Serial Mechanism Research Articles

Can cuteness soften my anxiety? The impact of conversational styles of service robots on consumer service acceptance

Purpose As artificial intelligence technology empowers service robots, they increasingly communicate with consumers in a human-like manner. This study aims to investigate the effect of service robots’ different conversational styles (competent conversational style vs. cute conversational style) on consumer service acceptance and demonstrate the moderating role of consumers’ technology anxiety. Design/methodology/approach Based on anthropomorphism theory and social presence theory, the authors conducted two scenario-based experiments (restaurant scenario and hotel scenario) to investigate this issue. Findings The results indicate that service robots’ conversational styles impact consumers’ willingness to accept the use of service robots through perceived social presence and positive emotion. Moreover, consumers perceived social presence and positive emotion play a serial mechanism. In addition, the effect of competent conversational style on consumers perceived social presence is less effective than that of cute conversational style. Finally, the authors demonstrate the moderating role of consumer technology anxiety in the relationship between conversational styles and perceived social presence. Practical implications To provide consumers with a positive human–robot interaction experience at the service front line, managers need to make better use of the conversational styles of service robots by comprehensively considering the characteristics of consumer technology anxiety. Originality/value This research extends the literature on service robots by integrating consumer characteristics and robots’ conversational styles. These findings highlight the effectiveness of cute conversational style in alleviating consumer technology anxiety.

Parallel–Serial Robotic Manipulators: A Review of Architectures, Applications, and Methods of Design and Analysis

Parallel–serial (hybrid) manipulators represent robotic systems composed of kinematic chains with parallel and serial structures. These manipulators combine the benefits of both parallel and serial mechanisms, such as increased stiffness, high positioning accuracy, and a large workspace. This study discusses the existing architectures and applications of parallel–serial robots and the methods of their design and analysis. The paper reviews around 500 articles and presents over 150 architectures of manipulators used in machining, medicine, and pick-and-place tasks, humanoids and legged systems, haptic devices, simulators, and other applications, covering both lower mobility and kinematically redundant robots. After that, the paper considers how researchers have developed and analyzed these manipulators. In particular, it examines methods of type synthesis, mobility, kinematic, and dynamic analysis, workspace and singularity determination, performance evaluation, optimal design, control, and calibration. The review concludes with a discussion of current trends in the field of parallel–serial manipulators and potential directions for future studies.

Development of 3-USR Type Spatial 6-DOF Parallel Mechanism with Large Workspace—Proposal of 3-USR Mechanism and Design of Spherical 5-Link Mechanism to Replace Active Universal Pairs (U)—

In this paper, we present a 3-USR-type 6-degree-of-freedom (6-DOF) parallel mechanism characterized by an expansive workspace. This mechanism consists of three coupling chains, each comprising a universal pair (U), a spherical pair (S), and a rotational pair (R), in sequence from the stationary base. To achieve a large workspace, the three stationary universal pairs are designated as active pairs, with their rotational axes intersecting at a single point, thereby creating a hemispherical workspace akin to that of a serial mechanism. To implement the active universal pair within a parallel mechanism, we replaced the spherical 5-link mechanism, which originally featured two stationary active rotational pairs, with stationary active universal pairs, and conducted an inverse kinematics analysis. Subsequently, we assessed the expansive workspace of the spherical 5-link mechanism, a key factor influencing the working area of the 3-USR-type 6-DOF parallel mechanism, by examining its motion transmissibility. Based on this evaluation, we designed two compact mechanisms that provide a large workspace and allow for the configuration of all three rotational axes to intersect at a single point. We experimentally investigated the relationship between motion transmissibility and rigidity for these two types of spherical 5-link mechanisms, demonstrating that motion transmissibility can serve as an indicator of rigidity. Finally, a prototype of the 3-USR mechanism was fabricated.

Can playing video games enhance reading skills through more efficient serial visual search mechanisms? Insights from an eye tracking study

ABSTRACT Reading disorders are associated with atypical top-down visual attention (VA) processes like reduced VA span and slower serial visual search (SVS). In contrast, expert action video game (AVG) players, known for their efficient top-down VA, exhibit improved reading abilities. It is unclear whether these benefits stem solely from AVGs or apply to other gaming experiences. To explore this, AVG players (AVGPs), players of genres excluding AVGs (VGPs), and non-players were evaluated on their VA span, and behavioural and oculomotor performance in SVS. VGPs, but not AVGPs, demonstrated enhanced performance and oculomotor behaviour in SVS compared to non-players, while both player groups showed a trend towards better VA span skills. Notably, reading-related skills were enhanced in the two player groups, but particularly more so in VGPs. These findings support the existence of potential benefits of playing video games different from classical AVGs for the development of top-down VA and reading-related abilities.

Optimizing Over Serial Dictatorships

Motivated by the success of the serial dictatorship mechanism in social choice settings, we explore its usefulness in tackling various combinatorial optimization problems. We do so by considering an abstract model, in which a set of agents are asked to act in a particular ordering, called the action sequence. Each agent acts in a way that gives her the maximum possible value, given the actions of the agents who preceded her in the action sequence. Our goal is to compute action sequences that yield approximately optimal total value to the agents (a.k.a., social welfare). We assume query access to the value vi(S)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$v_i(S)$$\\end{document} that the agent i gets when she acts after the agents in the ordered set S. We establish tight bounds on the social welfare that can be achieved using polynomially many queries. Even though these bounds show a marginally sublinear approximation of optimal social welfare in general, excellent approximations can be obtained when the valuations stem from an underlying combinatorial domain. Indicatively, when the valuations are defined using bipartite matchings, arborescences in directed graphs, and satisfiability of Boolean expressions, simple query-efficient algorithms yield 2-approximations. We discuss issues related to truthfulness and show how some of our algorithms can be implemented truthfully using VCG-like payments. Finally, we introduce and study the price of serial dictatorship, a notion that provides an optimistic measure of the quality of combinatorial optimization solutions generated by action sequences.

Dissociating parallel versus serial mechanisms responsible for the inefficiency of conjunction search - a goliath task!

Dissociating parallel versus serial mechanisms responsible for the inefficiency of conjunction search - a goliath task!

Development of a 6 degrees- of-freedom hybrid interface intended for teleoperated robotic cervical spine surgery

Abstract This paper deals with the development of a 6-degrees-of-freedom (DoF) hybrid interface for a teleoperated robotic platform intended to assist surgeons in cervical spine surgery. The targeted task is the drilling of cervical vertebrae for the attachment of spinal implants. Given the complex anatomy of the cervical region, with the proximity of the spinal cord and vertebral arteries, high accuracy in the drilling procedure is required to avoid complications for the patient. In this context, the proposed hybrid interface has been designed to meet the requirements of the drilling task, in terms of degrees of freedom, workspace and force feedback, which have been identified through a literature review. It consists of an association of two parallel mechanisms and a centrally located serial mechanism. Direct and inverse kinematic modelling of each mechanism as well as the one of the complete interface were carried out. A study of the dexterity distribution of the parallel mechanisms was carried out in order to select the suitable interface working mode that would keep the singularities away from the prescribed workspace. In addition, the force feedback was implemented in static mode, neglecting in a first time the weight of the system. The interface design parameters were then optimized to avoid singularities within the prescribed workspace, to minimize motor torques, and to reduce the size of the interface. These development stages led to the design of a motorized prototype of the hybrid interface.

Few-Shot Steel Defect Detection Based on a Fine-Tuned Network with Serial Multi-Scale Attention

Detecting defects on a steel surface is crucial for the quality enhancement of steel, but its effectiveness is impeded by the limited number of high-quality samples, diverse defect types, and the presence of interference factors such as dirt spots. Therefore, this article proposes a fine-tuned deep learning approach to overcome these obstacles in unstructured few-shot settings. Initially, to address steel surface defect complexities, we integrated a serial multi-scale attention mechanism, concatenating attention and spatial modules, to generate feature maps that contain both channel information and spatial information. Further, a pseudo-label semi-supervised learning algorithm (SSL) based on a variant of the locally linear embedding (LLE) algorithm was proposed, enhancing the generalization capability of the model through information from unlabeled data. Afterwards, the refined model was merged into a fine-tuned few-shot object detection network, which applied extensive base class samples for initial training and sparsed new class samples for fine-tuning. Finally, specialized datasets considering defect diversity and pixel scales were constructed and tested. Compared with conventional methods, our approach improved accuracy by 5.93% in 7-shot detection tasks, markedly reducing manual workload and signifying a leap forward for practical applications in steel defect detection.

Whether ChatGPT adoption inspires higher education students’ digital entrepreneurial intention? An integrated model of the SCCT and the TPB

Purpose This study aims to integrate the Social Cognitive Career Theory with the Theory of Planned Behavior to unravel the intricate dynamics of how engaging with ChatGPT affects individuals’ digital entrepreneurial intention, underlying the serial mediation mechanism of the cognitive and reasoned career process. Design/methodology/approach This research use a cross-sectional design, drawing on a sample of 604 higher education students from six universities in Vietnam. Multiple regression analyses were conducted to test the formulated hypotheses after assessing the reliability and validity of scales through Cronbach’s alpha and confirmatory factor analysis. Findings The results indicate that ChatGPT adoption significantly increases perceived AI competencies, entrepreneurial opportunity recognition and digital entrepreneurial self-efficacy. Digital entrepreneurial self-efficacy was found to have a positive impact on attitudes toward digital entrepreneurship, which, in turn, fosters digital entrepreneurial intention. ChatGPT adoption thus poses serial indirect impacts on digital entrepreneurial intention through the sequential pathways of enhanced digital entrepreneurial self-efficacy and positive attitudes. Practical implications This study’s findings provide valuable recommendations for entrepreneurs, higher education institutions and policymakers. Originality/value This research contributes to the entrepreneurship literature by integrating two prominent theoretical frameworks to elucidate how ChatGPT adoption impacts digital entrepreneurial intentions. The serial mediation model expands that understanding of the complex cognitive and reasoned processes involved, providing a novel perspective on the role of AI in entrepreneurship.

Transfer learning method for specific emitter identification based on pseudo‐labelling and meta‐learning

AbstractSpecific emitter identification (SEI) represents a prominent research direction within the electronic countermeasures domain aimed at discerning carrier identity attributes by analysing subtle radar characteristics. At present, most established SEI techniques assume that both the source and target domain (TD) data adhere to the same distribution. However, this assumption is invalidated by semantic drift which frequently occurs between TD and source domain (SD) samples owing to variations in the collection environment, equipment, and other factors. Considering the aforementioned challenges, this article introduces a transfer learning approach for SEI to leverage pseudo‐label integration within the framework of meta‐learning. This approach employs the bispectral perimeter integral for extracting emitter signal features to construct a feature extractor and basic learner based on CNN13. To label and filter the TD samples, the proposed approach utilises the multiple pseudo‐label serial filtering mechanism, which comprises positive and negative pseudo‐labelling strategies, label uncertainty prediction methods, and hard sample filtering strategies. Ultimately, to address algorithmic real‐time requirements, the labelled TD samples are integrated into the feature extractor and learner of the SD through meta‐learning to facilitate the transfer of TD features to the SD training model. Experimental validation conducted on a real radar dataset demonstrated that the proposed algorithm significantly enhances identification accuracy, exhibiting an improvement from approximately 50% to approximately 90%. Furthermore, the algorithm exhibits a short runtime and robust adaptability, effectively catering to the demands of practical scenarios.

Unveiling the power of word-of-mouth in pre-recruitment employer branding strategy during COVID-19

PurposeThis study, based on signaling theory, examines the pre-recruitment employer branding strategy during the COVID-19 pandemic. It investigates the relationship between spontaneous word-of-mouth (WOM) recommendations for companies and prospective candidates' job application intentions. Specifically, the study explores serial mechanisms mediating the characteristics of company online career pages, including the perceived informativeness of online job advertisements (ads), candidates' preferences for its web approach to them and the company’s reputation.Design/methodology/approachReflecting prospective candidates from students and young alumni of universities, partial least squares structural equation modeling (PLS-SEM) was employed on a sample of 737 individuals representing various fields of study from Greek universities.FindingsThe findings highlight the effectiveness of positive WOM recommendations during the initial stages of recruitment, particularly amidst COVID-19 challenges in the labor market, notably impacting young candidates. The study suggests that spontaneous WOM, originating from trustful sources, motivates job seekers to actively engage with the company’s web career channels, seeking information and favorable indications of the company’s approach toward its candidates. Positive WOM, combined with informative content and a friendly communication style, plays a critical role in shaping the company’s reputation. Consequently, this encouragement motivates individuals to start their job search efforts and consider applying for positions within the specific organization.Practical implicationsThis research provides valuable empirical evidence in the pre-recruitment field, particularly in unforeseen crisis circumstances such as the COVID-19 pandemic. It examines how spontaneous, positive WOM from sources, like peers and alumni, significantly influences young job seekers' perceptions and preferences regarding the company’s career web channels as sources of information and signals about working conditions. The combination of positive WOM with informative content and a friendly communication style in the web approach plays a crucial role in shaping a positive company reputation. Consequently, this encourages candidates to consider applying for positions within the company.Originality/valueThis research contributes to pre-recruitment studies, especially amidst crises like COVID-19. It examines how positive WOM from trusted sources like peers and alma mater alumni influences young job seekers' views on the company’s career web channels. By emphasizing the importance of combining positive WOM with informative web content and a friendly communication style, the study offers insights into effective recruitment strategies. It highlights the significance of positive and spontaneous WOM in attracting young talent and its impact on job seekers' decision-making, even in uncertain conditions. Overall, it advances recruitment practices for attracting candidates.

Impact of Performance Expectancy on Adaptive Performance: through Serial Mediation Mechanism

Performance Expectancy has an effect on the adaptive performance of managers in small and medium-sized businesses in Pakistan. This study looks at how this expectation work together. The research also looks at how mobile usage can act as a mediator, as well as how productivity also mediates in the same way. In this study, the researchers wanted to study that how usage of mobile and productivity helps managers change their performance at work. The people this study is aimed at are managers or owners of small and medium-sized businesses (SMEs) that are listed with the Chambers of Commerce in Pakistan's major cities. As part of the full study, 406 responses were gathered, which is a 75% answer rate. Structure Equation Modeling (SEM) was used to build measurement and structure models that were used to test the theory. The findings showed that there were progressive mediators in the link between Performance expectancy and adaptive performance. There was a strong and good direct effect of performance expectation on adaptive performance. This link was also affected by sequential mediators, such as the usage and productivity. There is a positive and statistically significant link between all the variables. The study's results will help academics, the banking industry, SMEDA, and practitioners understand how important it is to use mobile devices and how performance expectation affect flexible performance. Researchers should focus on doing an empirical study in the future to look into how information quality, system quality of mobile devices, and mobile payments affect the change in the system. Small and medium-sized businesses (SMEs) and big businesses in Pakistan might be compared as part of this study.

A Synthesis Method of Open-Chain Coupled Serial Linkage Mechanism Fusing Trajectory and Posture

In order to meet the motion characteristics requirements of multi-objective fusion of execution components, a synthesis method of open-chain coupled serial linkage mechanism fusing trajectory and posture is proposed. According to periodic change characteristics of the execution component trajectory and posture of the linkage mechanism, the motion characteristics equation including trajectory and posture information is established by using Fourier series. The harmonic parameters of the link trajectory and posture are calculated according to the principle of discrete Fourier transform. The complex vector theory is applied to determine the functional relationship between the harmonic parameters of the trajectory and posture and the independent variable of the linkage mechanism, and furthermore the motion synthesis equation of the open-chain linkage mechanism fusing trajectory and posture information is established. The linkage mechanism parameters are calculated using Mathcad Prime software. The single-degree-of-freedom open-chain coupled serial linkage mechanism fusing trajectory and posture information is obtained by using a noncircular gear planetary gear train to couple the connection points of the linkage mechanism. The correctness of the method is verified through an example.

Contextual and Individual Determinants of Sustainable Careers: A Serial Indirect Effect Model through Career Crafting and Person-Career Fit

The evolving nature of contemporary careers has sparked an interest in the sustainability of individual careers, which encompasses the pursuit of careers in a manner that promotes health, productivity, and overall happiness. Although previous studies have provided valuable perspectives on sustainable careers, there remains a notable lack of evidence regarding the interplay between individual and contextual determinants in crafting sustainable careers. Therefore, integrating the framework of sustainable careers with the Conservation of Resources (COR) theory, this study proposes a serial indirect effect mechanism that examines the relationship between contextual determinants (i.e., work/family demands and resources) and career sustainability indicators (i.e., work-family balance, employability, work engagement, and work strain) sequentially through career crafting and person-career fit. A two-wave time-lagged survey was conducted with 412 employees from Turkey. Hierarchical regression analyses were performed to test the proposed model, while Process Macro analyses were conducted to examine the serial indirect effects. Results showed that contextual demands and resources were positively associated with career crafting and such career initiatives were related to optimized person-career fit and career sustainability indicators. Notably, contextual determinants were indirectly related to employability and work engagement serially via career crafting and person-career fit. Highlighting the importance of a whole-life perspective in career development, which involves work and family contexts, this study reveals the integral role of career proactivity and its interplay with contextual determinants in building sustainable careers.

Revisiting the impact of public spaces on the mental health of rural migrants in Wuhan: an integrated multi-source data analysis

Current research on public spaces and mental health often focuses on the independent relationship of one or more social mediators, neglecting the nuanced implications and serial mechanisms inherent in the progressive social process. Using Wuhan city, China, as a study case with multi-source data, this research applies Multilevel Generalized Structural Equation Modeling and deep learning techniques to explore the differential effects of public spaces with varying degrees of publicness (i.e., typical, semi-, and privately owned) on rural migrants’ mental health. Crucially, this study scrutinizes both explicit (social interaction) and implicit (perceived integration) social mechanisms to revisit the relationships. The findings reveal that not all public spaces equally influence mental health, with typical and privately owned public spaces conferring profound benefits. Notably, public spaces impact mental health chiefly through perceived integration instead of through direct social interaction. Social interaction improves mental health primarily by enhancing perceived integration, suggesting that meaningful connections beyond superficial encounters are critical. In particular, we observed significant social effects in typical and privately owned public spaces but limited social functionality in semi-public spaces. This evidence contributes to the knowledge required to create supportive social environments within public spaces, integral to nurturing inclusive urban development.

Puzzle Pictures: A Study on Reversible Figures in Advertising

Reversible figures have fascinated researchers in the psychological sciences since the 1800s, and these investigators have generated a massive amount of information on the psychological underpinnings and manifestations of this intriguing visual phenomenon. However, although these puzzle pictures have consistently appeared in marketing communications, advertising research has been negligent in acknowledging reversible figures as a distinctive form of advertising. This paper aims to fill this research gap by systematically investigating reversible figure ads and studying their effects on variables pertinent to marketing and advertising, thereby contributing to theory and practice. The results obtained from four studies reveal that reversible figure ads boost mainstream indicators of ad effectiveness such as brand attitude, perceived brand innovativeness, and perceived ad creativity. Further, informed by MacInnis and Jaworski’s (1989) information processing framework, this paper supports a novel ad processing model in which reversible figure ads enhance perceptions of ad creativity, increasing perceived brand innovativeness and thereby strengthening brand attitude. Last, the results indicate conditional indirect effects, revealing that this serial mechanism materializes in individuals with higher (vs. lower) levels of artistic interest.

Automatic Design of Serial Linkage Using Virtual Screw Joint

Here, an automatic design method for a serial link mechanism is proposed. This method outputs all kinematic parameters of joints, position, orientation, number, and type of joint (revolute or prismatic). Several studies have been conducted on optimizing only the positions and directions of joints for a desired path. However, automatically determining the numbers and types of joints requires an excessive calculation time owing to the complicity of kinematics. To handle heavy computation, a virtual screw joint (VSJ) is introduced based on a screw axis and the product of exponentials formula. Screw joints have the advantage of including both rotation and translation. First, an additional joint is optimized as a VSJ. Then, adopting its position and orientation and selecting a revolute or prismatic joint facilitate an efficient design process. To demonstrate the effectiveness of this study, two task motions addressed in a related work are adopted as target paths. Consequently, the proposed method automatically generates serial linkages that contain both revolute and prismatic joints and can follow along desired paths.

Optimal Design of Lower Limb Rehabilitation System Based on Parallel and Serial Mechanisms

This paper presents the structure and model of a hybrid modular structure of a robotic system for lower limb rehabilitation. It is made of two modules identical in structure, including an active 3-PRRR manipulator for moving the patient’s foot and a passive orthosis based on the RRR mechanism for supporting the lower limb. A mathematical model has been developed to describe the positions for the links of the active and passive mechanisms of two modules, as a function of the angles in the joints of the passive orthosis, considering constraints for attaching the active manipulators to the moving platform and their configurations. A method has been formulated for a parametric synthesis of the hybrid robotic system proposed with modular structure, taking into account the generated levels of parametric constraints depending on the ergonomic and manufacturability features. The proposed design is based on a criterion in the form of a convolution, including two components, one of which is based on minimizing unattainable points of the trajectory, considering the characteristics of anthropometric data, and the other is based on the compactness of the design. The results of the mathematical modeling are discussed as well as the analysis results towards a prototype validation.

Exploring the complementary effects of business analytics capabilities and π-shaped skills on innovation outcomes

ABSTRACT While it is clear that business analytics (BA), on average, adds value to firms, it is less clear why some firms perform better than others in leveraging their data assets. To a large degree, prior research has attributed such differences to the human factor. Nevertheless, there is still limited knowledge concerning what impact competencies of key personnel have on generating value from BA initiatives, and to what extent such outcomes complement a firm’s investment in BA. To examine these questions, this study explores the complementary relationship between BA capabilities and π-shaped skills. It posits that the concurrent presence of both indirectly influences innovation outcomes by fostering a data-driven culture. We build on a sample of 185 individuals with supervisory positions in Turkey to unpack this process. The findings revealed that BA capabilities and π-shaped skills influence a firm’s data-driven culture, which in turn impacts the firms’ marketing innovation, and subsequently its innovative performance. That is, data-driven culture and firms’ marketing innovation are relevant underlying serial mechanisms by which BA capabilities and π-shaped skills influence innovative performance.

Active Compliance Smart Control Strategy of Hybrid Mechanism for Bonnet Polishing.

Compliance control strategies have been utilised for the ultraprecision polishing process for many years. Most researchers execute active compliance control strategies by employing impedance control law on a robot development platform. However, these methods are limited by the load capacity, positioning accuracy, and repeatability of polishing mechanisms. Moreover, a sophisticated actuator mounted at the end of the end-effector of robots is difficult to maintain in the polishing scenario. In contrast, a hybrid mechanism for polishing that possesses the advantages of serial and parallel mechanisms can mitigate the above problems, especially when an active compliance control strategy is employed. In this research, a high-frequency-impedance robust force control strategy is proposed. It outputs a position adjustment value directly according to a contact pressure adjustment value. An open architecture control system with customised software is developed to respond to external interrupts during the polishing procedure, implementing the active compliance control strategy on a hybrid mechanism. Through this method, the hybrid mechanism can adapt to the external environment with a given contact pressure automatically instead of relying on estimating the environment stiffness. Experimental results show that the proposed strategy adapts the unknown freeform surface without overshooting and improves the surface quality. The average surface roughness value decreases from 0.057 um to 0.027 um.