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Banditry and terrorism constitute serious security risks in Nigeria. This follows the fact that Nigeria is rated as one of the leading states in the world that is plagued by terrorism. Terrorists and bandits usually embark on predicate crimes such as kidnapping, smuggling, narcotics trade, and similar trades to finance their terrorist enterprises in Nigeria. The funds realized by criminals from nefarious sources such as sales of narcotics and ransom from kidnapping are usually laundered to make their criminal enterprises self-sustaining. Thus, all “dirty” money is laundered so as not to attract the attention of law enforcement agents. The funds realized through receipt of ransom from kidnapping, smuggling or funds from sponsors are laundered through channels such as bureau de change, which are difficult to monitor by the Nigerian authorities due, in part, to flaws and loopholes in the current anti-money laundering and anti-terrorist laws. This paper aims to adopt a doctrinal and qualitative desktop research methodology. In this regard, the current anti-money laundering and anti-terrorist laws are discussed to explore possible measures that could be adopted to remedy the flaws and loopholes in such laws and combat money laundering and financing of terrorism in Nigeria.

The article analyses the regulation and combating of money laundering and terrorist financing activities in Nigeria. In this regard, a doctrinal and qualitative research method is used to explore the flaws in the Nigerian anti-money laundering laws so as to recommend possible remedies in respect thereof.

It is hoped that policymakers and other relevant persons will use the recommendations provided in this article to enhance the curbing of money laundering and terrorist financing activities in Nigeria.

The article is not based on empirical research.

This study is important and vital to all policymakers, lawyers, law students and regulatory bodies in Nigeria and other countries globally.

The study seeks to curb money laundering and terrorist financing activities in Nigeria.

The study is based on original research which is focused on the regulation and combating of money laundering and terrorist financing activities in Nigeria.

Learning styles based education is becoming influential at higher education institutions around the world. Learning styles are characteristics of how students prefer to learn; they draw their origin from both biological and experiential conditions that make each student unique in the way he/she learns. An important first step in improving learning is to identify or assess students’ learning styles, and there are several instruments that can be used for this purpose. This is necessary for teachers and students who wish to improve learning and study strategies. Students who perform poorly in a conventional educational setting may suffer from a mismatch of learning and teaching styles; for example kinesthetic learners may not adapt to learning by listening or by reading. When we teach tactual and/or kinesthetic students by talking, they focus for only a brief amount of time and then wander off into their own thoughts and quickly forget (Burke & Dunn, 2002). We can improve students’ academic performance by providing them with alternative strategies and activities that respond to their learning style needs (Dunn & Dunn, 1993). In spring 2008, the learning styles of over 700 Zayed University students were assessed using the BE (Building Excellence) survey developed by Rundle & Dunn. The data collected is being analyzed with a view to making recommendations for teachers, students and parents to improve students’ learning. This paper represents the first in a series of publications on this subject; it reviews the survey process, and focuses on the nature and learning preferences of ZU students in perceptual elements (e.g. visual, auditory) and cognitive elements (e.g. Analytic-sequential (left-brain) vs. Global-simultaneous (right-brain) preferences).

This study aims to analyze the precursors of high and low intrapreneurial intentions among fitness center employees, considering various variables (gender, age, organization size and job satisfaction).

The study involved 166 fitness center employees of the Portuguese fitness center. The study used a two-part questionnaire to gather sociodemographic data and assess variables related to intrapreneurial intentions and job satisfaction among fitness employees. The first part collected basic demographic information, while the second used validated scales to measure intrapreneurial intentions (innovation and risk-taking) and job satisfaction (intrinsic and extrinsic).

This study underscores intrapreneurship as key for the evolving global fitness sector, highlighting job satisfaction as critical for fostering intrapreneurial intentions. Age, organizational size and gender diversity are also significant, suggesting that fostering a diverse and satisfied workforce under transformational leadership can enhance fitness organizations’ adaptability and growth.

This research supports the growth of the fitness sector by demonstrating how intrapreneurship, propelled by job satisfaction, can resolve challenges, benefiting fitness centers regardless of size, age or gender diversity.

The study highlights the vital role of intrapreneurs in the fitness industry, advocating a nongender-biased approach to intrapreneurship and identifying job satisfaction as key to fostering intrapreneurial intentions, beneficial for all fitness centers.

This research aims to explore how social media influences the academic performance of university students in Bangladesh and examines the benefits and drawbacks of its usage.

We distributed a well-structured questionnaire among students enrolled in various programs at different universities in Bangladesh to collect data. We analyzed the data using factor analysis and regression models to uncover the impact of social media on academic performance.

Our research findings demonstrate that social media plays a crucial role in facilitating communication, information sharing and content development among university students in Bangladesh. Excessive reliance on social media can lead to dependence and hinder innovation, as students tend to excessively rely on readily available resources.

We relied on self-reported data from a limited sample size, which may affect the generalizability of our findings.

This study highlights the need to promote responsible use of social media among university students in Bangladesh to enhance their academic performance. We recommend implementing effective policy measures to control and manage undesired usage patterns, foster an intellectually equipped student body and contribute to the development of a knowledgeable and successful Bangladesh.

This research makes a significant contribution by examining the influence of social media on academic performance among university students in Bangladesh. It proposes practical policy measures to address the drawbacks associated with excessive reliance on social media, thereby contributing to decision-making and intervention strategies for promoting responsible usage.

The impact of stress on personal and work-related outcomes has been studied in the information systems (IS) literature across several professions. However, the cybersecurity profession has received little attention despite numerous reports suggesting stress is a leading cause of various adverse professional outcomes. Cybersecurity professionals work in a constantly changing adversarial threat landscape, are focused on enforcement rather than compliance, and are required to adhere to ever-changing industry mandates – a work environment that is stressful and has been likened to a war zone. Hence, this literature review aims to reveal gaps and trends in the current extant general workplace and IS-specific stress literature and illuminate potentially fruitful paths for future research focused on stress among cybersecurity professionals.

Using the systematic literature review process (Okoli and Schabram, 2010), the authors examined the current IS research that studies stress in organizations. A disciplinary corpus was generated from IS journals and conferences encompassing 30 years. The authors analyzed 293 articles from 21 journals and six conferences to retain 77 articles and four conference proceedings for literature review.

The findings reveal four key research opportunities. First, the demands experienced by cybersecurity professionals are distinct from the demands experienced by regular information technology (IT) professionals. Second, it is crucial to identify the appraisal process that cybersecurity professionals follow in assessing security demands. Third, there are many stress responses from cybersecurity professionals, not just negative responses. Fourth, future research should focus on stress-related outcomes such as employee productivity, job satisfaction, job turnover, etc., and not only security compliance among cybersecurity professionals.

This study is the first to provide a systematic synthesis of the IS stress literature to reveal gaps, trends and opportunities for future research focused on stress among cybersecurity professionals. The study presents several novel trends and research opportunities. It contends that the demands experienced by cybersecurity professionals are distinct from those experienced by regular IT professionals and scholars should seek to identify the key characteristics of these demands that influence their appraisal process. Also, there are many stress responses, not just negative responses, deserving increased attention and future research should focus on unexplored stress-related outcomes for cybersecurity professionals.

Simulation is a well-known technique for using computers to imitate or simulate the operations of various kinds of real-world facilities or processes. The facility or process of interest is usually called a system, and to study it scientifically, we often have to make a set of assumptions about how it works. These assumptions, which usually take the form of mathematical or logical relationships, constitute a model that is used to gain some understanding of how the corresponding system behaves, and the quality of these understandings essentially depends on the credibility of given assumptions or models, known as VV&A (verification, validation and accreditation). The main purpose of this paper is to present an in-depth theoretical review and analysis for the application of VV&A in large-scale simulations.

After summarizing the VV&A of related research studies, the standards, frameworks, techniques, methods and tools have been discussed according to the characteristics of large-scale simulations (such as crowd network simulations).

The contributions of this paper will be useful for both academics and practitioners for formulating VV&A in large-scale simulations (such as crowd network simulations).

This paper will help researchers to provide support of a recommendation for formulating VV&A in large-scale simulations (such as crowd network simulations).

The aim of this study is to investigate subject independent emotion recognition capabilities of EEG and peripheral physiological signals namely: electroocoulogram (EOG), electromyography (EMG), electrodermal activity (EDA), temperature, plethysmograph and respiration. The experiments are conducted on both modalities independently and in combination. This study arranges the physiological signals in order based on the prediction accuracy obtained on test data using time and frequency domain features.

DEAP dataset is used in this experiment. Time and frequency domain features of EEG and physiological signals are extracted, followed by correlation-based feature selection. Classifiers namely – Naïve Bayes, logistic regression, linear discriminant analysis, quadratic discriminant analysis, logit boost and stacking are trained on the selected features. Based on the performance of the classifiers on the test set, the best modality for each dimension of emotion is identified.

 The experimental results with EEG as one modality and all physiological signals as another modality indicate that EEG signals are better at arousal prediction compared to physiological signals by 7.18%, while physiological signals are better at valence prediction compared to EEG signals by 3.51%. The valence prediction accuracy of EOG is superior to zygomaticus electromyography (zEMG) and EDA by 1.75% at the cost of higher number of electrodes. This paper concludes that valence can be measured from the eyes (EOG) while arousal can be measured from the changes in blood volume (plethysmograph). The sorted order of physiological signals based on arousal prediction accuracy is plethysmograph, EOG (hEOG + vEOG), vEOG, hEOG, zEMG, tEMG, temperature, EMG (tEMG + zEMG), respiration, EDA, while based on valence prediction accuracy the sorted order is EOG (hEOG + vEOG), EDA, zEMG, hEOG, respiration, tEMG, vEOG, EMG (tEMG + zEMG), temperature and plethysmograph.

Many of the emotion recognition studies in literature are subject dependent and the limited subject independent emotion recognition studies in the literature report an average of leave one subject out (LOSO) validation result as accuracy. The work reported in this paper sets the baseline for subject independent emotion recognition using DEAP dataset by clearly specifying the subjects used in training and test set. In addition, this work specifies the cut-off score used to classify the scale as low or high in arousal and valence dimensions. Generally, statistical features are used for emotion recognition using physiological signals as a modality, whereas in this work, time and frequency domain features of physiological signals and EEG are used. This paper concludes that valence can be identified from EOG while arousal can be predicted from plethysmograph.