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Biometric scans using fingerprints are widely used for security purposes. Eventually, for authentication purposes, fingerprint scans are not very reliable because they can be faked by obtaining a sample of the fingerprint of the person. There are a few spoof detection techniques available to reduce the incidence of spoofing of the biometric system. Among them, the most commonly used is the binary classification technique that detects real or fake fingerprints based on the fingerprint samples provided during training. However, this technique fails when it is provided with samples formed using other spoofing techniques that are different from the spoofing techniques covered in the training samples. This paper aims to improve the liveness detection accuracy by fusing electrocardiogram (ECG) and fingerprint.

In this paper, to avoid this limitation, an efficient liveness detection algorithm is developed using the fusion of ECG signals captured from the fingertips and fingerprint data in Internet of Things (IoT) environment. The ECG signal will ensure the detection of real fingerprint samples from fake ones.

Single model fingerprint methods have some disadvantages, such as noisy data and position of the fingerprint. To overcome this, fusion of both ECG and fingerprint is done so that the combined data improves the detection accuracy.

System security is improved in this approach, and the fingerprint recognition rate is also improved. IoT-based approach is used in this work to reduce the computation burden of data processing systems.

Corporate social responsibility (CSR) is gaining recognition and value among researchers, academicians and business professionals. Drawing on theories of social identity and person–organisation fit, the present research propounds a model that investigates the role of CSR branding in influencing employee retention.

The paper is based on primary survey data from 348 employees working in organisations in the Indian industrial hubs. The study uses the regression and PROCESS macro model to analyse relationship among study variables.

The study indicated how CSR initiatives could help organisations handle the threat of high turnover storm all over the world, thereby retaining the employees with a high set of skills. Moreover, the paper connotes that employee retention is influenced directly by CSR branding as well as indirectly under the presence of organisational identification and person–organisation fit (mediators).

Results suggest the role of a positive identity and a mutual fit as significant predictors of employee retention. The implications for future research on CSR, employees' stay intentions, employees' identification and value congruence are further discussed in light of the findings.

The novelty of this research insists on shedding light on the indirect mechanisms linking CSR to employee retention that has been overlooked so far, particularly in the Indian setting; studies on an integrated model of organisational identification and person–organisation fit are limited.

This paper aims to examine the evolution of organizational identification (OI) research over the past five decades and its journey through various lenses, such as the collaborative network of authors, organizations and countries. The conceptual and intellectual structure of the construct is analysed via keywords and co-citation pattern mapping.

OI research is rising in popularity, with 118 papers published in 2019, 168 papers in 2020 and 15 publications till February 2021 in the Scopus database. The Scopus database is used to retrieve 55 years of OI studies published between 1965 and 2021. The free bibliometric tools Biblioshiny and VOSviewer are used to analyse 1,034 journal papers.

The result showed that R. Van Dick is the most influential author and the USA is the most involved country in OI research. As per the findings, the Journal of Organizational Behaviour published most of OI research and “corporate social responsibility” and “organizational commitment” seem to be the most used keywords alongside OI.

This study will be highly beneficial to OI researchers making their understanding about the construct better. It will also encourage social psychologists to understand the construct utility in workplace social welfare programmes. The research could also help governments and funding bodies to evaluate grant requests. Furthermore, researchers from countries with the lowest proportion of OI studies would be encouraged to spend more time and effort in this area. It will offer insight into international marketing and how individuals and stakeholders perceive and connect with an organization globally.

To the best of the authors’ knowledge, this study is one of the important research studies carried out in the domain of OI in the international context. This is also one of the few studies which is spread out across different disciplinary areas including international marketing and management. The success of this paper can open avenues and influence future researchers to study in the OI and related cross-disciplinary areas of international management.

Single-shot multi-category clothing recognition and retrieval play a crucial role in online searching and offline settlement scenarios. Existing clothing recognition methods based on RGBD clothing images often suffer from high-dimensional feature representations, leading to compromised performance and efficiency.

To address this issue, this paper proposes a novel method called Manifold Embedded Discriminative Feature Selection (MEDFS) to select global and local features, thereby reducing the dimensionality of the feature representation and improving performance. Specifically, by combining three global features and three local features, a low-dimensional embedding is constructed to capture the correlations between features and categories. The MEDFS method designs an optimization framework utilizing manifold mapping and sparse regularization to achieve feature selection. The optimization objective is solved using an alternating iterative strategy, ensuring convergence.

Empirical studies conducted on a publicly available RGBD clothing image dataset demonstrate that the proposed MEDFS method achieves highly competitive clothing classification performance while maintaining efficiency in clothing recognition and retrieval.

This paper introduces a novel approach for multi-category clothing recognition and retrieval, incorporating the selection of global and local features. The proposed method holds potential for practical applications in real-world clothing scenarios.

The purpose of this paper is to discuss how agency conflicts between people and main government organs affect the combatting ability of white-collar money laundering in an emerging economy.

This paper uses a qualitative design under the philosophy of interpretivism. The case study research strategy is used inductively to investigate how structural limitations affect white-collar money laundering.

This study reveals that serious agency conflicts exist between public and main government organs which are detrimental to the rights of people to enjoy a crime-free society. First agency conflict of people and legislature intensifies as a result of limited understanding of the legislature and failure to take precautionary actions to develop an anti-money laundering and countering the financing of terrorism (AML/CFT) regime with evolving global standards. This delay has resulted in identifying Sri Lanka as a deficient AML/CFT regime twice. The second conflicts arise between people and the executive which is a serious conflict due to misuse of statutory power and failure to perform duties. The independence and integrity of administrative authorities who perform executive functions were inherent problems of implementing a sound AML/CFT regime. Lack of monitoring, nonavailability of an independent audit and inappropriate reporting channels were other encouraging factors of administrative organs to misuse statutory power. The third conflict between people and the judiciary was not intensified because the function was not so exposed to create agency conflicts. After all, an adequate number of cases had not proceeded to the judiciary due to inherent limitations as a result of intensified first two agency conflicts. The agency conflicts have intensified over the years and AML/CFT regime has been ineffective as a result of limited influence and understanding of the principal, people. Therefore, the principal has to influence the agents to make reforms in the AML/CFT regime to make the country a white-collar crime-free country.

This study uses a case study strategy to assess the context of Sri Lanka as an emerging economy. It is recommended to take into consideration the contextual facts when the findings are applied to other jurisdictions.

This paper is an original work of the authors which discusses how agency conflicts arise between people and three main government organs in implementing a sound AML/CFT regime in Sri Lanka as an emerging economy.

Empowering leadership has a wide range of positive individual employee-related outcomes. However, a limited number of research studies are available emphasizing the overall organization-related outcomes. The major aim of this study is to delve into the function of organizational identification and intellectual capital (structural, relational and human) in mediating the relationship between empowering leadership and organizational innovativeness. Depending upon the resource-based view theory, this study comprehensively investigates the sequential effects of empowered leadership on the mediating roles of organizational identification and intellectual capital in organizational innovativeness.

Data were gathered through a self-administered questionnaire, which got 337 responses from telecom employees. To evaluate the hypotheses, the data were analyzed in SEM-M-Plus using exploratory and confirmatory factor analyses.

The findings demonstrate that empowering leadership impacts organizational innovativeness with the sequential mediation of organizational identification and intellectual capital (structural, human and social).

Organizations can identify and encourage leaders who exhibit empowering behaviors such as delegating responsibilities, providing autonomy and fostering a sense of ownership among employees. Also, organizations can foster intellectual capital by providing opportunities for learning, training and development. Additionally, knowledge sharing and collaboration can help to enhance the intellectual capital of employees.

While much research has been conducted on empowering leadership, the continued development of knowledge and the emergence of new perspectives related to identification and intellectual capital highlights the importance of exploring alternative paths that have been overlooked. Therefore, there is a pressing need to conduct research that takes into account these additional factors.

The aim of this study was to conduct a systematic literature review (SLR) on vlog marketing. The focus was to analyse the major themes in this field and provide insights for future research directions.

The authors reviewed a total of 49 peer-reviewed publications that include the search terms “vlog” or “video blog” in their titles, keywords and abstracts, retrieved from digital databases Scopus and Web of Science, up to the end of July 2023. Thematic analysis was used to examine and synthesise the articles.

The authors found 19 sub-themes and identified four major themes that emerged from the literature: (1) endorsement outcomes, (2) vlogger characteristics, (3) consumer credibility and (4) vlog content crafting.

There are many unanswered questions in the literature, suggesting that vlog marketing research is still in its infancy, and that in-depth further studies are required for a more comprehensive understanding of the field. This study has identified potential avenues for future research that may contribute to the existing body of knowledge and valuable insights on vlog marketing.

The purpose of this paper is to highlight the key technical challenges that derive from the recently proposed European Artificial Intelligence Act and specifically, to investigate the applicability of the requirements that the AI Act mandates to high-risk AI systems from the perspective of AI security.

This paper presents the main points of the proposed AI Act, with emphasis on the compliance requirements of high-risk systems. It matches known AI security threats with the relevant technical requirements, it demonstrates the impact that these security threats can have to the AI Act technical requirements and evaluates the applicability of these requirements based on the effectiveness of the existing security protection measures. Finally, the paper highlights the necessity for an integrated framework for AI system evaluation.

The findings of the EU AI Act technical assessment highlight the gap between the proposed requirements and the available AI security countermeasures as well as the necessity for an AI security evaluation framework.

AI Act, high-risk AI systems, security threats, security countermeasures.

This study proposes a collaborative federated learning (CFL) framework to address personal data transmission and retention issues for artificial intelligence (AI)-enabled video surveillance in public spaces.

This study examines specific challenges for long-term people monitoring in public spaces and defines AI-enabled video surveillance requirements. Based on the requirements, this study proposes a CFL framework to gradually adapt AI models’ knowledge while reducing personal data transmission and retention. The framework uses three different federated learning strategies to rapidly learn from different new data sources while minimizing personal data transmission and retention to a central machine.

The findings confirm that the proposed CFL framework can help minimize the use of personal data without compromising the AI model's performance. The gradual learning strategies help develop AI-enabled video surveillance that continuously adapts for long-term deployment in public spaces.

This study makes two specific contributions to advance the development of AI-enabled video surveillance in public spaces. First, it examines specific challenges for long-term people monitoring in public spaces and defines AI-enabled video surveillance requirements. Second, it proposes a CFL framework to minimize data transmission and retention for AI-enabled video surveillance. The study provides comprehensive experimental results to evaluate the effectiveness of the proposed framework in the context of facial expression recognition (FER) which involves large-scale datasets.

Recently, both researchers and practitioners have been very interested in the impact of leadership on employee engagement. Thus, I aimed to examine the relationship between spiritual leadership and work engagement through the mediating role of spiritual well-being at work.

I assessed spiritual leadership, engagement, and well-being in an empirical study based on a sample of 223 employees. I collected data through a survey-based method and analyzed them using structural equation modeling (SEM).

The present study contributes to the existing knowledge in the leadership field, especially spiritual leadership. The results revealed that spiritual leadership impacts employees’ work engagement by indirectly influencing employees’ spiritual well-being.

Theoretically, the findings imply that spiritual well-being can be one of the factors considered in enhancing work engagement through spiritual leadership.

Finding evidence that spiritual leadership, like other leadership styles, can foster employee engagement. Therefore, leaders should take care of employees’ spiritual needs.

Many researchers have indicated that well-being is associated with employee engagement. However, they overlooked employees’ spiritual well-being in the research. The study confirmed the unexplored mediating role of spiritual well-being between spiritual leadership and employee engagement.