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This study aims to propose a calibration method to enhance the positioning accuracy in dual-robot collaborative operations, aiming to address the challenge of drilling hole spacing errors in spacecraft core cabin brackets that require an accuracy of less than 0.5 mm.

Initially, the cooperative error of dual robots is defined. Subsequently, an integrated model is constructed that encompasses the kinematic model errors of the dual robots, as well as the establishment errors of the base and tool frames. A calibration method for optimizing the cooperative accuracy of dual robots is proposed.

The application of the proposed method satisfies the collaborative drilling requirements for the spacecraft core cabin. The average cooperative positioning error of the dual robots was reduced from 0.507 to 0.156 mm, with the maximum value and standard deviation decreasing from 1.020 and 0.202 mm to 0.603 and 0.097 mm, respectively. Drilling experiments conducted on a core cabin simulator demonstrated that after calibration, the maximum hole spacing error was reduced from 1.219 to 0.403 mm, with all spacing errors falling below the 0.5 mm threshold, thus meeting the requirements.

This paper addresses the drilling accuracy requirements for spacecraft core cabins by using a calibration method to reduce the cooperative error of dual robots. The algorithm has been validated through experiments using ER 220 robots, confirming its effectiveness in fulfilling the drilling task requirements.

To enhance the fit, comfort and overall satisfaction of lower body attire for online shoppers, this study introduces a reclassification method of the lower body profiles of young females in complex environments, which is used in the framework of remote clothing mass customization.

Frontal and lateral photographs were collected from 170 females prior, marked as size M. Employing a salient object detection algorithm suitable for complex backgrounds, precise segmentation of body profiles was achieved while refining the performance through transfer learning techniques. Subsequently, a skeletal detection algorithm was employed to delineate distinct human regions, from which 21 pivotal dimensional metrics were derived. These metrics underwent clustering procedures, thus establishing a systematic framework for categorizing the lower body shapes of young females. Building upon this foundation, a methodology for the body type combination across different body parts was proposed. This approach incorporated a frequency-based filtering mechanism to regulate the enumeration of body type combinations. The automated identification of body types was executed through a support vector machine (SVM) model, achieving an average accuracy exceeding 95% for each defined type.

Young females prior to being marked as the same lower garment size can be further subdivided based on their lower body types. Participants' torso types were classified into barrel-shaped, hip-convex and fat-accumulation types. Leg profile shapes were categorized into slender-elongated and short-stocky types. The frontal straightness of participants’ legs was classified as X-shaped, I-shaped and O-shaped types, while the leg side straightness was categorized based on the knee hyperextended degree. The number of combinations can be controlled based on the frequency of occurrence of combinations of different body types.

This methodological advancement serves as a robust cornerstone for optimizing clothing sizing and enabling remote clothing mass customization in E-commerce, providing assistance for body type database and clothing size database management as well as strategies for establishing a comprehensive remote customization supply chain and on-demand production model.

The purpose of this paper is to design a climbing robot connected by a connecting rod mechanism to achieve multi-functional tasks such as obstacles crossing and climbing of power transmission towers.

A connecting rod type gripper has been designed to achieve stable grasping of angle steel. Before grasping, use coordination between structures to achieve stable docking and grasping. By using the alternating movements of two claws and the middle climbing mechanism, the climbing and obstacle crossing of the angle steel were achieved.

Through a simple linkage mechanism, a climbing robot has been designed, greatly reducing the overall mass of the robot. It can also carry a load of 1 kg, and the climbing mechanism can perform stable climbing. The maximum step distance of the climbing robot is 543 mm, which can achieve the crossing of angle steel obstacles.

A transmission tower climbing mechanism was proposed by analyzing the working environment. Through the locking ability of the screw nut, stable clamping of the angle steel is achieved, and a pitch mechanism is designed to adjust the posture of the hand claw.

In recent decades, interest in digital transformation (DX) within the architecture, engineering, and construction (AEC) industry has significantly increased. Despite the existence of several literature reviews on DX research, there remains a notable lack of systematic quantitative and visual investigations into the structure and evolution of this field. This study aims to address this gap by uncovering the current state, key topics, keywords, and emerging areas in DX research specific to the AEC sector.

Employing a holistic review approach, this study undertook a thorough and systematic analysis of the literature concerning DX in the AEC industry. Utilizing a bibliometric analysis, 3,656 papers were retrieved from the Web of Science spanning the years 1990–2023. A scientometric analysis was then applied to these publications to discern patterns in publication years, geographical distribution, journals, authors, citations, and keywords.

The findings identify China, the USA, and England as the leading contributors in the field of DX in AEC sector. Prominent keywords include “building information modeling”, “design”, “system”, “framework”, “adoption”, “model”, “safety”, “internet of things”, and “innovation”. Emerging areas of interest are “deep learning”, “embodied energy”, and “machine learning”. A cluster analysis of keywords reveals key research themes such as “deep learning”, “smart buildings”, “virtual reality”, “augmented reality”, “smart contracts”, “sustainable development”, “building information modeling”, “big data”, and “3D printing”.

This study is among the earliest to provide a comprehensive scientometric mapping of the DX field. The findings presented here have significant implications for both industry practitioners and the scientific community, offering a thorough overview of the current state, prominent keywords, topics, and emerging areas within DX in the AEC industry. Additionally, this research serves as an invaluable reference and guideline for scholars interested in this subject.

The purpose of this paper is to describe the design and development of “Pylon-Climber II”, a 5-DOF biped climbing robot (degree of freedom – DOF) for moving on the external surface of a tower and assisting the electricians to complete some maintenance tasks.

The paper introduces a pole-climbing robot, which consists of a 5-DOF mechanical arm and two novel grippers. The gripper is composed of a two-finger clamping module and a retractable L-shaped hook module. The robot is symmetrical in structure, and the rotary joint for connecting two arms is driven by a linear drive mechanism.

The developed prototype proved a new approach for the inspection and maintenance of the electricity pylon. The gripper can reliably grasp the angle bars with different specifications by using combined movement of the two-finger clamping module and the retractable L-shaped hook module and provide sufficient adhesion force for the Pylon-Climber II.

The clamping experiments of the gripper and the climbing experiments of the robot were carried out on a test tower composed of some angle bars with different specification.

This paper includes the design and development of a 5-DOF biped climbing robot for electricity pylon maintenance. The climbing robot can move on the external surface of the electric power tower through grasping the angle bar alternatively. The gripper that is composed of a two-finger gripping module and a retractable L-shaped hook module is very compact and can provide reliable adhesion force for the climbing robot.

This study investigated employees’ career planning in preparation for the impact of manufacturing transformation triggered by automation technology. Built on career construction theory, the purpose of this paper is to conceptualize career planning as an attempt to integrate oneself into the social environment. In this process of integration, career adaptability is a critical psychological resource for adaptation to anticipated changes.

Through an online survey, 476 participants answered questions regarding the following aspects: perceptions of the threats and opportunities posed by automation technology; career adaptability, that is, career-related concern, control, curiosity, and confidence in adapting to occupational transitions; and career plans and actions to address the challenge, including short-term job crafting behaviors and long-term career adjustment plan.

The results showed that opportunity and threat perceptions were associated with one’s job crafting behavior and long-term career adjustment plan and such relationships were moderated by career adaptability and work experience relevant to automation technologies. Specifically, career adaptability is a psychological resource helping individuals deal with perceived challenges, while relevant work experience moderated one’s strategies to catch opportunities.

This study contributes to the understanding of psychosocial determinants for better career planning in the midst of the industrial revolution. Policies that aim to prepare workers for the upcoming social transition may benefit from this study to leverage adaptive and proactive behaviors at a societal level.

To predict the price of battery-grade lithium carbonate accurately and provide proper guidance to investors, a method called MFTBGAM is proposed in this study. This method integrates textual and numerical information using TCN-BiGRU–Attention.

The Word2Vec model is initially employed to process the gathered textual data concerning battery-grade lithium carbonate. Subsequently, a dual-channel text-numerical extraction model, integrating TCN and BiGRU, is constructed to extract textual and numerical features separately. Following this, the attention mechanism is applied to extract fusion features from the textual and numerical data. Finally, the market price prediction results for battery-grade lithium carbonate are calculated and outputted using the fully connected layer.

Experiments in this study are carried out using datasets consisting of news and investor commentary. The findings reveal that the MFTBGAM model exhibits superior performance compared to alternative models, showing its efficacy in precisely forecasting the future market price of battery-grade lithium carbonate.

The dataset analyzed in this study spans from 2020 to 2023, and thus, the forecast results are specifically relevant to this timeframe. Altering the sample data would necessitate repetition of the experimental process, resulting in different outcomes. Furthermore, recognizing that raw data might include noise and irrelevant information, future endeavors will explore efficient data preprocessing techniques to mitigate such issues, thereby enhancing the model’s predictive capabilities in long-term forecasting tasks.

The price prediction model serves as a valuable tool for investors in the battery-grade lithium carbonate industry, facilitating informed investment decisions. By using the results of price prediction, investors can discern opportune moments for investment. Moreover, this study utilizes two distinct types of text information – news and investor comments – as independent sources of textual data input. This approach provides investors with a more precise and comprehensive understanding of market dynamics.

We propose a novel price prediction method based on TCN-BiGRU Attention for “text-numerical” information fusion. We separately use two types of textual information, news and investor comments, for prediction to enhance the model's effectiveness and generalization ability. Additionally, we utilize news datasets including both titles and content to improve the accuracy of battery-grade lithium carbonate market price predictions.

With the popularization of sustainable concepts, how to transform into a sustainable supply chain has received widespread attention in practice. Under this circumstance, this paper aims to propose a theoretical framework of sustainable supply chain transformation (SSCT) from a perspective of resource identification and utilization, investigates resources/capabilities that can be used to promote SSCT and explores how to use resources/capabilities to achieve SSCT effectively.

An inductive multi-case analysis is applied to this paper. Four state-owned/non-state-owned enterprises from the manufacturing sector are selected as the research objectives, which are all leaders in the industry based on the 2022 China TOP 500 Enterprises Ranking. Meanwhile, to guarantee the diversities of enterprises, the four selected enterprises are respectively positioned in upstream and downstream of the supply chain.

A theoretical framework of SSCT is proposed with following research findings: (1) Technology resources, facilities and equipment resources, and business process reengineering capability are the key resources/capabilities to promote SSCT. (2) From the supply chain structure perspective, there exists a leader-participant structure in SSCT. The enterprise with dominant resources/capabilities should actively transfer to a SSCT leader. From the supply chain function perspective, specific sustainability assessment indicators and special teams are two necessary settings for SSCT. From the supply chain lifecycle perspective, SSCT should be promoted in a phased manner and dynamically adjusted in each stage. (3) Digital transformation degree and enterprise ownership play a moderating role in the implementation of strategies.

This paper proposes a conceptual framework of SSCT based on the resource orchestration perspective, which provides decision support for enterprises in practice.

The purpose of this paper is to describe the design and development of “Pylon-Climber”, a pole climbing robot (PCR) for climbing along the corner columns of electricity pylon and assisting the electricians to complete maintenance tasks.

Introduces a PCR that is composed of a simple climbing mechanism and two novel grippers. The gripper consists of two angle-fixed V-blocks, and the size of V-block is variable. The clamping method of the angle bar meets the requirement of the force closure theorem. The whole design adopts symmetrical design ideas.

The developed prototype proved possibility of application of PCRs for inspection and maintenance of pylon. The novel gripper can provide enough adhesion force for climbing robot.

The robot is successfully tested on a test tower composed of different specification steel angles, oblique ledges and overlapping steel struts.

Design and development of a novel climbing assistive robot for pylon maintenance. The robot is able to climb along the column of electricity pylon and pass all obstacles. The gripper can reliably grasp the angle bar with different specification and overlapping steel struts from multiple directions.

This study aims to examine distinct influences of two dimension job stress on job satisfaction and the moderating effects of guanxi-oriented attitude on the relationship between job stress and job satisfaction under cognitive appraisal theory and transactional theory.

In this study, surveys are conducted among state-owned younger bank employees. The author uses the scale of job challenge stress and hindrance stress developed among Chinese younger bank employees to measure the two dimension job stress. After demonstrating guanxi-relative concepts, the moderating effects of guanxi-oriented attitude are examined in this study.

The results demonstrate that guanxi-oriented attitude does not significantly moderate the influence of challenge stress on job satisfaction, while it significantly moderates the noxious influence of hindrance stress on job satisfaction. Theoretical contributions are also discussed.

First, this study suggests specific procedures to conduct hierarchical regression analysis and confirms the effects by parameters. It also proposes and summarizes specific procedures on how to calculate regression equations and draw regression lines to check the interaction received from the hierarchical regression analysis visually. Second, based on cognitive appraisal theory, guanxi-oriented attitude, a Chinese indigenous cognitive concept, was verified in this study. According to the importance of guanxi in Chinese society, the paper shows that employees who value guanxi more will buffer the noxious effects of job stress. Trainings and counseling should be designed to regulate the normal guanxi-oriented-related cognition.