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Leading error in line laser weld seam tracking significantly affects tracking accuracy. This paper aims to propose an accurate and reliable compensation method without increasing system complexity for weld seam tracking to improve tracking precision.

Based on the line laser seam tracking method, the seam image is simultaneously captured to obtain the angle offset of the seam relative to the sensor direction, which is then combined with the leading distance to calculate the leading error. The two sensing methods use different wavelengths and are captured simultaneously by a color industrial camera. The images of the two different wavelengths can be separated by extracting the RGB components, and the compensated tracking results are obtained after image processing.

The results of static positioning experiment indicate that the average absolute error in weld seam positioning is reduced to 0.099 mm after compensation. The real-time tracking experiments demonstrate that the proposed method preserves tracking accuracy even with changes in the sensor’s angle of deviation during welding, with the average absolute error being 0.248 mm. This method effectively enhances the precision of line laser weld seam tracking when the sensor exhibits a deviation relative to the welding direction.

By using the dual-sensing and dual-wavelength method for leading error compensation, the method effectively addresses the leading error issue while maintaining the advantages of the line laser seam tracking method.

This study aims to address the challenge of the real-time state of charge (SOC) estimation for lithium-ion batteries in robotic systems, which is critical for monitoring remaining battery power, planning task execution, conserving energy and extending battery lifespan.

The authors introduced an optimal observer based on adaptive dynamic programming for online SOC estimation, leveraging a second-order resistor–capacitor model for the battery. The model parameters were determined by fitting an exponential function to the voltage response from pulse current discharges, and the observer's effectiveness was verified through extensive experimentation.

The proposed optimal observer demonstrated significant improvements in SOC estimation accuracy, robustness and real-time performance, outperforming traditional methods by minimizing estimation errors and eliminating the need for iterative steps in the adaptive critic and actor updates.

This study contributes a novel approach to SOC estimation using an optimal observer that optimizes the observer design by minimizing estimation errors. This method enhances the robustness of SOC estimation against observation errors and uncertainties in battery behavior, representing a significant advancement in battery management technology for robotic applications.

This paper aims to investigate the differences in hot corrosion behavior of the GTD222 superalloy and TiC/GTD222 composite in a mixed salt of 75% Na₂SO₄ and 25% K₂SO₄ at 900°C.

The GTD222 superalloy and TiC/GTD222 nickel-based composite were prepared using selective laser melting (SLM). Subsequently, the hot corrosion behavior of the two alloys was systematically investigated in a salt mixture consisting of 75% Na₂SO₄ and 25% K₂SO₄ (Wt.%) at 900°C.

The TiC/GTD222 composite exhibited better hot corrosion resistance compared to the GTD222 superalloy. First, the addition of alloying elements led to the formation of a protective oxide film on the TiC/GTD222 composites 20 h before hot corrosion. Second, TiC/GTD222 composite corrosion surface has a higher Ti content, after 100 h of hot corrosion, the composite corrosion surface Ti content of 10.8% is more than two times the GTD222 alloy 4% Ti. The Ti and Cr oxides are tightly bonded, effectively resisting the erosion of corrosive elements.

The hot corrosion behavior of GTD222 superalloy and TiC/GTD222 composites prepared by SLM in a mixed salt of 75% Na₂SO₄ and 25% K₂SO₄ was studied for the first time. This study provides insights into the design of high-temperature alloys resistant to hot corrosion.

Intelligent new energy vehicles (INEVs) are becoming the competitive hotspot for the automobile industry. The major purpose of this study is to determine how to increase innovation efficiency through knowledge sharing and technology spill between new energy vehicle (NEV) enterprises and technology enterprises. This will help to improve the core competence of the automobile industry in China. Also, it serves as a guide for the growth of other strategic.

The authors construct a tripartite evolutionary game model to study the cross-border cooperative innovation problem. Firstly, the payment matrix of NEV enterprise, technology enterprise and government is established, and the expected revenue of each participant is determined. Then, the replication dynamic equations and evolutionary stability strategies are analyzed. Finally, the theoretical research is validated through numerical simulation.

Results showed that: (1) An optimal range of revenue distribution coefficient exists in the cross-border cooperation. (2) Factors like research and development (R&D) success rate, subsidies, resource and technology complementarity, and vehicles intelligence positively influence the evolution towards cooperative strategies. (3) Factors like technology spillover risk cost inhibit the evolution towards cooperative strategies. To be specific, when the technology spillover risk cost is greater than 2.5, two enterprises are inclined to choose independent R&D, and the government chooses to provide subsidy.

The research perspective and theoretical analysis are helpful to further explore the cross-border cooperation of the intelligent automobile industry. The findings suggest that the government can optimize the subsidy policy according to the R&D capability and resource allocation of automobile industry. Moreover, measures are needed to reduce the risk of technology spillovers to encourage enterprise to collaborate and innovate. The results can provide reference for enterprises’ strategic choice and government’s policy making.

The INEV industry has become an important development direction of the global automobile industry. However, there is limited research on cross-border cooperation of INEV industry. Hence, authors construct a tripartite evolutionary game model involving NEV enterprise, technology enterprise and the government, and explore the relationship of cooperation and competition among players in the INEV industry, which provides a new perspective for the development of the INEV industry.

Purpose: This chapter aims to evaluate the significant impact of Gandhian values on sustainable consumption behaviour (SCB) by applying the value-attitude-behaviour (VAB) framework. This chapter contributes by incorporating Gandhian values as one influencing factor for SCB.

Need for the Study: Values are considered as guiding principles in people’s lives. Studies suggest that values and other social and psychological factors can be vital in determining consumers’ behaviour towards sustainable consumption. There needs to be more empirical research on consumer behaviour facets of sustainable consumption for markets in India.

Methodology: The study uses partial least square structural equation modelling to empirically test proposed hypotheses and the research model of the relationship. The study results are based on data collected by administering a survey through a questionnaire confined to India.

Findings: The results indicated that Gandhian values, attitude, and sustainable consumption intention significantly influence SCB. Intention acts as a mediator between both outward and inward environmental attitudes and behaviour. The study provides directions for further research.

Practical Implications: This research study is helpful for researchers, marketers, and policymakers.

This study aims to examine the acceptance of adaptive learning (AL) amongst construction professionals in Singapore. It seeks to compare their perceptions and attitudes with those of professionals from other industries to assess the rate of AL adoption in the construction sector. Furthermore, the study aims to identify the factors influencing construction professionals’ intention to adopt AL technologies.

A questionnaire survey was conducted with 188 construction professionals and 153 non-construction professionals. By employing the extended unified theory of acceptance and use of technology (UTAUT2) and the general extended technology acceptance model for e-learning (GETAMEL), this study also explored factors influencing construction professionals’ behavioural intention (BI) towards AL adoption. An SEM-machine learning approach facilitated the evaluation of the factors’ influence on BI.

A comparative analysis of the data found that construction professionals’ intention to use AL surpassed 75%, which had no significant difference with professionals from other industries. The findings revealed that learning value (LV) and self-efficacy (SE) were statistically significant predictors of construction professionals’ intentions to use AL. Furthermore, a supervised machine learning analysis identified performance expectancy (PE) as a crucial factor in predicting these intentions.

The study’s focus on self-reported intentions and a specific demographic limits its generalisability; further research should examine actual usage across diverse cultures.

The results offered insights into construction professionals’ perceptions and attitudes towards AL adoption, guiding the integration of AL into construction professional development.

This paper addresses a recognised gap by examining construction professionals’ perceptions and attitudes towards adopting AL.

This paper aims to explore the effectiveness of customer inoculation strategies in the context of AI service failures in the hospitality and tourism industries. Furthermore, it examines how these strategies can enhance customer complaint behavior and satisfaction with service recovery, thereby improving the overall service experience.

Four distinct studies were conducted: Study 1 investigated the influence of customer inoculation on complaint behavior post-AI service failure. Study 2 assessed the impact of service remedies on customer satisfaction. Study 3 explored the implications of initial purchase and usage intentions. Finally, Study 4 validated the findings using a large-scale online survey.

The results indicated that customer inoculation significantly increases customer complaint behavior and satisfaction with service remedies following AI service failures. They also showed that this relationship is mediated by psychological distance. Furthermore, customer inoculation positively affects initial purchase and usage intentions, demonstrating effectiveness at various customer engagement stages.

This study enriches the literature on AI hospitality service failure and recovery by introducing the novel concept of customer inoculation. Additionally, it significantly contributes to the inoculation theory literature, which covers diverse fields. Practically, this study proposes an efficient and low-cost strategy for marketers.

This study introduces the concept of customer inoculation in the context of AI service failures, a novel approach in the hospitality and tourism literature. It provides empirical evidence of the efficacy of the strategy, bridging a crucial gap in understanding customer behavior in the face of technological disruptions.

This paper aims to find a suitable solution to degrade the C.I. Reactive Red 24 (RR24) dyeing wastewater by using sodium persulphate to recycle water and inorganic salts.

The effects of temperature, the concentration of inorganic salts and Na₂CO₃ and the initial pH value on the degradation of RR24 were studied. Furthermore, the relationship between free radicals and RR24 degradation effect was investigated. Microscopic routes and mechanisms of dye degradation were further confirmed by testing the degradation karyoplasmic ratio of the product. The feasibility of the one-bath cyclic dyeing in the recycled dyeing wastewater was confirmed through the properties of dye utilization and color parameters.

The appropriate conditions were 0.3 g/L of sodium persulphate and treatment at 95°C for 30 min, which resulted in a decolorization rate of 98.4% for the dyeing wastewater. Acidic conditions are conducive to rapid degradation of dyes, while ·OH or SO₄⁻· have a destructive effect on dyes under alkaline conditions. In the early stage of degradation, ·OH played a major role in the degradation of dyes. For sustainable cyclic dyeing of RR24, inorganic salts were reused in this dyeing process and dye uptake increased with the times of cycles. After the fixation, some Na₂CO₃ may be converted to other salts, thereby increasing the dye uptake in subsequent cyclic staining. However, it has little impact on the dye exhaustion rate and color parameters of dyed fabrics.

The recommended technology not only reduces the quantity of dyeing wastewater but also enables the recycling of inorganic salts and water, which meets the requirements of sustainable development and clean production.

The purpose of this study is to conduct a comprehensive and precise investigation into the influence of office environments on employee performance. Office workers spend a considerable amount of time inside a building, and the office environment in which they work has a profound impact on their overall well-being and directly affects their effectiveness and productivity. Yet, the previous studies opted out the importance of hygiene factors like office environment and there is a need to uncover hidden causes and shed light on office environment areas that can be improved.

This research adopts a descriptive research design using a quantitative research method to study the relationships between office environment facilitations and employee performance. The technique of survey questionnaires was employed, and a total of 829 samples were analyzed. Measurement model, structural model and hypothesis testing using PLS-SEM software version 4.1.0.0 were briefly explained.

The study investigated the direct and indirect effects of the office environment on employee communication, interactions, productivity and performance. The findings revealed significant outcomes, indicating that the office environment does indeed have an impact on these employee-based factors. Both communication and interactions, as well as employee productivity as an indirect effect, were found to significantly mediate the connection between the office environment and employee performance.

Insufficient data and analysis exist regarding the factors influencing the effect of employee performance on business. The constraints of time, cost and scope impede comprehensive surveys and thorough analysis. Regrettably, only four specific aspects of the office environment were examined in relation to employee performance, neglecting other significant factors. By acknowledging the potential problems highlighted in this study concerning different office concepts, organizations can endeavor to establish a more conducive working environment. It is imperative to acknowledge that the absence of a well-structured office environment that meets employees’ expectations may lead to unfavorable consequences.

To the best of the authors knowledge, this is the first study of office environment facilitations related to employee behavioral attitude and employee performance in Yangon, Myanmar and this study will help discover new insights of the importance of employee performance in least developing countries.

The literature on unethical pro-organizational behavior (UPOB) has experienced significant growth in the past decade. However, there is limited research on the effects of organizational, team and malleable individual factors on UPOB. It is also necessary to explore its adverse effects for theoretical advancement and to uncover unexplored opportunities. This study aims to systematically examine the existing body of literature on UPOB, providing thorough theoretical, contextual and methodological insights.

Using the preferred reporting items for systematic reviews and meta-analysis technique, the authors identified 43 articles on UPOB from journals included in the ABDC-2019 list. The authors conducted an analysis of the identified articles and categorized them using a modified version of Paul and Rosado-Serrano’s (2019) TCCM framework.

Existing literature primarily focuses on attitudinal and contextual antecedents of UPOB, neglecting individual differences and their consequences. The review suggests that certain desired employee attitudes may also lead to UPOB. In addition, the study highlights underutilization of established behavioral theories, emphasizing the need for a more inclusive theoretical framework. The exploration identifies research gaps, including in multidisciplinary and transdisciplinary studies, aiming to broaden the research scope in this field.

The study highlights the need for a more comprehensive theoretical framework to understand UPOB.

It cautions organizations fostering positive employee attitudes, such as job satisfaction, workplace spirituality and organizational commitment, as these may inadvertently promote UPOB.

Socially, the paper highlights how engaging in UPOB affects the lives of involved employees.

This paper’s originality arises from its methodical review and categorization of prior research on UPOB using a distinctive, multidisciplinary research framework.