substrate materials showed lower tendency for substrate cracking, indicating that the reliability of glass interposers can be further enhanced with the implementation of such new materials.

This study signifies the first attempt to comprehensively evaluate the susceptibility to crack formation in glass interposers during heating. Therefore, this study provides new perspectives on how to achieve a significant potential reliability improvement for TGVs.

Glass is a promising interposer substrate for 2.5 D integration; yet detailed analysis of the interfacial reliability of through-glass vias (TGVs) has been lacking. The purpose of this paper is to investigate the design and material factors responsible for the interfacial delamination in TGVs and identify methods to improve reliability.

The interfacial reliability of TGVs is studied both analytically and numerically. An analytical solution is presented to show the dependence of the energy release rate (ERR) for interfacial delamination on the via design and the thermal mismatch strain. Then, finite element analysis (FEA) is used to investigate the influence of detailed design and material factors, including the pitch distance, via aspect ratio, via geometry and the glass and via materials, on the susceptibility to interfacial delamination.

ERR for interfacial delamination is directly proportional to the via diameter and the thermal mismatch strain. Thinner wafers with smaller aspect ratios show larger ERRs. Changing the via geometry from a fully filled via to an annular via leads to lower ERR. FEA results also show that certain material combinations have lower thermal mismatch strains, thus less prone to delamination.

The results and approach presented in this paper can guide the design and development of more reliable 2.5 D glass interposers.

This paper represents the first attempt to comprehensively evaluate the impact of design and material selection on the interfacial reliability of TGVs.

The evaluations of the magnetohydrodynamics angular rate sensor (MHD ARS) in its applications necessitate further improvements in the sensor’s dynamic measurement ability. The magnetic field of the MHD ARS is a key factor in the sensor’s modeling and error analysis. The aim of this study is to illustrate the influence of a non-uniform magnetic field on the sensor.

Numerical simulation is made using ANSYS FLUNET with the magnetic field calculated by 3D-Magnetostatic. The comparison of the simulation results between uniform and non-uniform magnetic fields is made to reveal and explain the effects of magnetic field inhomogeneity (MFI) on the flow and electric field in detail. Two different structures with different MFIs are designed to confirm the MFI effect on the sensor’s output in simulation and experiment. A cross-correlation experiment and an adaptive filter are carried out to extract the signal to identify the error of the sensor output caused by MFI.

The MFI effect on the flow field in MHD ARS is found to be insignificant, while its effect on the electric potential is considerable. The comparisons between two kinds of MHD ARS in numerical simulation and experiment show that the MFI effect on the sensor error can be identified by fitting the sensor output. The deviation is mainly generated at the peaks and valleys of an angular vibration.

The study of the MHD ARS under the influence of a non-uniform magnetic field can offer an understanding of the MFI effect on the sensor and an evaluation method of the sensor error caused by the MFI effect.

This study aims to discuss the formation mechanism of members’ emotional attachment to virtual travel communities from an online–offline perspective, focusing on the role of offline tourism experiences.

A questionnaire was designed to survey active travel enthusiast clubs that hold frequent offline tourism activities. A structural equation modeling method was used to estimate the model and test the research hypotheses.

Results demonstrated that offline travel experiences positively influenced online community attachment (i.e., community dependence and identity), and this effect was more pronounced than that of one’s sense of community (i.e., belonging, trust and immersion) on community attachment. Therefore, compared with online interaction, offline travel experiences played a greater part in strengthening virtual community attachment.

The study presents a pioneering effort on understanding how offline activities help shape the community attachment to virtual communities.

本研究从线上-线下的角度探讨了人们对虚拟旅行社区的情感依恋形成机制, 着重关注线下旅游体验的作用。

本研究设计了问卷, 对经常举办线下旅游活动的驴友俱乐部进行了调查。采用结构方程建模方法估计模型并验证研究假设。

结果表明, 线下旅游体验积极地影响着线上社区依恋, 并且这种影响比社区感对社区依恋的影响更为显著。因此, 相较于线上互动, 线下旅游体验在增强虚拟社区依恋方面起到了更大的作用。

本研究首次探讨了线下活动如何帮助塑造虚拟社区成员对虚拟社区的依恋。

In this research, the authors aim to investigate the impact of product display quantity on consumers' online purchase intention through the diminished pain of payment, in light of signaling theory and mental accounting theory. Additionally, the authors test the role of price in this psychological mechanism.

The authors use a combination of online studies and field experiments to test our predictions. Four online studies are conducted to test the main effect of product display quantity on purchase intention (Studies 1A and 1B), the mediating effect of the diminished pain of payment (Study 2), and the moderating role of price (Study 3). Two field experiments are conducted to strengthen the robustness of our findings.

The findings suggest that product display quantity has a significantly positive impact on purchase intention, mediated by the diminished pain of payment, and this effect is moderated by price.

This is the first study to investigate the effect of product display quantity on online purchase intention. This research advances the discussion of product display quantity, which provides retailers and consumers with a convenient way to communicate with each other and leads to a more relaxed purchase experience.

Document management is growing in importance proportionate to the growth of unstructured data, and its applications are increasing from process benchmarking to customer relationship management and so on. The purpose of this paper is to improve important components of document management that is keyword extraction and document clustering. It is achieved through knowledge extraction by updating the phrase document matrix. The objective is to manage documents by extending the phrase document matrix and achieve refined clusters. The study achieves consistency in cluster quality in spite of the increasing size of data set. Domain independence of the proposed method is tested and compared with other methods.

In this paper, a synset-based phrase document matrix construction method is proposed where semantically similar phrases are grouped to reduce the dimension curse. When a large collection of documents is to be processed, it includes some documents that are very much related to the topic of interest known as model documents and also the documents that deviate from the topic of interest. These non-relevant documents may affect the cluster quality. The first step in knowledge extraction from the unstructured textual data is converting it into structured form either as term frequency-inverse document frequency matrix or as phrase document matrix. Once in structured form, a range of mining algorithms from classification to clustering can be applied.

In the enhanced approach, the model documents are used to extract key phrases with synset groups, whereas the other documents participate in the construction of the feature matrix. It gives a better feature vector representation and improved cluster quality.

Various applications that require managing of unstructured documents can use this approach by specifically incorporating the domain knowledge with a thesaurus.

Experiment pertaining to the academic domain is presented that categorizes research papers according to the context and topic, and this will help academicians to organize and build knowledge in a better way. The grouping and feature extraction for resume data can facilitate the candidate selection process.

Applications like knowledge management, clustering of search engine results, different recommender systems like hotel recommender, task recommender, and so on, will benefit from this study. Hence, the study contributes to improving document management in business domains or areas of interest of its users from various strata’s of society.

The study proposed an improvement to document management approach that can be applied in various domains. The efficacy of the proposed approach and its enhancement is validated on three different data sets of well-articulated documents from data sets such as biography, resume and research papers. These results can be used for benchmarking further work carried out in these areas.