Search results

Gesture recognition plays an important role in many fields such as human–computer interaction, medical rehabilitation, virtual and augmented reality. Gesture recognition using wearable devices is a common and effective recognition method. This study aims to combine the inverse magnetostrictive effect and tunneling magnetoresistance effect and proposes a novel wearable sensing glove applied in the field of gesture recognition.

A magnetostrictive sensing glove with function of gesture recognition is proposed based on Fe-Ni alloy, tunneling magnetoresistive elements, Agilus30 base and square permanent magnets. The sensing glove consists of five sensing units to measure the bending angle of each finger joint. The optimal structure of the sensing units is determined through experimentation and simulation. The output voltage model of the sensing units is established, and the output characteristics of the sensing units are tested by the experimental platform. Fifteen gestures are selected for recognition, and the corresponding output voltages are collected to construct the data set and the data is processed using Back Propagation Neural Network.

The sensing units can detect the change in the bending angle of finger joints from 0 to 105 degrees and a maximum error of 4.69% between the experimental and theoretical values. The average recognition accuracy of Back Propagation Neural Network is 97.53% for 15 gestures.

The sensing glove can only recognize static gestures at present, and further research is still needed to recognize dynamic gestures.

A new approach to gesture recognition using wearable devices.

This study has a broad application prospect in the field of human–computer interaction.

The sensing glove can collect voltage signals under different gestures to realize the recognition of different gestures with good repeatability, which has a broad application prospect in the field of human–computer interaction.

This study aims to develop and validate a multidimensional scale to measure the motivating factors that lead to opportunity recognition in social entrepreneurship among higher education institute (HEI) students.

The scale was developed through two phases; in phase 1, semi-structured interviews with social entrepreneurs and aspiring students were conducted to explore themes for item generation. Phase 2 included developing and validating the scale using exploratory (EFA) and confirmatory factor analysis (CFA). The sample included HEI students (n = 300 for EFA, n = 300 for CFA) with either academic background or volunteering experiences in social entrepreneurship.

A 24-item scale is developed in the study, with six factors measuring the motivating factors influencing opportunity recognition in social entrepreneurship: life experiences, social awareness, social inclination, community development, institutional voids and natural option for a meaningful career.

The scale facilitates the development of theories and models in social entrepreneurship. The scale also enables policymakers and social entrepreneurship educators to understand the motivating factors that lead to opportunity recognition among students. It would help them to provide target-specific support to students.

To the best of the authors’ knowledge, this study is the first attempt to develop a scale that measures opportunity recognition in social entrepreneurship based on specific motivating factors. The study used the model by Yitshaki and Kropp (2016) as the conceptual framework. This study is the first attempt to triangulate the model’s findings using a quantitative methodology and through the development of a measurement scale. Besides, the scale adds value to social entrepreneurship research, which lacks empirical research on HEI students.

The purpose of this paper is to present a system for recognition of location names in ancient books written in languages, such as Chinese, in which proper names are not signaled by an initial capital letter.

Rule-based and statistical methods were combined to develop a set of rules for identification of product-related location names in the local chronicles of Guangdong. A name recognition system, with functions of document management, information extraction and storage, rule management, location name recognition, and inquiry and statistics, was developed using Microsoft's .NET framework, SQL Server 2005, ADO.NET and XML. The system was evaluated with precision ratio, recall ratio and the comprehensive index, F.

The system was quite successful at recognizing product-related location names (F was 71.8 percent), demonstrating the potential for application of automatic named entity recognition techniques in digital collation of ancient books such as local chronicles.

Results suffered from limitations in initial digitization of the text. Statistical methods, such as the hidden Markov model, should be combined with an extended set of recognition rules to improve recognition scores and system efficiency.

Electronic access to local chronicles by location name saves time for chorographers and provides researchers with new opportunities.

Named entity recognition brings previously isolated ancient documents together in a knowledge base of scholarly and cultural value.

Automatic name recognition can be implemented in information extraction from ancient books in languages other than English. The system described here can also be adapted to modern texts and other named entities.

Although numerous signal modalities are available for emotion recognition, audio and visual modalities are the most common and predominant forms for human beings to express their emotional states in daily communication. Therefore, how to achieve automatic and accurate audiovisual emotion recognition is significantly important for developing engaging and empathetic human–computer interaction environment. However, two major challenges exist in the field of audiovisual emotion recognition: (1) how to effectively capture representations of each single modality and eliminate redundant features and (2) how to efficiently integrate information from these two modalities to generate discriminative representations.

A novel key-frame extraction-based attention fusion network (KE-AFN) is proposed for audiovisual emotion recognition. KE-AFN attempts to integrate key-frame extraction with multimodal interaction and fusion to enhance audiovisual representations and reduce redundant computation, filling the research gaps of existing approaches. Specifically, the local maximum–based content analysis is designed to extract key-frames from videos for the purpose of eliminating data redundancy. Two modules, including “Multi-head Attention-based Intra-modality Interaction Module” and “Multi-head Attention-based Cross-modality Interaction Module”, are proposed to mine and capture intra- and cross-modality interactions for further reducing data redundancy and producing more powerful multimodal representations.

Extensive experiments on two benchmark datasets (i.e. RAVDESS and CMU-MOSEI) demonstrate the effectiveness and rationality of KE-AFN. Specifically, (1) KE-AFN is superior to state-of-the-art baselines for audiovisual emotion recognition. (2) Exploring the supplementary and complementary information of different modalities can provide more emotional clues for better emotion recognition. (3) The proposed key-frame extraction strategy can enhance the performance by more than 2.79 per cent on accuracy. (4) Both exploring intra- and cross-modality interactions and employing attention-based audiovisual fusion can lead to better prediction performance.

The proposed KE-AFN can support the development of engaging and empathetic human–computer interaction environment.

This study aims to propose a model of publics' ethical activism, testing the role of emotional outrage in an extended framework of the previously established STOPS model. Thus, this study aims to investigate (1) how ethical perception of a social issue affects situational motivation that leads to participation in public activism, and (2) how emotional outrage plays a role in mediating between situational motivation and activism behaviors.

The study aims at investigating the mediating role of emotional outrage between situational motivation and activism behaviors, which have not been investigated thoroughly in public relations research. By conducting a national survey with 386 people (N = 386) living in Australia, the study's suggestive model was tested in the context of two ethical issues (e.g. climate change and anti-racism). This study found that people who perceive an ethical issue are likely to be motivated to participate in activism behaviors. Specifically, three situational perceptions (i.e. problem recognition, constraint recognition and involvement recognition) were found to be significant factors affecting situational motivation (SM) in problem solving. A high level of emotional outrage was found to play a mediating role between SM and consequential ethical activism behaviors. The more people feel outraged about an ethical issue, the more likely they will engage in punitive behavior. This study contributes to the theoretical development of public relations by illuminating how situational perceptions lead to emotional outrage that promotes behavioral intentions in an ethical context. This study also suggests that a practitioner should be sought to manage the levels of perceptual factors when setting up a communication plan in response to an ethical public crisis.

This study found that people who perceive an ethical issue are likely to be motivated to participate in activism behaviors. Specifically, three situational perceptions (i.e. problem recognition, constraint recognition and involvement recognition) were found to be significant factors affecting situational motivation (SM) in problem solving. A high level of emotional outrage was found to play a mediating role between SM and consequential ethical activism behaviors. The more people feel outraged about an ethical issue, the more likely they will engage in punitive behavior.

This study substantiates how three perceptual antecedents may conjointly affect situational motivation. Also, the findings in this study also contribute to theoretical development in predicting ethical activism intentions. Another contribution of this study is to demonstrate the mediating role of emotional outrage between situational motivation and ethical activism. The authors strived to explore individuals' perceptions and its impact on intention to boycott against ethical problematic social issues. It should be considered that this study used a hypothetical and manipulated situation where respondents are exposed to the visual stimuli that focus on the moral problems that those specific issues have raised.

First, as problem recognition plays a prime mover role in the overall problem-solving process in an ethical context, organizations should reduce individual's ethical problem recognition. When setting up a communication plan, an organization should showcase their positive role in addressing the ethical problems (e.g. to show Adani's commitment to indigenous people and efforts to protect the environment). The response strategy should be effective enough to create an “ethical dilemma,” which refers to a situation in which one has a difficult choice to make between two ethical options.

This study contributes to theoretical development of public relations by illuminating how situational perceptions lead to emotional outrage that promotes behavioral intentions in an ethical context. This study also suggests that a practitioner should be sought to manage the levels of perceptual factors when setting up a communication plan in response to an ethical public crisis.

The article investigates the patterns of asset impairment recognition in search of signs of “big bath” earnings management practices across an internationally diversified sample of public companies. It also elucidates the incentives that may underlie such practices and explores possible safeguards embedded in the existing corporate governance mechanisms.

The article applied static panel and binary logit models to an international firm-level panel dataset of 1045 public companies observed between 2003 and 2018.

Our empirical results suggest that recognition of asset impairment has no determinate impact on earnings volatility. Investigating the possibility of “big bath” earnings management practices, the authors found no impact of asset impairment recognition on total senior executive compensation in firms, which pay performance-based remuneration. The quality of corporate governance has appeared to impact the firms’ intertemporal proclivity to recognize asset impairment with those having the more entrenched and management-controlled boards being more likely to time impairment recognition by delaying it during exceptionally good and exceptionally bad years. While generally unlikely, recognition of asset impairment in a period with a recorded negative operating performance is found to be closely associated with key executive departures.

The article corroborates the salient role of corporate governance mechanisms in shaping the intertemporal patterns of asset impairment recognition. The possible remedies to the phenomenon should be derived therefrom.

Knowledge management in any organization is important in enhancing the organization’s performance. This study aims to explore the influence of knowledge management capability on organizational performance with the mediation role of opportunity recognition and the moderation effect of environmental dynamism.

This study used an effective and well-developed survey to collect data from 387 managers working in different service organizations in the Kingdom of Saudi Arabia. Further, SmartPLS software was used for data analysis.

The outcomes confirm that knowledge management capability is directly and indirectly (via opportunity recognition) related to organizational performance. Environmental dynamism moderates the linkage between knowledge management capability and opportunity recognition, as well as between opportunity recognition and organizational performance.

This study provides a valuable and novel managerial and theoretical approach for management to improve firm performance with the help of knowledge management capabilities, opportunity recognition, and environmental dynamism. The findings of this paper can be implemented not only in the service sector but also in the production sector. Future studies can use this conceptual framework in different countries with the current data. Moreover, other analytical approaches can be used to check the variability of these findings.

This study contributes to connecting research gaps in the literature and advancing insights into how knowledge management capabilities affect organizational performance. The study explores the mediating role of opportunity recognition and environmental dynamics as moderators between knowledge management capability and opportunity recognition and between opportunity recognition and organizational performance.

This study aims to investigate the impact of accounting regulation (AR) on good news (GNs) recognition and conditional conservatism (CC), using the Chinese experiment in the 2006 AR.

The current study applies the Basu (1997) model to a sample of 26,755 firm-year observations from 1997 to 2017.

The study finds that GNs recognition is significantly reduced and becomes significantly less than bad news recognition under China’s 2006 AR, suggesting that CC is enhanced under China’s 2006 AR.

This paper excludes the financial sector from the sample. Thus, generalizing results on the financial sector is not appropriate. In addition, the available literature on this topic is limited as it deals with convergence with IFRS, not the full adoption of IFRS.

The study findings are expected to benefit policymakers and accounting standard setters in controlling GNs recognition and CC as well.

Whereas prior studies on this topic report their results on CC only, without considering the role of AR on GNs recognition, this paper highlights the role of AR on both GNs recognition and CC as well.

Data-driven marketing is replacing conventional marketing strategies. The modern marketing strategy is based on insights derived from customer behavior information gathered from their facial expressions and neuro-signals. This study explores the potential for face recognition and neuro-marketing in modern-day marketing.

The study conducts an in-depth examination of the extant literature on neuro-marketing and facial recognition marketing. The articles for review are downloaded from the Scopus database, and PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) is then used to screen and choose the relevant papers. The systematic literature review method is applied to conduct the study.

An extensive review of the literature reveals that the domains of neuro-marketing and face recognition marketing remain understudied. The authors’ review of selected papers delivers five neuro-marketing and facial recognition marketing themes that are essential to modern marketing concepts.

Neuro-marketing and facial recognition marketing are artificial intelligence (AI)-enabled marketing techniques that assist in gaining cognitive insights into human behavior. The findings would be of use to managers in designing marketing strategies to enhance their marketing approach and boost conversion rates.

The uniqueness of this study lies in that it provides an updated review on neuro-marketing and face recognition marketing.

The present research aims to investigate the influence of organizational positioning by drawing upon moral foundations theory in relation to driving charitable giving, and the moderating role of recognition in this regard.

Two experimental studies were conducted to examine the interactive effect of organizational positioning emphasizing a binding (vs an individualizing) moral foundation and donation recognition on charitable giving. Study 1 was conducted in Indonesia, while Study 2 was conducted in the US.

This research demonstrates that individuals will give higher donations to an organization with a binding (vs an individualizing) moral foundation that provides donation recognition. Further, this effect is mediated by social identity signaling.

The findings of this research provide a novel perspective on how organizational positioning can influence whether donation recognition increases charitable giving. Moreover, the findings offer managerial implications to non-profit organizations developing effective charitable campaigns in terms of combining appropriate organizational positioning and donation recognition strategies.